banner-in1

10 Current Database Research Topic Ideas in 2024

Home Blog Database 10 Current Database Research Topic Ideas in 2024

Play icon

As we head towards the second half of 2024, the world of technology evolves at a rapid pace. With the rise of AI and blockchain, the demand for data, its management and the need for security increases rapidly. A logical consequence of these changes is the way fields like database security research topics and DBMS research have come up as the need of the hour.

With new technologies and techniques emerging day-by-day, staying up-to-date with the latest trends in database research topics is crucial. Whether you are a student, researcher, or industry professional, we recommend taking our Database Certification courses to stay current with the latest research topics in DBMS.

In this blog post, we will introduce you to 10 current database research topic ideas that are likely to be at the forefront of the field in 2024. From blockchain-based database systems to real-time data processing with in-memory databases, these topics offer a glimpse into the exciting future of database research.

So, get ready to dive into the exciting world of databases and discover the latest developments in database research topics of 2024!

Blurring the Lines between Blockchains and Database Systems 

The intersection of blockchain technology and database systems offers fertile new grounds to anyone interested in database research.

As blockchain gains popularity, many thesis topics in DBMS[1] are exploring ways to integrate both fields. This research will yield innovative solutions for data management. Here are 3 ways in which these two technologies are being combined to create powerful new solutions:

Immutable Databases: By leveraging blockchain technology, it’s possible to create databases to be immutable. Once data has been added to such a database, it cannot be modified or deleted. This is particularly useful in situations where data integrity is critical, such as in financial transactions or supply chain management.

Decentralized Databases: Blockchain technology enables the creation of decentralized databases. Here data is stored on a distributed network of computers rather than in a central location. This can help to improve data security and reduce the risk of data loss or corruption.

Smart Contracts: Smart contracts are self-executing contracts with the terms of the agreement between buyer and seller being directly written into lines of code. By leveraging blockchain technology, it is possible to create smart contracts that are stored and executed on a decentralized database, making it possible to automate a wide range of business processes.

Childhood Obesity: Data Management 

Childhood obesity is a growing public health concern, with rates of obesity among children and adolescents rising around the world. To address this issue, it’s crucial to have access to comprehensive data on childhood obesity. Analyzing information on prevalence, risk factors, and interventions is a popular research topic in DBMS these days.

Effective data management is essential for ensuring that this information is collected, stored, and analyzed in a way that is useful and actionable. This is one of the hottest DBMS research paper topics. In this section, we will explore the topic of childhood obesity data management.

A key challenge to childhood obesity data management is ensuring data consistency. This is difficult as various organizations have varied methods for measuring and defining obesity. For example:

Some may use body mass index (BMI) as a measure of obesity.

Others may use waist circumference or skinfold thickness.   Another challenge is ensuring data security and preventing unauthorized access. To protect the privacy and confidentiality of individuals, it is important to ensure appropriate safeguards are in place. This calls for database security research and appropriate application.

Application of Computer Database Technology in Marketing

Leveraging data and analytics allows businesses to gain a competitive advantage in this digitized world today. With the rising demand for data, the use of computer databases in marketing has gained prominence.

The application of database capabilities in marketing has really come into its own as one of the most popular and latest research topics in DBMS[2]. In this section, we will explore how computer database technology is being applied in marketing, and the benefits this research can offer.

Customer Segmentation: Storage and analysis of customer data makes it possible to gain valuable insights. It allows businesses to identify trends in customer behavior, preferences and demographics. This information can be utilized to create highly targeted customer segments. This is how businesses can tailor their marketing efforts to specific groups of customers.

Personalization: Computer databases can be used to store and analyze customer data in real-time. In this way, businesses can personalize their marketing and offers based on individual customer preferences. This can help increase engagement and loyalty among customers, thereby driving greater revenue for businesses.

Predictive Analytics: Advanced analytics techniques such as machine learning and predictive modeling can throw light on patterns in customer behavior. This can even be used to predict their future actions. This information can be used to create more targeted marketing campaigns, and to identify opportunities for cross-selling and upselling.

Database Technology in Sports Competition Information Management

Database technology has revolutionized the way in which sports competition information is managed and analyzed. With the increasing popularity of sports around the world, there is a growing need for effective data management systems that can collect, store, and analyze large volumes of relevant data. Thus, researching database technologies[3] is vital to streamlining operations, improving decision-making, and enhancing the overall quality of events.

Sports organizations can use database technology to collect and manage a wide range of competition-related data such as: 

Athlete and team information,

competition schedules and results,

performance metrics, and

spectator feedback.

Collating this data in a distributed database lets sports organizations easily analyze and derive valuable insights. This is emerging as a key DBMS research paper topic.

Database Technology for the Analysis of Spatio-temporal Data

Spatio-temporal data refers to data which has a geographic as well as a temporal component. Meteorological readings, GPS data, and social media content are prime examples of this diverse field. This data can provide valuable insights into patterns and trends across space and time. However, its multidimensional nature makes analysis be super challenging. It’s no surprise that this has become a hot topic for distributed database research[4].

In this section, we will explore how database technology is being used to analyze spatio-temporal data, and the benefits this research offers.

Data Storage and Retrieval: Spatio-temporal data tends to be very high-volume. Advances in database technology are needed to make storage, retrieval and consumption of such information more efficient. A solution to this problem will make such data more available. It will then be easily retrievable and usable by a variety of data analytics tools.

Spatial Indexing: Database technology can create spatial indexes to enable faster queries on spatio-temporal data. This allows analysts to quickly retrieve data for specific geographic locations or areas of interest, and to analyze trends across these areas.

Temporal Querying: Distributed database research can also enable analysts to analyze data over specific time periods. This facilitates the identification of patterns over time. Ultimately, this enhances our understanding of how these patterns evolve over various seasons.

Artificial Intelligence and Database Technology

Artificial intelligence (AI) is another sphere of technology that’s just waiting to be explored. It hints at a wealth of breakthroughs which can change the entire world. It’s unsurprising that the combination of AI with database technology is such a hot topic for database research papers[5] in modern times. 

By using AI to analyze data, organizations can identify patterns and relationships that might not be apparent through traditional data analysis methods. In this section, we will explore some of the ways in which AI and database technology are being used together. We’ll also discuss the benefits that this amalgamation can offer.

Predictive Analytics: By analyzing large volumes of organizational and business data, AI can generate predictive models to forecast outcomes. For example, AI can go through customer data stored in a database and predict who is most likely to make a purchase in the near future.

Natural Language Processing: All businesses have huge, untapped wells of valuable information in the form of customer feedback and social media posts. These types of data sources are unstructured, meaning they don’t follow rigid parameters. By using natural language processing (NLP) techniques, AI can extract insights from this data. This helps organizations understand customer sentiment, preferences and needs.

Anomaly Detection: AI can be used to analyze large volumes of data to identify anomalies and outliers. Then, a second round of analysis can be done to pinpoint potential problems or opportunities. For example, AI can analyze sensor data from manufacturing equipment and detect when equipment is operating outside of normal parameters.

Data Collection and Management Techniques of a Qualitative Research Plan

Any qualitative research calls for the collection and management of empirical data. A crucial part of the research process, this step benefits from good database management techniques. Let’s explore some thesis topics in database management systems[6] to ensure the success of a qualitative research plan.

Interviews: This is one of the most common methods of data collection in qualitative research. Interviews can be conducted in person, over the phone, or through video conferencing. A standardized interview guide ensures the data collected is reliable and accurate. Relational databases, with their inherent structure, aid in this process. They are a way to enforce structure onto the interviews’ answers.

Focus Groups: Focus groups involve gathering a small group of people to discuss a particular topic. These generate rich data by allowing participants to share their views in a group setting. It is important to select participants who have knowledge or experience related to the research topic.

Observations: Observations involve observing and recording events in a given setting. These can be conducted openly or covertly, depending on the research objective and setting. To ensure that the data collected is accurate, it is important to develop a detailed observation protocol that outlines what behaviors or events to observe, how to record data, and how to handle ethical issues.

Database Technology in Video Surveillance System 

Video surveillance systems are used to monitor and secure public spaces, workplaces, even homes. With the increasing demand for such systems, it’s important to have an efficient and reliable way to store, manage and analyze the data generated. This is where database topics for research paper [7] come in.

By using database technology in video surveillance systems, it is possible to store and manage large amounts of video data efficiently. Database management systems (DBMS) can be used to organize video data in a way that is easily searchable and retrievable. This is particularly important in cases where video footage is needed as evidence in criminal investigations or court cases.

In addition to storage and management, database technology can also be used to analyze video data. For example, machine learning algorithms can be applied to video data to identify patterns and anomalies that may indicate suspicious activity. This can help law enforcement agencies and security personnel to identify and respond to potential threats more quickly and effectively.

Application of Java Technology in Dynamic Web Database Technology 

Java technology has proven its flexibility, scalability, and ease of use over the decades. This makes it widely used in the development of dynamic web database applications. In this section, we will explore research topics in DBMS[8] which seek to apply Java technology in databases.

Java Server Pages (JSP): JSP is a Java technology that is used to create dynamic web pages that can interact with databases. It allows developers to embed Java code within HTML scripts, thereby enabling dynamic web pages. These can interact with databases in real-time, and aid in data collection and maintenance.

Java Servlets: Java Servlets are Java classes used to extend the functionality of web servers. They provide a way to handle incoming requests from web browsers and generate dynamic content that can interact with databases.

Java Database Connectivity (JDBC): JDBC is a Java API that provides a standard interface for accessing databases. It allows Java applications to connect to databases. It can SQL queries to enhance, modify or control the backend database. This enables developers to create dynamic web applications.

Online Multi Module Educational Administration System Based on Time Difference Database Technology 

With the widespread adoption of remote learning post-COVID, online educational systems are gaining popularity at a rapid pace. A ubiquitous challenge these systems face is managing multiple modules across different time zones. This is one of the latest research topics in database management systems[9].

Time difference database technology is designed to handle time zone differences in online systems. By leveraging this, it’s possible to create a multi-module educational administration system that can handle users from different parts of the world, with different time zones.

This type of system can be especially useful for online universities or other educational institutions that have a global reach:

It makes it possible to schedule classes, assignments and other activities based on the user's time zone, ensuring that everyone can participate in real-time.

In addition to managing time zones, a time difference database system can also help manage student data, course materials, grades, and other important information.

Why is it Important to Study Databases?

Databases are the backbone of many modern technologies and applications, making it essential for professionals in various fields to understand how they work. Whether you're a software developer, data analyst or a business owner, understanding databases is critical to success in today's world. Here are a few reasons why it is important to study databases and more database topics for research paper should be published:

Efficient Data Management

Databases enable the efficient storage, organization, and retrieval of data. By studying databases, you can learn how to design and implement effective data management systems that can help organizations store, analyze, and use data efficiently.

Improved Decision-Making

Data is essential for making informed decisions, and databases provide a reliable source of data for analysis. By understanding databases, you can learn how to retrieve and analyze data to inform business decisions, identify trends, and gain insights.

Career Opportunities

In today's digital age, many career paths require knowledge of databases. By studying databases, you can open up new career opportunities in software development, data analysis, database administration and related fields.

Needless to say, studying databases is essential for anyone who deals with data. Whether you're looking to start a new career or enhance your existing skills, studying databases is a critical step towards success in today's data-driven world.

Final Takeaways

In conclusion, as you are interested in database technology, we hope this blog has given you some insights into the latest research topics in the field. From blockchain to AI, from sports to marketing, there are a plethora of exciting database topics for research papers that will shape the future of database technology.

As technology continues to evolve, it is essential to stay up-to-date with the latest trends in the field of databases. Our curated KnowledgeHut Database Certification Courses will help you stay ahead of the curve and develop new skills.

We hope this blog has inspired you to explore the exciting world of database research in 2024. Stay curious and keep learning!

Frequently Asked Questions (FAQs)

There are several examples of databases, with the five most common ones being:

MySQL : An open-source RDBMS used commonly in web applications.

Microsoft SQL Server : A popular RDBMS used in enterprise environments.

Oracle : A trusted commercial RDBMS famous for its high-scalability and security.

MongoDB : A NoSQL document-oriented database optimized for storing large amounts of unstructured data.

PostgreSQL : An open-source RDBMS offering advanced features like high concurrency and support for multiple data types.

Structured Query Language (SQL) is a high-level language designed to communicate with relational databases. It’s not a database in and of itself. Rather, it’s a language used to create, modify, and retrieve data from relational databases such as MySQL and Oracle.

A primary key is a column (or a set of columns) that uniquely identifies each row in a table. In technical terms, the primary key is a unique identifier of records. It’s used as a reference to establish relationships between various tables.

Profile

Spandita Hati

Spandita is a dynamic content writer who holds a master's degree in Forensics but loves to play with words and dabble in digital marketing. Being an avid travel blogger, she values engaging content that attracts, educates and inspires. With extensive experience in SEO tools and technologies, her writing interests are as varied as the articles themselves. In her leisure, she consumes web content and books in equal measure.

Avail your free 1:1 mentorship session.

Something went wrong

Upcoming Database Batches & Dates

Chat icon for mobile

67 Data Management Essay Topics & Database Research Topics

🏆 best database research topics, ✍️ data management essay topics for college, 🎓 most interesting database topics for research paper, 💡 simple data management systems essay topics.

  • Database Management Systems’ Major Capabilities
  • Relational Database Management Systems in Business
  • Data Assets Management of LuLu Hypermarkets System
  • Big Data Opportunities in Green Supply Chain Management
  • Information Technology-Based Data Management in Retail
  • Object-Oriented and Database Management Systems Tradeoffs
  • EHR Database Management: Diabetes Prevention
  • Why Open-Source Software Will (Or Will Not) Soon Dominate the Field of Database Management Tools The study aims at establishing whether open-source software will dominate the database field because there has been a changing trend in the business market.
  • Modern Data Management and Organization Strategies Today, with a shrinking focus on data and analytics, a proper data management strategy is imperative to meeting business goals.
  • Data Management in a Medium-Sized Business This paper will use a medium-sized business data management offering highly specialized, high-quality business development education services as an example.
  • Electronic Health Record Database and Data Management Progress in modern medicine has resulted in the amount of information related to the health of patients to grow exponentially.
  • Data Management and Financial Strategies By adopting comprehensive supply chain management, businesses can maximize the three main streams in the supply chain— information flow, product flow, and money flow.
  • Policy on People Data Management Law No. (13) of 2016 is a data protection legislation that applies to all public institutions and private organizations across Qatar.
  • The Choice of a Medical Data Management System The choice of a medical data management system is critically important for any organization providing healthcare services.
  • Data Analytics and Its Application to Management The role of the collection of data and its subsequent analysis in the industry is as big as ever. Specifically, it pertains to the managerial field.
  • Technology-Assisted Reviews of Data in a Document Management System The TAR that is used in DMS falls into two major categories. These are automatic TAR and semi-automatic TAR, where the last implies the intervention of a human reviewer.
  • Data Collection and Management Techniques for a Qualitative Research Plan To conduct complete qualitative research and present a cohesive qualitative research plan, it is necessary to match the structure and topic of the study.
  • Database Management and Machine Learning Machine learning is used in science, business, industry, healthcare, education, etc. The possibilities of using machine learning technologies are constantly expanding.
  • Data Collection and Management Techniques of a Qualitative Research Plan This research paper recommends interview method in the collection of data and the application of NVivo statistical software in the management of data.
  • Big Data Management Research This paper will present a literature review of three articles that examine text mining methods for quantitative analysis.
  • Big Data Fraud Management The growth of eCommerce systems has led to an increase in online transactions using credit cards and other methods of payment services.
  • Deli Depot Case Study: Data Analysis Management Reporting To improve customer service, Deli Depot has embarked on initiatives to better understand its customers. The company did market research using a questionnaire-based survey.
  • Data Storage Management Solutions: Losses of Personal Data The term data refers to a collection of facts about anything. As it is often said, processed data results to information and he who has information has power.
  • Data Management, Networking and Enterprise Software Enterprise software is often created “in-house” and thus has a far higher cost as compared to simply buying the software solution from another company.
  • Childhood Obesity: Data Management The use of electronic health records (EHR) is regarded as one of the effective ways to treat obesity in the population.
  • Health Data Management: Sharing and Saving Patient Data One of the ways to facilitate achieving the idealized environment of data sharing is developing the methods of accessing health-related information.
  • Big Data Usage in Supply Chain Management This paper gives a summary of the research that was conducted to understand the unique issues surrounding the use of big data in the supply chain.
  • Adopting Electronic Data Management in the Health Care Industry
  • Distributed Operating System and Infrastructure for Scientific Data Management
  • Advanced Drill Data Management Solutions Market: Growth and Forecast
  • The Changing Role of Data Management in Clinical Trials
  • Business Rules and Their Relationship to Effective Data Management
  • Class Enterprise Data Management and Administration
  • Developing Highly Scalable and Autonomic Data Management
  • Cloud Computing: Installation and Maintenance of Energy Efficient Data Management
  • Exploring, Mapping, and Data Management Integration of Habitable Environments in Astrobiology
  • Data Management: Data Warehousing and Data Mining
  • Efficient Algorithmic Techniques for Several Multidimensional Geometric Data Management and Analysis Problems
  • Data Management for Photovoltaic Power Plants Operation and Maintenance
  • Elderly Patients and Falls: Adverse Trends and Data Management
  • Data Management for Pre- and Post-Release Workforce Services
  • Epidemiological Data Management During an Outbreak of Ebola Virus Disease
  • Dealing With Identifier Variables in Data Management and Analysis
  • How Data Mining, Data Warehousing, and On-Line Transactional Databases Are Helping Solve the Data Management Predicament
  • Improving the New Data Management Technologies and Leverage
  • Integrated Process and Data Management for Healthcare Applications
  • Making Data Management Manageable: A Risk Assessment Activity for Managing Research Data
  • The Use of Temporal Database in the Data Management System
  • Multi-Cloud Data Management Using Shamir’s Secret Sharing and Quantum Byzantine Agreement Schemes
  • Data Management Is More Than Just Managing Data
  • Is Effective Data Management a Key Driver of Business Success?
  • National Data Centre and Financial Statistics Office: A Conceptual Design for Public Data Management
  • Big Data Management and Relevance of Big Data to E-Business
  • Redefining the Data Management Strategy: A Way to Leverage the Huge Chunk of Data
  • Structured Data Management Software Market in Taiwan
  • Towards Effective GML Data Management: Framework and Prototype
  • Data Management in Cloud Environments
  • Digital Communication: Enterprise Data Management
  • The Impact of Big Data on Data Management Functions
  • Analysis of Data Management Strategies at Tesco
  • The Best Data Management Tools Overview
  • What Is Data Management and Why Is It Important
  • Data Management and Use: Governance in the 21st Century
  • What Is Data Management and How Do Businesses Use It?
  • The Difference Between Data Management and Data Governance
  • Types of Data Management Systems for Data-First Marketing Strategies and Success
  • Reasons Why Data Management Leads to Business Success

Cite this post

  • Chicago (N-B)
  • Chicago (A-D)

StudyCorgi. (2022, June 5). 67 Data Management Essay Topics & Database Research Topics. Retrieved from https://studycorgi.com/ideas/data-management-essay-topics/

StudyCorgi. (2022, June 5). 67 Data Management Essay Topics & Database Research Topics. https://studycorgi.com/ideas/data-management-essay-topics/

"67 Data Management Essay Topics & Database Research Topics." StudyCorgi , 5 June 2022, studycorgi.com/ideas/data-management-essay-topics/.

1. StudyCorgi . "67 Data Management Essay Topics & Database Research Topics." June 5, 2022. https://studycorgi.com/ideas/data-management-essay-topics/.

Bibliography

StudyCorgi . "67 Data Management Essay Topics & Database Research Topics." June 5, 2022. https://studycorgi.com/ideas/data-management-essay-topics/.

StudyCorgi . 2022. "67 Data Management Essay Topics & Database Research Topics." June 5, 2022. https://studycorgi.com/ideas/data-management-essay-topics/.

StudyCorgi . (2022) '67 Data Management Essay Topics & Database Research Topics'. 5 June.

These essay examples and topics on Data Management were carefully selected by the StudyCorgi editorial team. They meet our highest standards in terms of grammar, punctuation, style, and fact accuracy. Please ensure you properly reference the materials if you’re using them to write your assignment.

This essay topic collection was updated on December 27, 2023 .

Database Search

What is Database Search?

Harvard Library licenses hundreds of online databases, giving you access to academic and news articles, books, journals, primary sources, streaming media, and much more.

The contents of these databases are only partially included in HOLLIS. To make sure you're really seeing everything, you need to search in multiple places. Use Database Search to identify and connect to the best databases for your topic.

In addition to digital content, you will find specialized search engines used in specific scholarly domains.

Related Services & Tools

Database Management Systems (DBMS)

Database group website: db.cs.berkeley.edu

Declarative languages and runtime systems

Design and implementation of declarative programming languages with applications to distributed systems, networking, machine learning, metadata management, and interactive visualization; design of query interface for applications.

Scalable data analysis and query processing

Scalable data processing in new settings, including interactive exploration, metadata management, cloud and serverless environments, and machine learning; query processing on compressed, semi-structured, and streaming data; query processing with additional constraints, including fairness, resource utilization, and cost.

Consistency, concurrency, coordination and reliability

Coordination avoidance, consistency and monotonicity analysis; transaction isolation levels and protocols; distributed analytics and data management, geo-replication; fault tolerance and fault injection.

Data storage and physical design

Hot and cold storage; immutable data structures; indexing and data skipping; versioning; new data types; implications of hardware evolution.

Metadata management

Data lineage and versioning; usage tracking and collective intelligence; scalability of metadata management services; metadata representations; reproducibility and debugging of data pipelines.

Systems for machine learning and model management

Distributed machine learning and graph analytics; physical and logical optimization of machine learning pipelines; online model management and maintenance; prediction serving; real-time personalization; latency-accuracy tradeoffs and edge computing for large-scale models; machine learning lifecycle management.

Data cleaning, data transformation, and crowdsourcing

Human-data interaction including interactive transformation, query authoring, and crowdsourcing; machine learning for data cleaning; statistical properties of data cleaning pipelines; end-to-end systems for crowdsourcing.

Interactive data exploration and visualization

Interactive querying and direct manipulation; scalable spreadsheets and data visualization; languages and interfaces for interactive exploration; progressive query visualization; predictive interaction.

Secure data processing

Data processing under homomorphic encryption; data compression and encryption; differential privacy; oblivious data processing; databases in secure hardware enclaves.

Foundations of data management

Optimal trade-offs between storage, quality, latency, and cost, with applications to crowdsourcing, distributed data management, stream data processing, version management; expressiveness, complexity, and completeness of data representations, query languages, and query processing; query processing with fairness constraints.

Research Centers

  • EPIC Data lab
  • Sky Computing Lab
  • Alvin Cheung
  • Natacha Crooks
  • Joseph Gonzalez
  • Joseph M. Hellerstein (coordinator)
  • Jiantao Jiao
  • Aditya Parameswaran
  • Matei Zaharia
  • Eric Brewer
  • Michael Lustig
  • Jelani Nelson

Faculty Awards

  • ACM Prize in Computing: Eric Brewer, 2009.
  • National Academy of Engineering (NAE) Member: Ion Stoica, 2024. Eric Brewer, 2007.
  • American Academy of Arts and Sciences Member: Eric Brewer, 2018.
  • Sloan Research Fellow: Aditya Parameswaran, 2020. Alvin Cheung, 2019. Jelani Nelson, 2017. Michael Lustig, 2013. Ion Stoica, 2003. Joseph M. Hellerstein, 1998. Eric Brewer, 1997.

Related Courses

  • CS 186. Introduction to Database Systems
  • CS 262A. Advanced Topics in Computer Systems

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

  • Knowledge Base
  • Working with sources

How to Find Sources | Scholarly Articles, Books, Etc.

Published on June 13, 2022 by Eoghan Ryan . Revised on May 31, 2023.

It’s important to know how to find relevant sources when writing a  research paper , literature review , or systematic review .

The types of sources you need will depend on the stage you are at in the research process , but all sources that you use should be credible , up to date, and relevant to your research topic.

There are three main places to look for sources to use in your research:

Research databases

  • Your institution’s library
  • Other online resources

Table of contents

Library resources, other online sources, other interesting articles, frequently asked questions about finding sources.

You can search for scholarly sources online using databases and search engines like Google Scholar . These provide a range of search functions that can help you to find the most relevant sources.

If you are searching for a specific article or book, include the title or the author’s name. Alternatively, if you’re just looking for sources related to your research problem , you can search using keywords. In this case, it’s important to have a clear understanding of the scope of your project and of the most relevant keywords.

Databases can be general (interdisciplinary) or subject-specific.

  • You can use subject-specific databases to ensure that the results are relevant to your field.
  • When using a general database or search engine, you can still filter results by selecting specific subjects or disciplines.

Example: JSTOR discipline search filter

Filtering by discipline

Check the table below to find a database that’s relevant to your research.

Google Scholar

To get started, you might also try Google Scholar , an academic search engine that can help you find relevant books and articles. Its “Cited by” function lets you see the number of times a source has been cited. This can tell you something about a source’s credibility and importance to the field.

Example: Google Scholar “Cited by” function

Google Scholar cited by function

Boolean operators

Boolean operators can also help to narrow or expand your search.

Boolean operators are words and symbols like AND , OR , and NOT that you can use to include or exclude keywords to refine your results. For example, a search for “Nietzsche NOT nihilism” will provide results that include the word “Nietzsche” but exclude results that contain the word “nihilism.”

Many databases and search engines have an advanced search function that allows you to refine results in a similar way without typing the Boolean operators manually.

Example: Project Muse advanced search

Project Muse advanced search

Scribbr Citation Checker New

The AI-powered Citation Checker helps you avoid common mistakes such as:

  • Missing commas and periods
  • Incorrect usage of “et al.”
  • Ampersands (&) in narrative citations
  • Missing reference entries

database topics for research paper

You can find helpful print sources in your institution’s library. These include:

  • Journal articles
  • Encyclopedias
  • Newspapers and magazines

Make sure that the sources you consult are appropriate to your research.

You can find these sources using your institution’s library database. This will allow you to explore the library’s catalog and to search relevant keywords. You can refine your results using Boolean operators .

Once you have found a relevant print source in the library:

  • Consider what books are beside it. This can be a great way to find related sources, especially when you’ve found a secondary or tertiary source instead of a primary source .
  • Consult the index and bibliography to find the bibliographic information of other relevant sources.

You can consult popular online sources to learn more about your topic. These include:

  • Crowdsourced encyclopedias like Wikipedia

You can find these sources using search engines. To refine your search, use Boolean operators in combination with relevant keywords.

However, exercise caution when using online sources. Consider what kinds of sources are appropriate for your research and make sure the sites are credible .

Look for sites with trusted domain extensions:

  • URLs that end with .edu are educational resources.
  • URLs that end with .gov are government-related resources.
  • DOIs often indicate that an article is published in a peer-reviewed , scientific article.

Other sites can still be used, but you should evaluate them carefully and consider alternatives.

If you want to know more about ChatGPT, AI tools , citation , and plagiarism , make sure to check out some of our other articles with explanations and examples.

  • ChatGPT vs human editor
  • ChatGPT citations
  • Is ChatGPT trustworthy?
  • Using ChatGPT for your studies
  • What is ChatGPT?
  • Chicago style
  • Paraphrasing

 Plagiarism

  • Types of plagiarism
  • Self-plagiarism
  • Avoiding plagiarism
  • Academic integrity
  • Consequences of plagiarism
  • Common knowledge

Prevent plagiarism. Run a free check.

You can find sources online using databases and search engines like Google Scholar . Use Boolean operators or advanced search functions to narrow or expand your search.

For print sources, you can use your institution’s library database. This will allow you to explore the library’s catalog and to search relevant keywords.

It is important to find credible sources and use those that you can be sure are sufficiently scholarly .

  • Consult your institute’s library to find out what books, journals, research databases, and other types of sources they provide access to.
  • Look for books published by respected academic publishing houses and university presses, as these are typically considered trustworthy sources.
  • Look for journals that use a peer review process. This means that experts in the field assess the quality and credibility of an article before it is published.

When searching for sources in databases, think of specific keywords that are relevant to your topic , and consider variations on them or synonyms that might be relevant.

Once you have a clear idea of your research parameters and key terms, choose a database that is relevant to your research (e.g., Medline, JSTOR, Project MUSE).

Find out if the database has a “subject search” option. This can help to refine your search. Use Boolean operators to combine your keywords, exclude specific search terms, and search exact phrases to find the most relevant sources.

There are many types of sources commonly used in research. These include:

You’ll likely use a variety of these sources throughout the research process , and the kinds of sources you use will depend on your research topic and goals.

Scholarly sources are written by experts in their field and are typically subjected to peer review . They are intended for a scholarly audience, include a full bibliography, and use scholarly or technical language. For these reasons, they are typically considered credible sources .

Popular sources like magazines and news articles are typically written by journalists. These types of sources usually don’t include a bibliography and are written for a popular, rather than academic, audience. They are not always reliable and may be written from a biased or uninformed perspective, but they can still be cited in some contexts.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Ryan, E. (2023, May 31). How to Find Sources | Scholarly Articles, Books, Etc.. Scribbr. Retrieved February 22, 2024, from https://www.scribbr.com/working-with-sources/finding-sources/

Is this article helpful?

Eoghan Ryan

Eoghan Ryan

Other students also liked, types of sources explained | examples & tips, primary vs. secondary sources | difference & examples, boolean operators | quick guide, examples & tips.

Information

  • Eugene Wu (Instructor) OH: TBA 421 Mudd
  • Class: Th 2-4PM
  • Syllabus & FAQ
  • Reviews Wiki
  • Req: W4111 Intro to DB
  • Pref: W4112 DB Impl
  • Ugrads OK; see Prof Wu
  • Proposal 5%
  • Paper Draft 10%
  • Demo/Poster 10%
  • Participation 10% <!–
  • Paper Reviews 10%
  • Assignments 15% –>

Data management systems are the corner-stone of modern applications, businesses, and science (including data). If you were excited by the topics in 4111, this graduate level course in database systems research will be a deep dive into classic and modern database systems research. Topics will range from classic database system design, modern optimizations in single-machine and multi-machine settings, data cleaning and quality, and application-oriented databases. This semester’s theme will look at how learning has affected many classic data management systems challenges, and also how data management systems support and extends ML needs.

See FAQ for difference between 6113 and the other database courses.

  • Class: Th 2-4PM in 829 Mudd
  • Instructor: Eugene Wu , OH: Thurs 12-1PM 421 Mudd
  • Syllabus & FAQ , Slack , Project , Papers
  • Prereqs: W4111 Intro to DB (required), W4112 DB Implementations (recommended). Ugrads OK; see Prof Wu
  • Discussion Prep 30%
  • Class participation 30%
  • Project 40%: Final Presentation 10% , Paper 30%

Recent Announcements

Tentative schedule.

Course design inspired by

  • Cal’s CS286
  • Waterloo’s CS848
  • Colin Raffel’s Role playing seminar
  • Carl Vondrick’s self supervision graduate seminar

U.S. flag

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • Publications
  • Account settings
  • Advanced Search
  • Journal List
  • Springer Nature - PMC COVID-19 Collection

Logo of phenaturepg

Advances in database systems education: Methods, tools, curricula, and way forward

Muhammad ishaq.

1 Department of Computer Science, National University of Computer and Emerging Sciences, Lahore, Pakistan

2 Department of Computer Science, Virtual University of Pakistan, Lahore, Pakistan

3 Department of Computer Science, University of Management and Technology, Lahore, Pakistan

Muhammad Shoaib Farooq

Muhammad faraz manzoor.

4 Department of Computer Science, Lahore Garrison University, Lahore, Pakistan

Uzma Farooq

Kamran abid.

5 Department of Electrical Engineering, University of the Punjab, Lahore, Pakistan

Mamoun Abu Helou

6 Faculty of Information Technology, Al Istiqlal University, Jericho, Palestine

Associated Data

Not Applicable.

Fundamentals of Database Systems is a core course in computing disciplines as almost all small, medium, large, or enterprise systems essentially require data storage component. Database System Education (DSE) provides the foundation as well as advanced concepts in the area of data modeling and its implementation. The first course in DSE holds a pivotal role in developing students’ interest in this area. Over the years, the researchers have devised several different tools and methods to teach this course effectively, and have also been revisiting the curricula for database systems education. In this study a Systematic Literature Review (SLR) is presented that distills the existing literature pertaining to the DSE to discuss these three perspectives for the first course in database systems. Whereby, this SLR also discusses how the developed teaching and learning assistant tools, teaching and assessment methods and database curricula have evolved over the years due to rapid change in database technology. To this end, more than 65 articles related to DSE published between 1995 and 2022 have been shortlisted through a structured mechanism and have been reviewed to find the answers of the aforementioned objectives. The article also provides useful guidelines to the instructors, and discusses ideas to extend this research from several perspectives. To the best of our knowledge, this is the first research work that presents a broader review about the research conducted in the area of DSE.

Introduction

Database systems play a pivotal role in the successful implementation of the information systems to ensure the smooth running of many different organizations and companies (Etemad & Küpçü, 2018 ; Morien, 2006 ). Therefore, at least one course about the fundamentals of database systems is taught in every computing and information systems degree (Nagataki et al., 2013 ). Database System Education (DSE) is concerned with different aspects of data management while developing software (Park et al., 2017 ). The IEEE/ACM computing curricula guidelines endorse 30–50 dedicated hours for teaching fundamentals of design and implementation of database systems so as to build a very strong theoretical and practical understanding of the DSE topics (Cvetanovic et al., 2010 ).

Practically, most of the universities offer one user-oriented course at undergraduate level that covers topics related to the data modeling and design, querying, and a limited number of hours on theory (Conklin & Heinrichs, 2005 ; Robbert & Ricardo, 2003 ), where it is often debatable whether to utilize a design-first or query-first approach. Furthermore, in order to update the course contents, some recent trends, including big data and the notion of NoSQL should also be introduced in this basic course (Dietrich et al., 2008 ; Garcia-Molina, 2008 ). Whereas, the graduate course is more theoretical and includes topics related to DB architecture, transactions, concurrency, reliability, distribution, parallelism, replication, query optimization, along with some specialized classes.

Researchers have designed a variety of tools for making different concepts of introductory database course more interesting and easier to teach and learn interactively (Brusilovsky et al., 2010 ) either using visual support (Nagataki et al., 2013 ), or with the help of gamification (Fisher & Khine, 2006 ). Similarly, the instructors have been improvising different methods to teach (Abid et al., 2015 ; Domínguez & Jaime, 2010 ) and evaluate (Kawash et al., 2020 ) this theoretical and practical course. Also, the emerging and hot topics such as cloud computing and big data has also created the need to revise the curriculum and methods to teach DSE (Manzoor et al., 2020 ).

The research in database systems education has evolved over the years with respect to modern contents influenced by technological advancements, supportive tools to engage the learners for better learning, and improvisations in teaching and assessment methods. Particularly, in recent years there is a shift from self-describing data-driven systems to a problem-driven paradigm that is the bottom-up approach where data exists before being designed. This mainly relies on scientific, quantitative, and empirical methods for building models, while pushing the boundaries of typical data management by involving mathematics, statistics, data mining, and machine learning, thus opening a multidisciplinary perspective. Hence, it is important to devote a few lectures to introducing the relevance of such advance topics.

Researchers have provided useful review articles on other areas including Introductory Programming Language (Mehmood et al., 2020 ), use of gamification (Obaid et al., 2020 ), research trends in the use of enterprise service bus (Aziz et al., 2020 ), and the role of IoT in agriculture (Farooq et al., 2019 , 2020 ) However, to the best of our knowledge, no such study was found in the area of database systems education. Therefore, this study discusses research work published in different areas of database systems education involving curricula, tools, and approaches that have been proposed to teach an introductory course on database systems in an effective manner. The rest of the article has been structured in the following manner: Sect.  2 presents related work and provides a comparison of the related surveys with this study. Section  3 presents the research methodology for this study. Section  4 analyses the major findings of the literature reviewed in this research and categorizes it into different important aspects. Section  5 represents advices for the instructors and future directions. Lastly, Sect.  6 concludes the article.

Related work

Systematic Literature Reviews have been found to be a very useful artifact for covering and understanding a domain. A number of interesting review studies have been found in different fields (Farooq et al., 2021 ; Ishaq et al., 2021 ). Review articles are generally categorized into narrative or traditional reviews (Abid et al., 2016 ; Ramzan et al., 2019 ), systematic literature review (Naeem et al., 2020 ) and meta reviews or mapping study (Aria & Cuccurullo, 2017 ; Cobo et al., 2012 ; Tehseen et al., 2020 ). This study presents a systematic literature review on database system education.

The database systems education has been discussed from many different perspectives which include teaching and learning methods, curriculum development, and the facilitation of instructors and students by developing different tools. For instance, a number of research articles have been published focusing on developing tools for teaching database systems course (Abut & Ozturk, 1997 ; Connolly et al., 2005 ; Pahl et al., 2004 ). Furthermore, few authors have evaluated the DSE tools by conducting surveys and performing empirical experiments so as to gauge the effectiveness of these tools and their degree of acceptance among important stakeholders, teachers and students (Brusilovsky et al., 2010 ; Nelson & Fatimazahra, 2010 ). On the other hand, some case studies have also been discussed to evaluate the effectiveness of the improvised approaches and developed tools. For example, Regueras et al. ( 2007 ) presented a case study using the QUEST system, in which e-learning strategies are used to teach the database course at undergraduate level, while, Myers and Skinner ( 1997 ) identified the conflicts that arise when theories in text books regarding the development of databases do not work on specific applications.

Another important facet of DSE research focuses on the curriculum design and evolution for database systems, whereby (Alrumaih, 2016 ; Bhogal et al., 2012 ; Cvetanovic et al., 2010 ; Sahami et al., 2011 ) have proposed solutions for improvements in database curriculum for the better understanding of DSE among the students, while also keeping the evolving technology into the perspective. Similarly, Mingyu et al. ( 2017 ) have shared their experience in reforming the DSE curriculum by adding topics related to Big Data. A few authors have also developed and evaluated different tools to help the instructors teaching DSE.

There are further studies which focus on different aspects including specialized tools for specific topics in DSE (Mcintyre et al, 1995 ; Nelson & Fatimazahra, 2010 ). For instance, Mcintyre et al. ( 1995 ) conducted a survey about using state of the art software tools to teach advanced relational database design courses at Cleveland State University. However, the authors did not discuss the DSE curricula and pedagogy in their study. Similarly, a review has been conducted by Nelson and Fatimazahra ( 2010 ) to highlight the fact that the understanding of basic knowledge of database is important for students of the computer science domain as well as those belonging to other domains. They highlighted the issues encountered while teaching the database course in universities and suggested the instructors investigate these difficulties so as to make this course more effective for the students. Although authors have discussed and analyzed the tools to teach database, the tools are yet to be categorized according to different methods and research types within DSE. There also exists an interesting systematic mapping study by Taipalus and Seppänen ( 2020 ) that focuses on teaching SQL which is a specific topic of DSE. Whereby, they categorized the selected primary studies into six categories based on their research types. They utilized directed content analysis, such as, student errors in query formulation, characteristics and presentation of the exercise database, specific or non-specific teaching approach suggestions, patterns and visualization, and easing teacher workload.

Another relevant study that focuses on collaborative learning techniques to teach the database course has been conducted by Martin et al. ( 2013 ) This research discusses collaborative learning techniques and adapted it for the introductory database course at the Barcelona School of Informatics. The motive of the authors was to introduce active learning methods to improve learning and encourage the acquisition of competence. However, the focus of the study was only on a few methods for teaching the course of database systems, while other important perspectives, including database curricula, and tools for teaching DSE were not discussed in this study.

The above discussion shows that a considerable amount of research work has been conducted in the field of DSE to propose various teaching methods; develop and test different supportive tools, techniques, and strategies; and to improve the curricula for DSE. However, to the best of our knowledge, there is no study that puts all these relevant and pertinent aspects together while also classifying and discussing the supporting methods, and techniques. This review is considerably different from previous studies. Table ​ Table1 1 highlights the differences between this study and other relevant studies in the field of DSE using ✓ and – symbol reflecting "included" and "not included" respectively. Therefore, this study aims to conduct a systematic mapping study on DSE that focuses on compiling, classifying, and discussing the existing work related to pedagogy, supporting tools, and curricula.

Comparison with other related research articles

Research methodology

In order to preserve the principal aim of this study, which is to review the research conducted in the area of database systems education, a piece of advice has been collected from existing methods described in various studies (Elberzhager et al., 2012 ; Keele et al., 2007 ; Mushtaq et al., 2017 ) to search for the relevant papers. Thus, proper research objectives were formulated, and based on them appropriate research questions and search strategy were formulated as shown in Fig.  1 .

An external file that holds a picture, illustration, etc.
Object name is 10639_2022_11293_Fig1_HTML.jpg

Research objectives

The Following are the research objectives of this study:

  • i. To find high quality research work in DSE.
  • ii. To categorize different aspects of DSE covered by other researchers in the field.
  • iii. To provide a thorough discussion of the existing work in this study to provide useful information in the form of evolution, teaching guidelines, and future research directions of the instructors.

Research questions

In order to fulfill the research objectives, some relevant research questions have been formulated. These questions along with their motivations have been presented in Table ​ Table2 2 .

Study selection results

Search strategy

The Following search string used to find relevant articles to conduct this study. “Database” AND (“System” OR “Management”) AND (“Education*” OR “Train*” OR “Tech*” OR “Learn*” OR “Guide*” OR “Curricul*”).

Articles have been taken from different sources i.e. IEEE, Springer, ACM, Science Direct and other well-known journals and conferences such as Wiley Online Library, PLOS and ArXiv. The planning for search to find the primary study in the field of DSE is a vital task.

Study selection

A total of 29,370 initial studies were found. These articles went through a selection process, and two authors were designated to shortlist the articles based on the defined inclusion criteria as shown in Fig.  2 . Their conflicts were resolved by involving a third author; while the inclusion/exclusion criteria were also refined after resolving the conflicts as shown in Table ​ Table3. 3 . Cohen’s Kappa coefficient 0.89 was observed between the two authors who selected the articles, which reflects almost perfect agreement between them (Landis & Koch, 1977 ). While, the number of papers in different stages of the selection process for all involved portals has been presented in Table ​ Table4 4 .

An external file that holds a picture, illustration, etc.
Object name is 10639_2022_11293_Fig2_HTML.jpg

Selection criteria

Title based search: Papers that are irrelevant based on their title are manually excluded in the first stage. At this stage, there was a large portion of irrelevant papers. Only 609 papers remained after this stage.

Abstract based search: At this stage, abstracts of the selected papers in the previous stage are studied and the papers are categorized for the analysis along with research approach. After this stage only 152 papers were left.

Full text based analysis: Empirical quality of the selected articles in the previous stage is evaluated at this stage. The analysis of full text of the article has been conducted. The total of 70 papers were extracted from 152 papers for primary study. Following questions are defined for the conduction of final data extraction.

Quality assessment criteria

Following are the criteria used to assess the quality of the selected primary studies. This quality assessment was conducted by two authors as explained above.

  • The study focuses on curricula, tools, approach, or assessments in DSE, the possible answers were Yes (1), No (0)
  • The study presents a solution to the problem in DSE, the possible answers to this question were Yes (1), Partially (0.5), No (0)
  • The study focuses on empirical results, Yes (1), No (0)

Score pattern of publication channels

Almost 50.00% of papers had scored more than average and 33.33% of papers had scored between the average range i.e., 2.50–3.50. Some articles with the score below 2.50 have also been included in this study as they present some useful information and were published in education-based journals. Also, these studies discuss important demography and technology based aspects that are directly related to DSE.

Threats to validity

The validity of this study could be influenced by the following factors during the literature of this publication.

Construct validity

In this study this validity identifies the primary study for research (Elberzhager et al., 2012 ). To ensure that many primary studies have been included in this literature two authors have proposed possible search keywords in multiple repetitions. Search string is comprised of different terms related to DS and education. Though, list might be incomplete, count of final papers found can be changed by the alternative terms (Ampatzoglou et al., 2013 ). IEEE digital library, Science direct, ACM digital library, Wiley Online Library, PLOS, ArXiv and Google scholar are the main libraries where search is done. We believe according to the statistics of search engines of literature the most research can be found on these digital libraries (Garousi et al., 2013 ). Researchers also searched related papers in main DS research sites (VLDB, ICDM, EDBT) in order to minimize the risk of missing important publication.

Including the papers that does not belong to top journals or conferences may reduce the quality of primary studies in this research but it indicates that the representativeness of the primary studies is improved. However, certain papers which were not from the top publication sources are included because of their relativeness wisth the literature, even though they reduce the average score for primary studies. It also reduces the possibility of alteration of results which might have caused by the improper handling of duplicate papers. Some cases of duplications were found which were inspected later whether they were the same study or not. The two authors who have conducted the search has taken the final decision to the select the papers. If there is no agreement between then there must be discussion until an agreement is reached.

Internal validity

This validity deals with extraction and data analysis (Elberzhager et al., 2012 ). Two authors carried out the data extraction and primary studies classification. While the conflicts between them were resolved by involving a third author. The Kappa coefficient was 0.89, according to Landis and Koch ( 1977 ), this value indicates almost perfect level of agreement between the authors that reduces this threat significantly.

Conclusion validity

This threat deals with the identification of improper results which may cause the improper conclusions. In this case this threat deals with the factors like missing studies and wrong data extraction (Ampatzoglou et al., 2013 ). The objective of this is to limit these factors so that other authors can perform study and produce the proper conclusions (Elberzhager et al., 2012 ).

Interpretation of results might be affected by the selection and classification of primary studies and analyzing the selected study. Previous section has clearly described each step performed in primary study selection and data extraction activity to minimize this threat. The traceability between the result and data extracted was supported through the different charts. In our point of view, slight difference based on the publication selection and misclassification would not alter the main results.

External validity

This threat deals with the simplification of this research (Mateo et al., 2012 ). The results of this study were only considered that related to the DSE filed and validation of the conclusions extracted from this study only concerns the DSE context. The selected study representativeness was not affected because there was no restriction on time to find the published research. Therefore, this external validity threat is not valid in the context of this research. DS researchers can take search string and the paper classification scheme represented in this study as an initial point and more papers can be searched and categorized according to this scheme.

Analysis of compiled research articles

This section presents the analysis of the compiled research articles carefully selected for this study. It presents the findings with respect to the research questions described in Table ​ Table2 2 .

Selection results

A total of 70 papers were identified and analyzed for the answers of RQs described above. Table ​ Table6 6 represents a list of the nominated papers with detail of the classification results and their quality assessment scores.

Classification and quality assessment of selected articles

RQ1.Categorization of research work in DSE field

The analysis in this study reveals that the literature can be categorized as: Tools: any additional application that helps instructors in teaching and students in learning. Methods: any improvisation aimed at improving pedagogy or cognition. Curriculum: refers to the course content domains and their relative importance in a degree program, as shown in Fig.  3 .

An external file that holds a picture, illustration, etc.
Object name is 10639_2022_11293_Fig3_HTML.jpg

Taxonomy of DSE study types

Most of the articles provide a solution by gathering the data and also prove the novelty of their research through results. These papers are categorized as experiments w.r.t. their research types. Whereas, some of them case study papers which are used to generate an in depth, multifaceted understanding of a complex issue in its real-life context, while few others are review studies analyzing the previously used approaches. On the other hand, a majority of included articles have evaluated their results with the help of experiments, while others conducted reviews to establish an opinion as shown in Fig.  4 .

An external file that holds a picture, illustration, etc.
Object name is 10639_2022_11293_Fig4_HTML.jpg

Cross Mapping of DSE study type and research Types

Educational tools, especially those related to technology, are making their place in market faster than ever before (Calderon et al., 2011 ). The transition to active learning approaches, with the learner more engaged in the process rather than passively taking in information, necessitates a variety of tools to help ensure success. As with most educational initiatives, time should be taken to consider the goals of the activity, the type of learners, and the tools needed to meet the goals. Constant reassessment of tools is important to discover innovation and reforms that improve teaching and learning (Irby & Wilkerson, 2003 ). For this purpose, various type of educational tools such as, interactive, web-based and game based have been introduced to aid the instructors in order to explain the topic in more effective way.

The inclusion of technology into the classroom may help learners to compete in the competitive market when approaching the start of their career. It is important for the instructors to acknowledge that the students are more interested in using technology to learn database course instead of merely being taught traditional theory, project, and practice-based methods of teaching (Adams et al., 2004 ). Keeping these aspects in view many authors have done significant research which includes web-based and interactive tools to help the learners gain better understanding of basic database concepts.

Great research has been conducted with the focus of students learning. In this study we have discussed the students learning supportive with two major finding’s objectives i.e., tools which prove to be more helpful than other tools. Whereas, proposed tools with same outcome as traditional classroom environment. Such as, Abut and Ozturk ( 1997 ) proposed an interactive classroom environment to conduct database classes. The online tools such as electronic “Whiteboard”, electronic textbooks, advance telecommunication networks and few other resources such as Matlab and World Wide Web were the main highlights of their proposed smart classroom. Also, Pahl et al. ( 2004 ) presented an interactive multimedia-based system for the knowledge and skill oriented Web-based education of database course students. The authors had differentiated their proposed classroom environment from traditional classroom-based approach by using tool mediated independent learning and training in an authentic setting. On the other hand, some authors have also evaluated the educational tools based on their usage and impact on students’ learning. For example, Brusilovsky et al. ( 2010 )s evaluated the technical and conceptual difficulties of using several interactive educational tools in the context of a single course. A combined Exploratorium has been presented for database courses and an experimental platform, which delivers modified access to numerous types of interactive learning activities.

Also, Taipalus and Perälä ( 2019 ) investigated the types of errors that are persistent in writing SQL by the students. The authors also contemplated the errors while mapping them onto different query concepts. Moreover, Abelló Gamazo et al. ( 2016 ) presented a software tool for the e-assessment of relational database skills named LearnSQL. The proposed software allows the automatic and efficient e-learning and e-assessment of relational database skills. Apart from these, Yue ( 2013 ) proposed the database tool named Sakila as a unified platform to support instructions and multiple assignments of a graduate database course for five semesters. According to this study, students find this tool more useful and interesting than the highly simplified databases developed by the instructor, or obtained from textbook. On the other hand, authors have proposed tools with the main objective to help the student’s grip on the topic by addressing the pedagogical problems in using the educational tools. Connolly et al. ( 2005 ) discussed some of the pedagogical problems sustaining the development of a constructive learning environment using problem-based learning, a simulation game and interactive visualizations to help teach database analysis and design. Also, Yau and Karim ( 2003 ) proposed smart classroom with prevalent computing technology which will facilitate collaborative learning among the learners. The major aim of this smart classroom is to improve the quality of interaction between the instructors and students during lecture.

Student satisfaction is also an important factor for the educational tools to more effective. While it supports in students learning process it should also be flexible to achieve the student’s confidence by making it as per student’s needs (Brusilovsky et al., 2010 ; Connolly et al., 2005 ; Pahl et al., 2004 ). Also, Cvetanovic et al. ( 2010 ) has proposed a web-based educational system named ADVICE. The proposed solution helps the students to reduce the gap between DBMS, theory and its practice. On the other hand, authors have enhanced the already existing educational tools in the traditional classroom environment to addressed the student’s concerns (Nelson & Fatimazahra, 2010 ; Regueras et al., 2007 ) Table ​ Table7 7 .

Tools: Adopted in DSE and their impacts

Hands on database development is the main concern in most of the institute as well as in industry. However, tools assisting the students in database development and query writing is still major concern especially in SQL (Brusilovsky et al., 2010 ; Nagataki et al., 2013 ).

Student’s grades reflect their conceptual clarity and database development skills. They are also important to secure jobs and scholarships after passing out, which is why it is important to have the educational learning tools to help the students to perform well in the exams (Cvetanovic et al., 2010 ; Taipalus et al., 2018 ). While, few authors (Wang et al., 2010 ) proposed Metube which is a variation of YouTube. Subsequently, existing educational tools needs to be upgraded or replaced by the more suitable assessment oriented interactive tools to attend challenging students needs (Pahl et al., 2004 ; Yuelan et al., 2011 ).

One other objective of developing the educational tools is to increase the interaction between the students and the instructors. In the modern era, almost every institute follows the student centered learning(SCL). In SCL the interaction between students and instructor increases with most of the interaction involves from the students. In order to support SCL the educational based interactive and web-based tools need to assign more roles to students than the instructors (Abbasi et al., 2016 ; Taipalus & Perälä, 2019 ; Yau & Karim, 2003 ).

Theory versus practice is still one of the main issues in DSE teaching methods. The traditional teaching method supports theory first and then the concepts learned in the theoretical lectures implemented in the lab. Whereas, others think that it is better to start by teaching how to write query, which should be followed by teaching the design principles for database, while a limited amount of credit hours are also allocated for the general database theory topics. This part of the article discusses different trends of teaching and learning style along with curriculum and assessments methods discussed in DSE literature.

A variety of teaching methods have been designed, experimented, and evaluated by different researchers (Yuelan et al., 2011 ; Chen et al., 2012 ; Connolly & Begg, 2006 ). Some authors have reformed teaching methods based on the requirements of modern way of delivering lectures such as Yuelan et al. ( 2011 ) reform teaching method by using various approaches e.g. a) Modern ways of education: includes multimedia sound, animation, and simulating the process and working of database systems to motivate and inspire the students. b) Project driven approach: aims to make the students familiar with system operations by implementing a project. c) Strengthening the experimental aspects: to help the students get a strong grip on the basic knowledge of database and also enable them to adopt a self-learning ability. d) Improving the traditional assessment method: the students should turn in their research and development work as the content of the exam, so that they can solve their problem on their own.

The main aim of any teaching method is to make student learn the subject effectively. Student must show interest in order to gain something from the lectures delivered by the instructors. For this, teaching methods should be interactive and interesting enough to develop the interest of the students in the subject. Students can show interest in the subject by asking more relative questions or completing the home task and assignments on time. Authors have proposed few teaching methods to make topic more interesting such as, Chen et al. ( 2012 ) proposed a scaffold concept mapping strategy, which considers a student’s prior knowledge, and provides flexible learning aids (scaffolding and fading) for reading and drawing concept maps. Also, Connolly & Begg (200s6) examined different problems in database analysis and design teaching, and proposed a teaching approach driven by principles found in the constructivist epistemology to overcome these problems. This constructivist approach is based on the cognitive apprenticeship model and project-based learning. Similarly, Domínguez & Jaime ( 2010 ) proposed an active method for database design through practical tasks development in a face-to-face course. They analyzed results of five academic years using quasi experimental. The first three years a traditional strategy was followed and a course management system was used as material repository. On the other hand, Dietrich and Urban ( 1996 ) have described the use of cooperative group learning concepts in support of an undergraduate database management course. They have designed the project deliverables in such a way that students develop skills for database implementation. Similarly, Zhang et al. ( 2018 ) have discussed several effective classroom teaching measures from the aspects of the innovation of teaching content, teaching methods, teaching evaluation and assessment methods. They have practiced the various teaching measures by implementing the database technologies and applications in Qinghai University. Moreover, Hou and Chen ( 2010 ) proposed a new teaching method based on blending learning theory, which merges traditional and constructivist methods. They adopted the method by applying the blending learning theory on Access Database programming course teaching.

Problem solving skills is a key aspect to any type of learning at any age. Student must possess this skill to tackle the hurdles in institute and also in industry. Create mind and innovative students find various and unique ways to solve the daily task which is why they are more likeable to secure good grades and jobs. Authors have been working to introduce teaching methods to develop problem solving skills in the students(Al-Shuaily, 2012 ; Cai & Gao, 2019 ; Martinez-González & Duffing, 2007 ; Gudivada et al., 2007 ). For instance, Al-Shuaily ( 2012 ) has explored four cognitive factors such as i) Novices’ ability in understanding, ii) Novices’ ability to translate, iii) Novice’s ability to write, iv) Novices’ skills that might influence SQL teaching, and learning methods and approaches. Also, Cai and Gao ( 2019 ) have reformed the teaching method in the database course of two higher education institutes in China. Skills and knowledge, innovation ability, and data abstraction were the main objective of their study. Similarly, Martinez-González and Duffing ( 2007 ) analyzed the impact of convergence of European Union (EU) in different universities across Europe. According to their study, these institutes need to restructure their degree program and teaching methodologies. Moreover, Gudivada et al. ( 2007 ) proposed a student’s learning method to work with the large datasets. they have used the Amazon Web Services API and.NET/C# application to extract a subset of the product database to enhance student learning in a relational database course.

On the other hand, authors have also evaluated the traditional teaching methods to enhance the problem-solving skills among the students(Eaglestone & Nunes, 2004 ; Wang & Chen, 2014 ; Efendiouglu & Yelken, 2010 ) Such as, Eaglestone and Nunes ( 2004 ) shared their experiences of delivering a database design course at Sheffield University and discussed some of the issues they faced, regarding teaching, learning and assessments. Likewise, Wang and Chen ( 2014 ) summarized the problems mainly in teaching of the traditional database theory and application. According to the authors the teaching method is outdated and does not focus on the important combination of theory and practice. Moreover, Efendiouglu and Yelken ( 2010 ) investigated the effects of two different methods Programmed Instruction (PI) and Meaningful Learning (ML) on primary school teacher candidates’ academic achievements and attitudes toward computer-based education, and to define their views on these methods. The results show that PI is not favoured for teaching applications because of its behavioural structure Table ​ Table8 8 .

Methods: Teaching approaches adopted in DSE

Students become creative and innovative when the try to study on their own and also from different resources rather than curriculum books only. In the modern era, there are various resources available on both online and offline platforms. Modern teaching methods must emphasize on making the students independent from the curriculum books and educate them to learn independently(Amadio et al., 2003 ; Cai & Gao, 2019 ; Martin et al., 2013 ). Also, in the work of Kawash et al. ( 2020 ) proposed he group study-based learning approach called Graded Group Activities (GGAs). In this method students team up in order to take the exam as a group. On the other hand, few studies have emphasized on course content to prepare students for the final exams such as, Zheng and Dong ( 2011 ) have discussed the issues of computer science teaching with particular focus on database systems, where different characteristics of the course, teaching content and suggestions to teach this course effectively have been presented.

As technology is evolving at rapid speed, so students need to have practical experience from the start. Basic theoretical concepts of database are important but they are of no use without its implementation in real world projects. Most of the students study in the institutes with the aim of only clearing the exams with the help of theoretical knowledge and very few students want to have practical experience(Wang & Chen, 2014 ; Zheng & Dong, 2011 ). To reduce the gap between the theory and its implementation, authors have proposed teaching methods to develop the student’s interest in the real-world projects (Naik & Gajjar, 2021 ; Svahnberg et al., 2008 ; Taipalus et al., 2018 ). Moreover, Juxiang and Zhihong ( 2012 ) have proposed that the teaching organization starts from application scenarios, and associate database theoretical knowledge with the process from analysis, modeling to establishing database application. Also, Svahnberg et al. ( 2008 ) explained that in particular conditions, there is a possibility to use students as subjects for experimental studies in DSE and influencing them by providing responses that are in line with industrial practice.

On the other hand, Nelson et al. ( 2003 ) evaluated the different teaching methods used to teach different modules of database in the School of Computing and Technology at the University of Sunder- land. They outlined suggestions for changes to the database curriculum to further integrate research and state-of-the-art systems in databases.

  • III. Curriculum

Database curriculum has been revisited many times in the form of guidelines that not only present the contents but also suggest approximate time to cover different topics. According to the ACM curriculum guidelines (Lunt et al., 2008 ) for the undergraduate programs in computer science, the overall coverage time for this course is 46.50 h distributed in such a way that 11 h is the total coverage time for the core topics such as, Information Models (4 core hours), Database Systems (3 core hours) and Data Modeling (4 course hours). Whereas, the remaining hours are allocated for elective topics such as Indexing, Relational Databases, Query Languages, Relational Database Design, Transaction Processing, Distributed Databases, Physical Database Design, Data Mining, Information Storage and Retrieval, Hypermedia, Multimedia Systems, and Digital Libraries(Marshall, 2012 ). While, according to the ACM curriculum guidelines ( 2013 ) for undergraduate programs in computer science, this course should be completed in 15 weeks with two and half hour lecture per week and lab session of four hours per week on average (Brady et al., 2004 ). Thus, the revised version emphasizes on the practice based learning with the help of lab component. Numerous organizations have exerted efforts in this field to classify DSE (Dietrich et al., 2008 ). DSE model curricula, bodies of knowledge (BOKs), and some standardization aspects in this field are discussed below:

Model curricula

There are standard bodies who set the curriculum guidelines for teaching undergraduate degree programs in computing disciplines. Curricula which include the guidelines to teach database are: Computer Engineering Curricula (CEC) (Meier et al., 2008 ), Information Technology Curricula (ITC) (Alrumaih, 2016 ), Computing Curriculum Software Engineering (CCSE) (Meyer, 2001 ), Cyber Security Curricula (CSC) (Brady et al., 2004 ; Bishop et al., 2017 ).

Bodies of knowledge (BOK)

A BOK includes the set of thoughts and activities related to the professional area, while in model curriculum set of guidelines are given to address the education issues (Sahami et al., 2011 ). Database body of Knowledge comprises of (a) The Data Management Body of Knowledge (DM- BOK), (b) Software Engineering Education Knowledge (SEEK) (Sobel, 2003 ) (Sobel, 2003 ), and (c) The SE body of knowledge (SWEBOK) (Swebok Evolution: IEEE Computer Society n.d. ).

Apart from the model curricula, and bodies of knowledge, there also exist some standards related to the database and its different modules: ISO/IEC 9075–1:2016 (Computing Curricula, 1991 ), ISO/IEC 10,026–1: 1998 (Suryn, 2003 ).

We also utilize advices from some studies (Elberzhager et al., 2012 ; Keele et al., 2007 ) to search for relevant papers. In order to conduct this systematic study, it is essential to formulate the primary research questions (Mushtaq et al., 2017 ). Since the data management techniques and software are evolving rapidly, the database curriculum should also be updated accordingly to meet these new requirements. Some authors have described ways of updating the content of courses to keep pace with specific developments in the field and others have developed new database curricula to keep up with the new data management techniques.

Furthermore, some authors have suggested updates for the database curriculum based on the continuously evolving technology and introduction of big data. For instance Bhogal et al. ( 2012 ) have shown that database curricula need to be updated and modernized, which can be achieved by extending the current database concepts that cover the strategies to handle the ever changing user requirements and how database technology has evolved to meet the requirements. Likewise, Picciano ( 2012 ) examines the evolving world of big data and analytics in American higher education. According to the author, the “data driven” decision making method should be used to help the institutes evaluate strategies that can improve retention and update the curriculum that has big data basic concepts and applications, since data driven decision making has already entered in the big data and learning analytic era. Furthermore, Marshall ( 2011 ) presented the challenges faced when developing a curriculum for a Computer Science degree program in the South African context that is earmarked for international recognition. According to the author, the Curricula needs to adhere both to the policy and content requirements in order to be rated as being of a particular quality.

Similarly, some studies (Abourezq & Idrissi, 2016 ; Mingyu et al., 2017 ) described big data influence from a social perspective and also proceeded with the gaps in database curriculum of computer science, especially, in the big data era and discovers the teaching improvements in practical and theoretical teaching mode, teaching content and teaching practice platform in database curriculum. Also Silva et al. ( 2016 ) propose teaching SQL as a general language that can be used in a wide range of database systems from traditional relational database management systems to big data systems.

On the other hand, different authors have developed a database curriculum based on the different academic background of students. Such as, Dean and Milani ( 1995 ) have recommended changes in computer science curricula based on the practice in United Stated Military Academy (USMA). They emphasized greatly on the practical demonstration of the topic rather than the theoretical explanation. Especially, for the non-computer science major students. Furthermore, Urban and Dietrich ( 2001 ) described the development of a second course on database systems for undergraduates, preparing students for the advanced database concepts that they will exercise in the industry. They also shared their experience with teaching the course, elaborating on the topics and assignments. Also, Andersson et al. ( 2019 ) proposed variations in core topics of database management course for the students with the engineering background. Moreover, Dietrich et al. ( 2014 ) described two animations developed with images and color that visually and dynamically introduce fundamental relational database concepts and querying to students of many majors. The goal is that the educators, in diverse academic disciplines, should be able to incorporate these animations in their existing courses to meet their pedagogical needs.

The information systems have evolved into large scale distributed systems that store and process a huge amount of data across different servers, and process them using different distributed data processing frameworks. This evolution has given birth to new paradigms in database systems domain termed as NoSQL and Big Data systems, which significantly deviate from conventional relational and distributed database management systems. It is pertinent to mention that in order to offer a sustainable and practical CS education, these new paradigms and methodologies as shown in Fig.  5 should be included into database education (Kleiner, 2015 ). Tables ​ Tables9 9 and ​ and10 10 shows the summarized findings of the curriculum based reviewed studies. This section also proposed appropriate text book based on the theory, project, and practice-based teaching methodology as shown in Table ​ Table9. 9 . The proposed books are selected purely on the bases of their usage in top universities around the world such as, Massachusetts Institute of Technology, Stanford University, Harvard University, University of Oxford, University of Cambridge and, University of Singapore and the coverage of core topics mentioned in the database curriculum.

An external file that holds a picture, illustration, etc.
Object name is 10639_2022_11293_Fig5_HTML.jpg

Concepts in Database Systems Education (Kleiner, 2015 )

Recommended text books for DSE

Curriculum: Findings of Reviewed Literature

RQ.2 Evolution of DSE research

This section discusses the evolution of database while focusing the DSE over the past 25 years as shown in Fig.  6 .

An external file that holds a picture, illustration, etc.
Object name is 10639_2022_11293_Fig6_HTML.jpg

Evolution of DSE studies

This study shows that there is significant increase in research in DSE after 2004 with 78% of the selected papers are published after 2004. The main reason of this outcome is that some of the papers are published in well-recognized channels like IEEE Transactions on Education, ACM Transactions on Computing Education, International Conference on Computer Science and Education (ICCSE), and Teaching, Learning and Assessment of Database (TLAD) workshop. It is also evident that several of these papers were published before 2004 and only a few articles were published during late 1990s. This is because of the fact that DSE started to gain interest after the introduction of Body of Knowledge and DSE standards. The data intensive scientific discovery has been discussed as the fourth paradigm (Hey et al., 2009 ): where the first involves empirical science and observations; second contains theoretical science and mathematically driven insights; third considers computational science and simulation driven insights; while the fourth involves data driven insights of modern scientific research.

Over the past few decades, students have gone from attending one-room class to having the world at their fingertips, and it is a great challenge for the instructors to develop the interest of students in learning database. This challenge has led to the development of the different types of interactive tools to help the instructors teach DSE in this technology oriented era. Keeping the importance of interactive tools in DSE in perspective, various authors have proposed different interactive tools over the years, such as during 1995–2003, when different authors proposed various interactive tools. Some studies (Abut & Ozturk, 1997 ; Mcintyre et al., 1995 ) introduced state of the art interactive tools to teach and enhance the collaborative learning among the students. Similarly, during 2004–2005 more interactive tools in the field of DSE were proposed such as Pahl et al. ( 2004 ), Connolly et al. ( 2005 ) introduced multimedia system based interactive model and game based collaborative learning environment.

The Internet has started to become more common in the first decade of the twenty-first century and its positive impact on the education sector was undeniable. Cost effective, student teacher peer interaction, keeping in touch with the latest information were the main reasons which made the instructors employ web-based tools to teach database in the education sector. Due to this spike in the demand of web-based tools, authors also started to introduce new instruments to assist with teaching database. In 2007 Regueras et al. ( 2007 ) proposed an e-learning tool named QUEST with a feedback module to help the students to learn from their mistakes. Similarly, in 2010, multiple authors have proposed and evaluated various web-based tools. Cvetanovic et al. ( 2010 ) proposed ADVICE with the functionality to monitor student’s progress, while, few authors (Wang et al., 2010 ) proposed Metube which is a variation of YouTube. Furthermore, Nelson and Fatimazahra ( 2010 ) evaluated different web-based tools to highlight the complexities of using these web-based instruments.

Technology has changed the teaching methods in the education sector but technology cannot replace teachers, and despite the amount of time most students spend online, virtual learning will never recreate the teacher-student bond. In the modern era, innovation in technology used in educational sectors is not meant to replace the instructors or teaching methods.

During the 1990s some studies (Dietrich & Urban, 1996 ; Urban & Dietrich, 1997 ) proposed learning and teaching methods respectively keeping the evolving technology in view. The highlight of their work was project deliverables and assignments where students progressively advanced to a step-by-step extension, from a tutorial exercise and then attempting more difficult extension of assignment.

During 2002–2007 various authors have discussed a number of teaching and learning methods to keep up the pace with the ever changing database technology, such as Connolly and Begg ( 2006 ) proposing a constructive approach to teach database analysis and design. Similarly, Prince and Felder ( 2006 ) reviewed the effectiveness of inquiry learning, problem based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching. Also, McIntyre et al. (Mcintyre et al., 1995 ) brought to light the impact of convergence of European Union (EU) in different universities across Europe. They suggested a reconstruction of teaching and learning methodologies in order to effectively teach database.

During 2008–2013 more work had been done to address the different methods of teaching and learning in the field of DSE, like the work of Dominguez and Jaime ( 2010 ) who proposed an active learning approach. The focus of their study was to develop the interest of students in designing and developing databases. Also, Zheng and Dong ( 2011 ) have highlighted various characteristics of the database course and its teaching content. Similarly, Yuelan et al. ( 2011 ) have reformed database teaching methods. The main focus of their study were the Modern ways of education, project driven approach, strengthening the experimental aspects, and improving the traditional assessment method. Likewise, Al-Shuaily ( 2012 ) has explored 4 cognitive factors that can affect the learning process of database. The main focus of their study was to facilitate the students in learning SQL. Subsequently, Chen et al. ( 2012 ) also proposed scaffolding-based concept mapping strategy. This strategy helps the students to better understand database management courses. Correspondingly, Martin et al. ( 2013 ) discussed various collaborative learning techniques in the field of DSE while keeping database as an introductory course.

In the years between 2014 and 2021, research in the field of DSE increased, which was the main reason that the most of teaching, learning and assessment methods were proposed and discussed during this period. Rashid and Al-Radhy ( 2014 ) discussed the issues of traditional teaching, learning, assessing methods of database courses at different universities in Kurdistan and the main focus of their study being reformation issues, such as absence of teaching determination and contradiction between content and theory. Similarly, Wang and Chen ( 2014 ) summarized the main problems in teaching the traditional database theory and its application. Curriculum assessment mode was the main focus of their study. Eaglestone and Nunes ( 2004 ) shared their experiences of delivering a databases design course at Sheffield University. Their focus of study included was to teach the database design module to a diverse group of students from different backgrounds. Rashid ( 2015 ) discussed some important features of database courses, whereby reforming the conventional teaching, learning, and assessing strategies of database courses at universities were the main focus of this study. Kui et al. ( 2018 ) reformed the teaching mode of database courses based on flipped classroom. Initiative learning of database courses was their main focus in this study. Similarly, Zhang et al. ( 2018 ) discussed several effective classroom teaching measures. The main focus of their study was teaching content, teaching methods, teaching evaluation and assessment methods. Cai and Gao ( 2019 ) also carried out the teaching reforms in the database course of liberal arts. Diversified teaching modes, such as flipping classroom, case oriented teaching and task oriented were the focus of their study. Teaching Kawash et al. ( 2020 ) proposed a learning approach called Graded Group Activities (GGAs). Their main focus of the study was reforming learning and assessment method.

Database course covers several topics that range from data modeling to data implementation and examination. Over the years, various authors have given their suggestions to update these topics in database curriculum to meet the requirements of modern technologies. On the other hand, authors have also proposed a new curriculum for the students of different academic backgrounds and different areas. These reformations in curriculum helped the students in their preparation, practically and theoretically, and enabled them to compete in the competitive market after graduation.

During 2003 and 2006 authors have proposed various suggestions to update and develop computer science curriculum across different universities. Robbert and Ricardo ( 2003 ) evaluated three reviews from 1999 to 2002 that were given to the groups of educators. The focus of their study was to highlight the trends that occurred in database curriculum. Also, Calero et al. ( 2003 ) proposed a first draft for this Database Body of Knowledge (DBBOK). Database (DB), Database Design (DBD), Database Administration (DBAd), Database Application (DBAp) and Advance Databases (ADVDB) were the main focus of their study. Furthermore, Conklin and Heinrichs (Conklin & Heinrichs, 2005 ) compared the content included in 13 database textbooks and the main focus of their study was IS 2002, CC2001, and CC2004 model curricula.

The years from 2007 and 2011, authors managed to developed various database curricula, like Luo et al. ( 2008 ) developed curricula in Zhejiang University City College. The aim of their study to nurture students to be qualified computer scientists. Likewise, Dietrich et al. ( 2008 ) proposed the techniques to assess the development of an advanced database course. The purpose behind the addition of an advanced database course at undergraduate level was to prepare the students to respond to industrial requirements. Also, Marshall ( 2011 ) developed a new database curriculum for Computer Science degree program in the South African context.

During 2012 and 2021 various authors suggested updates for the database curriculum such as Bhogal et al. ( 2012 ) who suggested updating and modernizing the database curriculum. Data management and data analytics were the focus of their study. Similarly, Picciano ( 2012 ) examined the curriculum in the higher level of American education. The focus of their study was big data and analytics. Also, Zhanquan et al. ( 2016 ) proposed the design for the course content and teaching methods in the classroom. Massive Open Online Courses (MOOCs) were the focus of their study. Likewise, Mingyu et al. ( 2017 ) suggested updating the database curriculum while keeping new technology concerning the database in perspective. The focus of their study was big data.

The above discussion clearly shows that the SQL is most discussed topic in the literature where more than 25% of the studies have discussed it in the previous decade as shown in Fig.  7 . It is pertinent to mention that other SQL databases such as Oracle, MS access are discussed under the SQL banner (Chen et al., 2012 ; Hou & Chen, 2010 ; Wang & Chen, 2014 ). It is mainly because of its ability to handle data in a relational database management system and direct implementation of database theoretical concepts. Also, other database topics such as transaction management, application programming etc. are also the main highlights of the topics discussed in the literature.

An external file that holds a picture, illustration, etc.
Object name is 10639_2022_11293_Fig7_HTML.jpg

Evolution of Database topics discussed in literature

Research synthesis, advice for instructors, and way forward

This section presents the synthesized information extracted after reading and analyzing the research articles considered in this study. To this end, it firstly contextualizes the tools and methods to help the instructors find suitable tools and methods for their settings. Similarly, developments in curriculum design have also been discussed. Subsequently, general advice for instructors have been discussed. Lastly, promising future research directions for developing new tools, methods, and for revising the curriculum have also been discussed in this section.

Methods, tools, and curriculum

Methods and tools.

Web-based tools proposed by Cvetanovic et al. ( 2010 ) and Wang et al. ( 2010 ) have been quite useful, as they are growing increasingly pertinent as online mode of education is prevalent all around the globe during COVID-19. On the other hand, interactive tools and smart class room methodology has also been used successfully to develop the interest of students in database class. (Brusilovsky et al., 2010 ; Connolly et al., 2005 ; Pahl et al., 2004 ; Canedo et al., 2021 ; Ko et al., 2021 ).

One of the most promising combination of methodology and tool has been proposed by Cvetanovic et al. ( 2010 ), whereby they developed a tool named ADVICE that helps students learn and implement database concepts while using project centric methodology, while a game based collaborative learning environment was proposed by Connolly et al. ( 2005 ) that involves a methodology comprising of modeling, articulation, feedback, and exploration. As a whole, project centric teaching (Connolly & Begg, 2006 ; Domínguez & Jaime, 2010 ) and teaching database design and problem solving skills Wang and Chen ( 2014 ), are two successful approaches for DSE. Whereas, other studies (Urban & Dietrich, 1997 ) proposed teaching methods that are more inclined towards practicing database concepts. While a topic specific approach has been proposed by Abbasi et al. ( 2016 ), Taipalus et al. ( 2018 ) and Silva et al. ( 2016 ) to teach and learn SQL. On the other hand, Cai and Gao ( 2019 ) developed a teaching method for students who do not have a computer science background. Lastly, some useful ways for defining assessments for DSE have been proposed by Kawash et al. ( 2020 ) and Zhang et al. ( 2018 ).

Curriculum of database adopted by various institutes around the world does not address how to teach the database course to the students who do not have a strong computer science background. Such as Marshall ( 2012 ), Luo et al. ( 2008 ) and Zhanquan et al. ( 2016 ) have proposed the updates in current database curriculum for the students who are not from computer science background. While Abid et al. ( 2015 ) proposed a combined course content and various methodologies that can be used for teaching database systems course. On the other hand, current database curriculum does not include the topics related to latest technologies in database domain. This factor was discussed by many other studies as well (Bhogal et al., 2012 ; Mehmood et al., 2020 ; Picciano, 2012 ).

Guidelines for instructors

The major conclusion of this study are the suggestions based on the impact and importance for instructors who are teaching DSE. Furthermore, an overview of productivity of every method can be provided by the empirical studies. These instructions are for instructors which are the focal audience of this study. These suggestions are subjective opinions after literature analysis in form of guidelines according to the authors and their meaning and purpose were maintained. According to the literature reviewed, various issues have been found in this section. Some other issues were also found, but those were not relevant to DSE. Following are some suggestions that provide interesting information:

Project centric and applied approach

  • To inculcate database development skills for the students, basic elements of database development need to be incorporated into teaching and learning at all levels including undergraduate studies (Bakar et al., 2011 ). To fulfill this objective, instructors should also improve the data quality in DSE by assigning the projects and assignments to the students where they can assess, measure and improve the data quality using already deployed databases. They should demonstrate that the quality of data is determined not only by the effective design of a database, but also through the perception of the end user (Mathieu & Khalil, 1997 )
  • The gap between the database course theory and industrial practice is big. Fresh graduate students find it difficult to cope up with the industrial pressure because of the contrast between what they have been taught in institutes and its application in industry (Allsopp et al., 2006 ). Involve top performers from classes in industrial projects so that they are able to acquiring sufficient knowledge and practice, especially for post graduate courses. There must be some other activities in which industry practitioners come and present the real projects and also share their industrial experiences with the students. The gap between theoretical and the practical sides of database has been identified by Myers and Skinner ( 1997 ). In order to build practical DS concepts, instructors should provide the students an accurate view of reality and proper tools.

Importance of software development standards and impact of DB in software success

  • They should have the strategies, ability and skills that can align the DSE course with the contemporary Global Software Development (GSD) (Akbar & Safdar, 2015 ; Damian et al., 2006 ).
  • Enable the students to explain the approaches to problem solving, development tools and methodologies. Also, the DS courses are usually taught in normal lecture format. The result of this method is that students cannot see the influence on the success or failure of projects because they do not realize the importance of DS activities.

Pedagogy and the use of education technology

  • Some studies have shown that teaching through play and practical activities helps to improve the knowledge and learning outcome of students (Dicheva et al., 2015 ).
  • Interactive classrooms can help the instructors to deliver their lecture in a more effective way by using virtual white board, digital textbooks, and data over network(Abut & Ozturk, 1997 ). We suggest that in order to follow the new concept of smart classroom, instructors should use the experience of Yau and Karim ( 2003 ) which benefits in cooperative learning among students and can also be adopted in DSE.
  • The instructors also need to update themselves with full spectrum of technology in education, in general, and for DSE, in particular. This is becoming more imperative as during COVID the world is relying strongly on the use of technology, particularly in education sector.

Periodic Curriculum Revision

  • There is also a need to revisit the existing series of courses periodically, so that they are able to offer the following benefits: (a) include the modern day database system concepts; (b) can be offered as a specialization track; (c) a specialized undergraduate degree program may also be designed.

DSE: Way forward

This research combines a significant work done on DSE at one place, thus providing a point to find better ways forward in order to improvise different possible dimensions for improving the teaching process of a database system course in future. This section discusses technology, methods, and modifications in curriculum would most impact the delivery of lectures in coming years.

Several tools have already been developed for effective teaching and learning in database systems. However, there is a great room for developing new tools. Recent rise of the notion of “serious games” is marking its success in several domains. Majority of the research work discussed in this review revolves around web-based tools. The success of serious games invites researchers to explore this new paradigm of developing useful tools for learning and practice database systems concepts.

Likewise, due to COVID-19 the world is setting up new norms, which are expected to affect the methods of teaching as well. This invites the researchers to design, develop, and test flexible tools for online teaching in a more interactive manner. At the same time, it is also imperative to devise new techniques for assessments, especially conducting online exams at massive scale. Moreover, the researchers can implement the idea of instructional design in web-based teaching in which an online classroom can be designed around the learners’ unique backgrounds and effectively delivering the concepts that are considered to be highly important by the instructors.

The teaching, learning and assessment methods discussed in this study can help the instructors to improve their methods in order to teach the database system course in a better way. It is noticed that only 16% of authors have the assessment methods as their focus of study, which clearly highlights that there is still plenty of work needed to be done in this particular domain. Assessment techniques in the database course will help the learners to learn from their mistakes. Also, instructors must realize that there is a massive gap between database theory and practice which can only be reduced with maximum practice and real world database projects.

Similarly, the technology is continuously influencing the development and expansion of modern education, whereas the instructors’ abilities to teach using online platforms are critical to the quality of online education.

In the same way, the ideas like flipped classroom in which students have to prepare the lesson prior to the class can be implemented on web-based teaching. This ensures that the class time can be used for further discussion of the lesson, share ideas and allow students to interact in a dynamic learning environment.

The increasing impact of big data systems, and data science and its anticipated impact on the job market invites the researchers to revisit the fundamental course of database systems as well. There is a need to extend the boundaries of existing contents by including the concepts related to distributed big data systems data storage, processing, and transaction management, with possible glimpse of modern tools and technologies.

As a whole, an interesting and long term extension is to establish a generic and comprehensive framework that engages all the stakeholders with the support of technology to make the teaching, learning, practicing, and assessing easier and more effective.

This SLR presents review on the research work published in the area of database system education, with particular focus on teaching the first course in database systems. The study was carried out by systematically selecting research papers published between 1995 and 2021. Based on the study, a high level categorization presents a taxonomy of the published under the heads of Tools, Methods, and Curriculum. All the selected articles were evaluated on the basis of a quality criteria. Several methods have been developed to effectively teach the database course. These methods focus on improving learning experience, improve student satisfaction, improve students’ course performance, or support the instructors. Similarly, many tools have been developed, whereby some tools are topic based, while others are general purpose tools that apply for whole course. Similarly, the curriculum development activities have also been discussed, where some guidelines provided by ACM/IEEE along with certain standards have been discussed. Apart from this, the evolution in these three areas has also been presented which shows that the researchers have been presenting many different teaching methods throughout the selected period; however, there is a decrease in research articles that address the curriculum and tools in the past five years. Besides, some guidelines for the instructors have also been shared. Also, this SLR proposes a way forward in DSE by emphasizing on the tools: that need to be developed to facilitate instructors and students especially post Covid-19 era, methods: to be adopted by the instructors to close the gap between the theory and practical, Database curricula update after the introduction of emerging technologies such as big data and data science. We also urge that the recognized publication venues for database research including VLDB, ICDM, EDBT should also consider publishing articles related to DSE. The study also highlights the importance of reviving the curricula, tools, and methodologies to cater for recent advancements in the field of database systems.

Data availability

Code availability, declarations.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

  • Abbasi, S., Kazi, H., Khowaja, K., Abelló Gamazo, A., Burgués Illa, X., Casany Guerrero, M. J., Martin Escofet, C., Quer, C., Rodriguez González, M. E., Romero Moral, Ó., Urpi Tubella, A., Abid, A., Farooq, M. S., Raza, I., Farooq, U., Abid, K., Hussain, N., Abid, K., Ahmad, F., …, Yatim, N. F. M. (2016). Research trends in enterprise service bus (ESB) applications: A systematic mapping study. Journal of Informetrics, 27 (1), 217–220.
  • Abbasi, S., Kazi, H., & Khowaja, K. (2017). A systematic review of learning object oriented programming through serious games and programming approaches. 2017 4th IEEE International Conference on Engineering Technologies and Applied Sciences (ICETAS) , 1–6.
  • Abelló Gamazo A, Burgués Illa X, Casany Guerrero MJ, Martin Escofet C, Quer C, Rodriguez González ME, Romero Moral Ó, Urpi Tubella A. A software tool for E-assessment of relational database skills. International Journal of Engineering Education. 2016; 32 (3A):1289–1312. [ Google Scholar ]
  • Abid A, Farooq MS, Raza I, Farooq U, Abid K. Variants of teaching first course in database systems. Bulletin of Education and Research. 2015; 37 (2):9–25. [ Google Scholar ]
  • Abid A, Hussain N, Abid K, Ahmad F, Farooq MS, Farooq U, Khan SA, Khan YD, Naeem MA, Sabir N. A survey on search results diversification techniques. Neural Computing and Applications. 2016; 27 (5):1207–1229. [ Google Scholar ]
  • Abourezq, M., & Idrissi, A. (2016). Database-as-a-service for big data: An overview. International Journal of Advanced Computer Science and Applications (IJACSA) , 7 (1).
  • Abut, H., & Ozturk, Y. (1997). Interactive classroom for DSP/communication courses. 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing , 1 , 15–18.
  • Adams ES, Granger M, Goelman D, Ricardo C. Managing the introductory database course: What goes in and what comes out? ACM SIGCSE Bulletin. 2004; 36 (1):497–498. [ Google Scholar ]
  • Akbar, R., & Safdar, S. (2015). A short review of global software development (gsd) and latest software development trends. 2015 International Conference on Computer, Communications, and Control Technology (I4CT) , 314–317.
  • Allsopp DH, DeMarie D, Alvarez-McHatton P, Doone E. Bridging the gap between theory and practice: Connecting courses with field experiences. Teacher Education Quarterly. 2006; 33 (1):19–35. [ Google Scholar ]
  • Alrumaih, H. (2016). ACM/IEEE-CS information technology curriculum 2017: status report. Proceedings of the 1st National Computing Colleges Conference (NC3 2016) .
  • Al-Shuaily, H. (2012). Analyzing the influence of SQL teaching and learning methods and approaches. 10 Th International Workshop on the Teaching, Learning and Assessment of Databases , 3.
  • Amadio, W., Riyami, B., Mansouri, K., Poirier, F., Ramzan, M., Abid, A., Khan, H. U., Awan, S. M., Ismail, A., Ahmed, M., Ilyas, M., Mahmood, A., Hey, A. J. G., Tansley, S., Tolle, K. M., others, Tehseen, R., Farooq, M. S., Abid, A., …, Fatimazahra, E. (2003). The fourth paradigm: data-intensive scientific discovery. Innovation in Teaching and Learning in Information and Computer Sciences , 1 (1), 823–828. https://www.iso.org/standard/27614.html
  • Amadio, W. (2003). The dilemma of Team Learning: An assessment from the SQL programming classroom . 823–828.
  • Ampatzoglou A, Charalampidou S, Stamelos I. Research state of the art on GoF design patterns: A mapping study. Journal of Systems and Software. 2013; 86 (7):1945–1964. [ Google Scholar ]
  • Andersson C, Kroisandt G, Logofatu D. Including active learning in an online database management course for industrial engineering students. IEEE Global Engineering Education Conference (EDUCON) 2019; 2019 :217–220. [ Google Scholar ]
  • Aria M, Cuccurullo C. bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics. 2017; 11 (4):959–975. [ Google Scholar ]
  • Aziz O, Farooq MS, Abid A, Saher R, Aslam N. Research trends in enterprise service bus (ESB) applications: A systematic mapping study. IEEE Access. 2020; 8 :31180–31197. [ Google Scholar ]
  • Bakar MA, Jailani N, Shukur Z, Yatim NFM. Final year supervision management system as a tool for monitoring computer science projects. Procedia-Social and Behavioral Sciences. 2011; 18 :273–281. [ Google Scholar ]
  • Beecham S, Baddoo N, Hall T, Robinson H, Sharp H. Motivation in Software Engineering: A systematic literature review. Information and Software Technology. 2008; 50 (9–10):860–878. [ Google Scholar ]
  • Bhogal, J. K., Cox, S., & Maitland, K. (2012). Roadmap for Modernizing Database Curricula. 10 Th International Workshop on the Teaching, Learning and Assessment of Databases , 73.
  • Bishop, M., Burley, D., Buck, S., Ekstrom, J. J., Futcher, L., Gibson, D., ... & Parrish, A. (2017, May). Cybersecurity curricular guidelines . In IFIP World Conference on Information Security Education (pp. 3–13). Cham: Springer.
  • Brady A, Bruce K, Noonan R, Tucker A, Walker H. The 2003 model curriculum for a liberal arts degree in computer science: preliminary report. ACM SIGCSE Bulletin. 2004; 36 (1):282–283. [ Google Scholar ]
  • Brusilovsky P, Sosnovsky S, Lee DH, Yudelson M, Zadorozhny V, Zhou X. An open integrated exploratorium for database courses. AcM SIGcSE Bulletin. 2008; 40 (3):22–26. [ Google Scholar ]
  • Brusilovsky P, Sosnovsky S, Yudelson MV, Lee DH, Zadorozhny V, Zhou X. Learning SQL programming with interactive tools: From integration to personalization. ACM Transactions on Computing Education (TOCE) 2010; 9 (4):1–15. [ Google Scholar ]
  • Cai, Y., & Gao, T. (2019). Teaching Reform in Database Course for Liberal Arts Majors under the Background of" Internet Plus". 2018 6th International Education, Economics, Social Science, Arts, Sports and Management Engineering Conference (IEESASM 2018) , 208–213.
  • Calderon KR, Vij RS, Mattana J, Jhaveri KD. Innovative teaching tools in nephrology. Kidney International. 2011; 79 (8):797–799. [ PubMed ] [ Google Scholar ]
  • Calero C, Piattini M, Ruiz F. Towards a database body of knowledge: A study from Spain. ACM SIGMOD Record. 2003; 32 (2):48–53. [ Google Scholar ]
  • Canedo, E. D., Bandeira, I. N., & Costa, P. H. T. (2021). Challenges of database systems teaching amidst the Covid-19 pandemic. In 2021 IEEE Frontiers in Education Conference (FIE) (pp. 1–9). IEEE.
  • Chen H-H, Chen Y-J, Chen K-J. The design and effect of a scaffolded concept mapping strategy on learning performance in an undergraduate database course. IEEE Transactions on Education. 2012; 56 (3):300–307. [ Google Scholar ]
  • Cobo MJ, López-Herrera AG, Herrera-Viedma E, Herrera F. SciMAT: A new science mapping analysis software tool. Journal of the American Society for Information Science and Technology. 2012; 63 (8):1609–1630. [ Google Scholar ]
  • Conklin M, Heinrichs L. In search of the right database text. Journal of Computing Sciences in Colleges. 2005; 21 (2):305–312. [ Google Scholar ]
  • Connolly, T. M., & Begg, C. E. (2006). A constructivist-based approach to teaching database analysis and design. Journal of Information Systems Education , 17 (1).
  • Connolly, T. M., Stansfield, M., & McLellan, E. (2005). An online games-based collaborative learning environment to teach database design. Web-Based Education: Proceedings of the Fourth IASTED International Conference(WBE-2005) .
  • Curricula Computing. (1991). Report of the ACM/IEEE-CS Joint Curriculum Task Force. Technical Report . New York: Association for Computing Machinery.
  • Cvetanovic M, Radivojevic Z, Blagojevic V, Bojovic M. ADVICE—Educational system for teaching database courses. IEEE Transactions on Education. 2010; 54 (3):398–409. [ Google Scholar ]
  • Damian, D., Hadwin, A., & Al-Ani, B. (2006). Instructional design and assessment strategies for teaching global software development: a framework. Proceedings of the 28th International Conference on Software Engineering , 685–690.
  • Dean, T. J., & Milani, W. G. (1995). Transforming a database systems and design course for non computer science majors. Proceedings Frontiers in Education 1995 25th Annual Conference. Engineering Education for the 21st Century , 2 , 4b2--17.
  • Dicheva, D., Dichev, C., Agre, G., & Angelova, G. (2015). Gamification in education: A systematic mapping study. Journal of Educational Technology \& Society , 18 (3), 75–88.
  • Dietrich SW, Urban SD, Haag S. Developing advanced courses for undergraduates: A case study in databases. IEEE Transactions on Education. 2008; 51 (1):138–144. [ Google Scholar ]
  • Dietrich SW, Goelman D, Borror CM, Crook SM. An animated introduction to relational databases for many majors. IEEE Transactions on Education. 2014; 58 (2):81–89. [ Google Scholar ]
  • Dietrich, S. W., & Urban, S. D. (1996). Database theory in practice: learning from cooperative group projects. Proceedings of the Twenty-Seventh SIGCSE Technical Symposium on Computer Science Education , 112–116.
  • Dominguez, C., & Jaime, A. (2010). Database design learning: A project-based approach organized through a course management system. Computers \& Education , 55 (3), 1312–1320.
  • Eaglestone, B., & Nunes, M. B. (2004). Pragmatics and practicalities of teaching and learning in the quicksand of database syllabuses. Journal of Innovations in Teaching and Learning for Information and Computer Sciences , 3 (1).
  • Efendiouglu A, Yelken TY. Programmed instruction versus meaningful learning theory in teaching basic structured query language (SQL) in computer lesson. Computers & Education. 2010; 55 (3):1287–1299. [ Google Scholar ]
  • Elberzhager F, Münch J, Nha VTN. A systematic mapping study on the combination of static and dynamic quality assurance techniques. Information and Software Technology. 2012; 54 (1):1–15. [ Google Scholar ]
  • Etemad M, Küpçü A. Verifiable database outsourcing supporting join. Journal of Network and Computer Applications. 2018; 115 :1–19. [ Google Scholar ]
  • Farooq MS, Riaz S, Abid A, Abid K, Naeem MA. A Survey on the role of IoT in agriculture for the implementation of smart farming. IEEE Access. 2019; 7 :156237–156271. [ Google Scholar ]
  • Farooq MS, Riaz S, Abid A, Umer T, Zikria YB. Role of IoT technology in agriculture: A systematic literature review. Electronics. 2020; 9 (2):319. [ Google Scholar ]
  • Farooq U, Rahim MSM, Sabir N, Hussain A, Abid A. Advances in machine translation for sign language: Approaches, limitations, and challenges. Neural Computing and Applications. 2021; 33 (21):14357–14399. [ Google Scholar ]
  • Fisher, D., & Khine, M. S. (2006). Contemporary approaches to research on learning environments: Worldviews . World Scientific.
  • Garcia-Molina, H. (2008). Database systems: the complete book . Pearson Education India.
  • Garousi V, Mesbah A, Betin-Can A, Mirshokraie S. A systematic mapping study of web application testing. Information and Software Technology. 2013; 55 (8):1374–1396. [ Google Scholar ]
  • Gudivada, V. N., Nandigam, J., & Tao, Y. (2007). Enhancing student learning in database courses with large data sets. 2007 37th Annual Frontiers In Education Conference-Global Engineering: Knowledge Without Borders, Opportunities Without Passports , S2D--13.
  • Hey, A. J. G., Tansley, S., Tolle, K. M., & others. (2009). The fourth paradigm: data-intensive scientific discovery (Vol. 1). Microsoft research Redmond, WA.
  • Holliday, M. A., & Wang, J. Z. (2009). A multimedia database project and the evolution of the database course. 2009 39th IEEE Frontiers in Education Conference , 1–6.
  • Hou, S., & Chen, S. (2010). Research on applying the theory of Blending Learning on Access Database Programming Course teaching. 2010 2nd International Conference on Education Technology and Computer , 3 , V3--396.
  • Irby DM, Wilkerson L. Educational innovations in academic medicine and environmental trends. Journal of General Internal Medicine. 2003; 18 (5):370–376. [ PMC free article ] [ PubMed ] [ Google Scholar ]
  • Ishaq K, Zin NAM, Rosdi F, Jehanghir M, Ishaq S, Abid A. Mobile-assisted and gamification-based language learning: A systematic literature review. PeerJ Computer Science. 2021; 7 :e496. [ PMC free article ] [ PubMed ] [ Google Scholar ]
  • Joint Task Force on Computing Curricula, A. F. C. M. (acm), & Society, I. C. (2013). Computer science curricula 2013: Curriculum guidelines for undergraduate degree programs in computer science . New York, NY, USA: Association for Computing Machinery.
  • Juxiang R, Zhihong N. Taking database design as trunk line of database courses. Fourth International Conference on Computational and Information Sciences. 2012; 2012 :767–769. [ Google Scholar ]
  • Kawash, J., Jarada, T., & Moshirpour, M. (2020). Group exams as learning tools: Evidence from an undergraduate database course. Proceedings of the 51st ACM Technical Symposium on Computer Science Education , 626–632.
  • Keele, S., et al. (2007). Guidelines for performing systematic literature reviews in software engineering .
  • Kleiner, C. (2015). New Concepts in Database System Education: Experiences and Ideas. Proceedings of the 46th ACM Technical Symposium on Computer Science Education , 698.
  • Ko J, Paek S, Park S, Park J. A news big data analysis of issues in higher education in Korea amid the COVID-19 pandemic. Sustainability. 2021; 13 (13):7347. [ Google Scholar ]
  • Kui, X., Du, H., Zhong, P., & Liu, W. (2018). Research and application of flipped classroom in database course. 2018 13th International Conference on Computer Science \& Education (ICCSE) , 1–5.
  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics , 159–174. [ PubMed ]
  • Lunt, B., Ekstrom, J., Gorka, S., Hislop, G., Kamali, R., Lawson, E., ... & Reichgelt, H. (2008). Curriculum guidelines for undergraduate degree programs in information technology . ACM.
  • Luo, R., Wu, M., Zhu, Y., & Shen, Y. (2008). Exploration of Curriculum Structures and Educational Models of Database Applications. 2008 The 9th International Conference for Young Computer Scientists , 2664–2668.
  • Luxton-Reilly, A., Albluwi, I., Becker, B. A., Giannakos, M., Kumar, A. N., Ott, L., Paterson, J., Scott, M. J., Sheard, J., & Szabo, C. (2018). Introductory programming: a systematic literature review. Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education , 55–106.
  • Manzoor MF, Abid A, Farooq MS, Nawaz NA, Farooq U. Resource allocation techniques in cloud computing: A review and future directions. Elektronika Ir Elektrotechnika. 2020; 26 (6):40–51. doi: 10.5755/j01.eie.26.6.25865. [ CrossRef ] [ Google Scholar ]
  • Marshall, L. (2011). Developing a computer science curriculum in the South African context. CSERC , 9–19.
  • Marshall, L. (2012). A comparison of the core aspects of the acm/ieee computer science curriculum 2013 strawman report with the specified core of cc2001 and cs2008 review. Proceedings of Second Computer Science Education Research Conference , 29–34.
  • Martin C, Urpi T, Casany MJ, Illa XB, Quer C, Rodriguez ME, Abello A. Improving learning in a database course using collaborative learning techniques. The International Journal of Engineering Education. 2013; 29 (4):986–997. [ Google Scholar ]
  • Martinez-González MM, Duffing G. Teaching databases in compliance with the European dimension of higher education: Best practices for better competences. Education and Information Technologies. 2007; 12 (4):211–228. [ Google Scholar ]
  • Mateo PR, Usaola MP, Alemán JLF. Validating second-order mutation at system level. IEEE Transactions on Software Engineering. 2012; 39 (4):570–587. [ Google Scholar ]
  • Mathieu, R. G., & Khalil, O. (1997). Teaching Data Quality in the Undergraduate Database Course. IQ , 249–266.
  • Mcintyre, D. R., Pu, H.-C., & Wolff, F. G. (1995). Use of software tools in teaching relational database design. Computers \& Education , 24 (4), 279–286.
  • Mehmood E, Abid A, Farooq MS, Nawaz NA. Curriculum, teaching and learning, and assessments for introductory programming course. IEEE Access. 2020; 8 :125961–125981. [ Google Scholar ]
  • Meier, R., Barnicki, S. L., Barnekow, W., & Durant, E. (2008). Work in progress-Year 2 results from a balanced, freshman-first computer engineering curriculum. In 38th Annual Frontiers in Education Conference (pp. S1F-17). IEEE.
  • Meyer B. Software engineering in the academy. Computer. 2001; 34 (5):28–35. [ Google Scholar ]
  • Mingyu, L., Jianping, J., Yi, Z., & Cuili, Z. (2017). Research on the teaching reform of database curriculum major in computer in big data era. 2017 12th International Conference on Computer Science and Education (ICCSE) , 570–573.
  • Morien, R. I. (2006). A Critical Evaluation Database Textbooks, Curriculum and Educational Outcomes. Director , 7 .
  • Mushtaq Z, Rasool G, Shehzad B. Multilingual source code analysis: A systematic literature review. IEEE Access. 2017; 5 :11307–11336. [ Google Scholar ]
  • Myers M, Skinner P. The gap between theory and practice: A database application case study. Journal of International Information Management. 1997; 6 (1):5. [ Google Scholar ]
  • Naeem A, Farooq MS, Khelifi A, Abid A. Malignant melanoma classification using deep learning: Datasets, performance measurements, challenges and opportunities. IEEE Access. 2020; 8 :110575–110597. [ Google Scholar ]
  • Nagataki, H., Nakano, Y., Nobe, M., Tohyama, T., & Kanemune, S. (2013). A visual learning tool for database operation. Proceedings of the 8th Workshop in Primary and Secondary Computing Education , 39–40.
  • Naik, S., & Gajjar, K. (2021). Applying and Evaluating Engagement and Application-Based Learning and Education (ENABLE): A Student-Centered Learning Pedagogy for the Course Database Management System. Journal of Education , 00220574211032319.
  • Nelson, D., Stirk, S., Patience, S., & Green, C. (2003). An evaluation of a diverse database teaching curriculum and the impact of research. 1st LTSN Workshop on Teaching, Learning and Assessment of Databases, Coventry .
  • Nelson D, Fatimazahra E. Review of Contributions to the Teaching, Learning and Assessment of Databases (TLAD) Workshops. Innovation in Teaching and Learning in Information and Computer Sciences. 2010; 9 (1):78–86. [ Google Scholar ]
  • Obaid I, Farooq MS, Abid A. Gamification for recruitment and job training: Model, taxonomy, and challenges. IEEE Access. 2020; 8 :65164–65178. [ Google Scholar ]
  • Pahl C, Barrett R, Kenny C. Supporting active database learning and training through interactive multimedia. ACM SIGCSE Bulletin. 2004; 36 (3):27–31. [ Google Scholar ]
  • Park, Y., Tajik, A. S., Cafarella, M., & Mozafari, B. (2017). Database learning: Toward a database that becomes smarter every time. Proceedings of the 2017 ACM International Conference on Management of Data , 587–602.
  • Picciano AG. The evolution of big data and learning analytics in American higher education. Journal of Asynchronous Learning Networks. 2012; 16 (3):9–20. [ Google Scholar ]
  • Prince MJ, Felder RM. Inductive teaching and learning methods: Definitions, comparisons, and research bases. Journal of Engineering Education. 2006; 95 (2):123–138. [ Google Scholar ]
  • Ramzan M, Abid A, Khan HU, Awan SM, Ismail A, Ahmed M, Ilyas M, Mahmood A. A review on state-of-the-art violence detection techniques. IEEE Access. 2019; 7 :107560–107575. [ Google Scholar ]
  • Rashid, T. A., & Al-Radhy, R. S. (2014). Transformations to issues in teaching, learning, and assessing methods in databases courses. 2014 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE) , 252–256.
  • Rashid, T. (2015). Investigation of instructing reforms in databases. International Journal of Scientific \& Engineering Research , 6 (8), 64–72.
  • Regueras, L. M., Verdú, E., Verdú, M. J., Pérez, M. A., & De Castro, J. P. (2007). E-learning strategies to support databases courses: a case study. First International Conference on Technology, Training and Communication .
  • Robbert MA, Ricardo CM. Trends in the evolution of the database curriculum. ACM SIGCSE Bulletin. 2003; 35 (3):139–143. [ Google Scholar ]
  • Sahami, M., Guzdial, M., McGettrick, A., & Roach, S. (2011). Setting the stage for computing curricula 2013: computer science--report from the ACM/IEEE-CS joint task force. Proceedings of the 42nd ACM Technical Symposium on Computer Science Education , 161–162.
  • Sciore E. SimpleDB: A simple java-based multiuser syst for teaching database internals. ACM SIGCSE Bulletin. 2007; 39 (1):561–565. [ Google Scholar ]
  • Shebaro B. Using active learning strategies in teaching introductory database courses. Journal of Computing Sciences in Colleges. 2018; 33 (4):28–36. [ Google Scholar ]
  • Sibia, N., & Liut, M. (2022, June). The Positive Effects of using Reflective Prompts in a Database Course. In 1st International Workshop on Data Systems Education (pp. 32–37).
  • Silva, Y. N., Almeida, I., & Queiroz, M. (2016). SQL: From traditional databases to big data. Proceedings of the 47th ACM Technical Symposium on Computing Science Education , 413–418.
  • Sobel, A. E. K. (2003). Computing Curricula--Software Engineering Volume. Proc. of the Final Draft of the Software Engineering Education Knowledge (SEEK) .
  • Suryn, W., Abran, A., & April, A. (2003). ISO/IEC SQuaRE: The second generation of standards for software product quality .
  • Svahnberg, M., Aurum, A., & Wohlin, C. (2008). Using students as subjects-an empirical evaluation. Proceedings of the Second ACM-IEEE International Symposium on Empirical Software Engineering and Measurement , 288–290.
  • Swebok evolution: IEEE Computer Society. (n.d.). In IEEE Computer Society SWEBOK Evolution Comments . Retrieved March 24, 2021 https://www.computer.org/volunteering/boards-and-committees/professional-educational-activities/software-engineering-committee/swebok-evolution
  • Taipalus T, Seppänen V. SQL education: A systematic mapping study and future research agenda. ACM Transactions on Computing Education (TOCE) 2020; 20 (3):1–33. [ Google Scholar ]
  • Taipalus T, Siponen M, Vartiainen T. Errors and complications in SQL query formulation. ACM Transactions on Computing Education (TOCE) 2018; 18 (3):1–29. [ Google Scholar ]
  • Taipalus, T., & Perälä, P. (2019). What to expect and what to focus on in SQL query teaching. Proceedings of the 50th ACM Technical Symposium on Computer Science Education , 198–203.
  • Tehseen R, Farooq MS, Abid A. Earthquake prediction using expert systems: A systematic mapping study. Sustainability. 2020; 12 (6):2420. [ Google Scholar ]
  • Urban, S. D., & Dietrich, S. W. (2001). Advanced database concepts for undergraduates: experience with teaching a second course. Proceedings of the Thirty-Second SIGCSE Technical Symposium on Computer Science Education , 357–361.
  • Urban SD, Dietrich SW. Integrating the practical use of a database product into a theoretical curriculum. ACM SIGCSE Bulletin. 1997; 29 (1):121–125. [ Google Scholar ]
  • Wang, J., & Chen, H. (2014). Research and practice on the teaching reform of database course. International Conference on Education Reform and Modern Management, ERMM .
  • Wang, J. Z., Davis, T. A., Westall, J. M., & Srimani, P. K. (2010). Undergraduate database instruction with MeTube. Proceedings of the Fifteenth Annual Conference on Innovation and Technology in Computer Science Education , 279–283.
  • Yau, G., & Karim, S. W. (2003). Smart classroom: Enhancing collaborative learning using pervasive computing technology. II American Society… .
  • Yue K-B. Using a semi-realistic database to support a database course. Journal of Information Systems Education. 2013; 24 (4):327. [ Google Scholar ]
  • Yuelan L, Yiwei L, Yuyan H, Yuefan L. Study on teaching methods of database application courses. Procedia Engineering. 2011; 15 :5425–5428. [ Google Scholar ]
  • Zhang, X., Wang, X., Liu, Z., Xue, W., & ZHU, X. (2018). The Exploration and Practice on the Classroom Teaching Reform of the Database Technologies Course in colleges. 2018 3rd International Conference on Modern Management, Education Technology, and Social Science (MMETSS 2018) , 320–323.
  • Zhanquan W, Zeping Y, Chunhua G, Fazhi Z, Weibin G. Research of database curriculum construction under the environment of massive open online courses. International Journal of Educational and Pedagogical Sciences. 2016; 10 (12):3873–3877. [ Google Scholar ]
  • Zheng, Y., & Dong, J. (2011). Teaching reform and practice of database principles. 2011 6th International Conference on Computer Science \& Education (ICCSE) , 1460–1462.
  • How It Works

214 Best Big Data Research Topics for Your Thesis Paper

big data research topics

Finding an ideal big data research topic can take you a long time. Big data, IoT, and robotics have evolved. The future generations will be immersed in major technologies that will make work easier. Work that was done by 10 people will now be done by one person or a machine. This is amazing because, in as much as there will be job loss, more jobs will be created. It is a win-win for everyone. Big data is a major topic that is being embraced globally. Data science and analytics are helping institutions, governments, and the private sector. We will share with you the best big data research topics. On top of that, we can offer you the best writing tips to ensure you prosper well in your academics. As students in the university, you need to do proper research to get top grades. Hence, you can consult us if in need of research paper writing services .

Big Data Analytics Research Topics for your Research Project

Are you looking for an ideal big data analytics research topic? Once you choose a topic, consult your professor to evaluate whether it is a great topic. This will help you to get good grades.

  • Which are the best tools and software for big data processing?
  • Evaluate the security issues that face big data.
  • An analysis of large-scale data for social networks globally.
  • The influence of big data storage systems.
  • The best platforms for big data computing.
  • The relation between business intelligence and big data analytics.
  • The importance of semantics and visualization of big data.
  • Analysis of big data technologies for businesses.
  • The common methods used for machine learning in big data.
  • The difference between self-turning and symmetrical spectral clustering.
  • The importance of information-based clustering.
  • Evaluate the hierarchical clustering and density-based clustering application.
  • How is data mining used to analyze transaction data?
  • The major importance of dependency modeling.
  • The influence of probabilistic classification in data mining.

Interesting Big Data Analytics Topics

Who said big data had to be boring? Here are some interesting big data analytics topics that you can try. They are based on how some phenomena are done to make the world a better place.

  • Discuss the privacy issues in big data.
  • Evaluate the storage systems of scalable in big data.
  • The best big data processing software and tools.
  • Data mining tools and techniques are popularly used.
  • Evaluate the scalable architectures for parallel data processing.
  • The major natural language processing methods.
  • Which are the best big data tools and deployment platforms?
  • The best algorithms for data visualization.
  • Analyze the anomaly detection in cloud servers
  • The scrutiny normally done for the recruitment of big data job profiles.
  • The malicious user detection in big data collection.
  • Learning long-term dependencies via the Fourier recurrent units.
  • Nomadic computing for big data analytics.
  • The elementary estimators for graphical models.
  • The memory-efficient kernel approximation.

Big Data Latest Research Topics

Do you know the latest research topics at the moment? These 15 topics will help you to dive into interesting research. You may even build on research done by other scholars.

  • Evaluate the data mining process.
  • The influence of the various dimension reduction methods and techniques.
  • The best data classification methods.
  • The simple linear regression modeling methods.
  • Evaluate the logistic regression modeling.
  • What are the commonly used theorems?
  • The influence of cluster analysis methods in big data.
  • The importance of smoothing methods analysis in big data.
  • How is fraud detection done through AI?
  • Analyze the use of GIS and spatial data.
  • How important is artificial intelligence in the modern world?
  • What is agile data science?
  • Analyze the behavioral analytics process.
  • Semantic analytics distribution.
  • How is domain knowledge important in data analysis?

Big Data Debate Topics

If you want to prosper in the field of big data, you need to try even hard topics. These big data debate topics are interesting and will help you to get a better understanding.

  • The difference between big data analytics and traditional data analytics methods.
  • Why do you think the organization should think beyond the Hadoop hype?
  • Does the size of the data matter more than how recent the data is?
  • Is it true that bigger data are not always better?
  • The debate of privacy and personalization in maintaining ethics in big data.
  • The relation between data science and privacy.
  • Do you think data science is a rebranding of statistics?
  • Who delivers better results between data scientists and domain experts?
  • According to your view, is data science dead?
  • Do you think analytics teams need to be centralized or decentralized?
  • The best methods to resource an analytics team.
  • The best business case for investing in analytics.
  • The societal implications of the use of predictive analytics within Education.
  • Is there a need for greater control to prevent experimentation on social media users without their consent?
  • How is the government using big data; for the improvement of public statistics or to control the population?

University Dissertation Topics on Big Data

Are you doing your Masters or Ph.D. and wondering the best dissertation topic or thesis to do? Why not try any of these? They are interesting and based on various phenomena. While doing the research ensure you relate the phenomenon with the current modern society.

  • The machine learning algorithms are used for fall recognition.
  • The divergence and convergence of the internet of things.
  • The reliable data movements using bandwidth provision strategies.
  • How is big data analytics using artificial neural networks in cloud gaming?
  • How is Twitter accounts classification done using network-based features?
  • How is online anomaly detection done in the cloud collaborative environment?
  • Evaluate the public transportation insights provided by big data.
  • Evaluate the paradigm for cancer patients using the nursing EHR to predict the outcome.
  • Discuss the current data lossless compression in the smart grid.
  • How does online advertising traffic prediction helps in boosting businesses?
  • How is the hyperspectral classification done using the multiple kernel learning paradigm?
  • The analysis of large data sets downloaded from websites.
  • How does social media data help advertising companies globally?
  • Which are the systems recognizing and enforcing ownership of data records?
  • The alternate possibilities emerging for edge computing.

The Best Big Data Analysis Research Topics and Essays

There are a lot of issues that are associated with big data. Here are some of the research topics that you can use in your essays. These topics are ideal whether in high school or college.

  • The various errors and uncertainty in making data decisions.
  • The application of big data on tourism.
  • The automation innovation with big data or related technology
  • The business models of big data ecosystems.
  • Privacy awareness in the era of big data and machine learning.
  • The data privacy for big automotive data.
  • How is traffic managed in defined data center networks?
  • Big data analytics for fault detection.
  • The need for machine learning with big data.
  • The innovative big data processing used in health care institutions.
  • The money normalization and extraction from texts.
  • How is text categorization done in AI?
  • The opportunistic development of data-driven interactive applications.
  • The use of data science and big data towards personalized medicine.
  • The programming and optimization of big data applications.

The Latest Big Data Research Topics for your Research Proposal

Doing a research proposal can be hard at first unless you choose an ideal topic. If you are just diving into the big data field, you can use any of these topics to get a deeper understanding.

  • The data-centric network of things.
  • Big data management using artificial intelligence supply chain.
  • The big data analytics for maintenance.
  • The high confidence network predictions for big biological data.
  • The performance optimization techniques and tools for data-intensive computation platforms.
  • The predictive modeling in the legal context.
  • Analysis of large data sets in life sciences.
  • How to understand the mobility and transport modal disparities sing emerging data sources?
  • How do you think data analytics can support asset management decisions?
  • An analysis of travel patterns for cellular network data.
  • The data-driven strategic planning for citywide building retrofitting.
  • How is money normalization done in data analytics?
  • Major techniques used in data mining.
  • The big data adaptation and analytics of cloud computing.
  • The predictive data maintenance for fault diagnosis.

Interesting Research Topics on A/B Testing In Big Data

A/B testing topics are different from the normal big data topics. However, you use an almost similar methodology to find the reasons behind the issues. These topics are interesting and will help you to get a deeper understanding.

  • How is ultra-targeted marketing done?
  • The transition of A/B testing from digital to offline.
  • How can big data and A/B testing be done to win an election?
  • Evaluate the use of A/B testing on big data
  • Evaluate A/B testing as a randomized control experiment.
  • How does A/B testing work?
  • The mistakes to avoid while conducting the A/B testing.
  • The most ideal time to use A/B testing.
  • The best way to interpret results for an A/B test.
  • The major principles of A/B tests.
  • Evaluate the cluster randomization in big data
  • The best way to analyze A/B test results and the statistical significance.
  • How is A/B testing used in boosting businesses?
  • The importance of data analysis in conversion research
  • The importance of A/B testing in data science.

Amazing Research Topics on Big Data and Local Governments

Governments are now using big data to make the lives of the citizens better. This is in the government and the various institutions. They are based on real-life experiences and making the world better.

  • Assess the benefits and barriers of big data in the public sector.
  • The best approach to smart city data ecosystems.
  • The big analytics used for policymaking.
  • Evaluate the smart technology and emergence algorithm bureaucracy.
  • Evaluate the use of citizen scoring in public services.
  • An analysis of the government administrative data globally.
  • The public values are found in the era of big data.
  • Public engagement on local government data use.
  • Data analytics use in policymaking.
  • How are algorithms used in public sector decision-making?
  • The democratic governance in the big data era.
  • The best business model innovation to be used in sustainable organizations.
  • How does the government use the collected data from various sources?
  • The role of big data for smart cities.
  • How does big data play a role in policymaking?

Easy Research Topics on Big Data

Who said big data topics had to be hard? Here are some of the easiest research topics. They are based on data management, research, and data retention. Pick one and try it!

  • Who uses big data analytics?
  • Evaluate structure machine learning.
  • Explain the whole deep learning process.
  • Which are the best ways to manage platforms for enterprise analytics?
  • Which are the new technologies used in data management?
  • What is the importance of data retention?
  • The best way to work with images is when doing research.
  • The best way to promote research outreach is through data management.
  • The best way to source and manage external data.
  • Does machine learning improve the quality of data?
  • Describe the security technologies that can be used in data protection.
  • Evaluate token-based authentication and its importance.
  • How can poor data security lead to the loss of information?
  • How to determine secure data.
  • What is the importance of centralized key management?

Unique IoT and Big Data Research Topics

Internet of Things has evolved and many devices are now using it. There are smart devices, smart cities, smart locks, and much more. Things can now be controlled by the touch of a button.

  • Evaluate the 5G networks and IoT.
  • Analyze the use of Artificial intelligence in the modern world.
  • How do ultra-power IoT technologies work?
  • Evaluate the adaptive systems and models at runtime.
  • How have smart cities and smart environments improved the living space?
  • The importance of the IoT-based supply chains.
  • How does smart agriculture influence water management?
  • The internet applications naming and identifiers.
  • How does the smart grid influence energy management?
  • Which are the best design principles for IoT application development?
  • The best human-device interactions for the Internet of Things.
  • The relation between urban dynamics and crowdsourcing services.
  • The best wireless sensor network for IoT security.
  • The best intrusion detection in IoT.
  • The importance of big data on the Internet of Things.

Big Data Database Research Topics You Should Try

Big data is broad and interesting. These big data database research topics will put you in a better place in your research. You also get to evaluate the roles of various phenomena.

  • The best cloud computing platforms for big data analytics.
  • The parallel programming techniques for big data processing.
  • The importance of big data models and algorithms in research.
  • Evaluate the role of big data analytics for smart healthcare.
  • How is big data analytics used in business intelligence?
  • The best machine learning methods for big data.
  • Evaluate the Hadoop programming in big data analytics.
  • What is privacy-preserving to big data analytics?
  • The best tools for massive big data processing
  • IoT deployment in Governments and Internet service providers.
  • How will IoT be used for future internet architectures?
  • How does big data close the gap between research and implementation?
  • What are the cross-layer attacks in IoT?
  • The influence of big data and smart city planning in society.
  • Why do you think user access control is important?

Big Data Scala Research Topics

Scala is a programming language that is used in data management. It is closely related to other data programming languages. Here are some of the best scala questions that you can research.

  • Which are the most used languages in big data?
  • How is scala used in big data research?
  • Is scala better than Java in big data?
  • How is scala a concise programming language?
  • How does the scala language stream process in real-time?
  • Which are the various libraries for data science and data analysis?
  • How does scala allow imperative programming in data collection?
  • Evaluate how scala includes a useful REPL for interaction.
  • Evaluate scala’s IDE support.
  • The data catalog reference model.
  • Evaluate the basics of data management and its influence on research.
  • Discuss the behavioral analytics process.
  • What can you term as the experience economy?
  • The difference between agile data science and scala language.
  • Explain the graph analytics process.

Independent Research Topics for Big Data

These independent research topics for big data are based on the various technologies and how they are related. Big data will greatly be important for modern society.

  • The biggest investment is in big data analysis.
  • How are multi-cloud and hybrid settings deep roots?
  • Why do you think machine learning will be in focus for a long while?
  • Discuss in-memory computing.
  • What is the difference between edge computing and in-memory computing?
  • The relation between the Internet of things and big data.
  • How will digital transformation make the world a better place?
  • How does data analysis help in social network optimization?
  • How will complex big data be essential for future enterprises?
  • Compare the various big data frameworks.
  • The best way to gather and monitor traffic information using the CCTV images
  • Evaluate the hierarchical structure of groups and clusters in the decision tree.
  • Which are the 3D mapping techniques for live streaming data.
  • How does machine learning help to improve data analysis?
  • Evaluate DataStream management in task allocation.
  • How is big data provisioned through edge computing?
  • The model-based clustering of texts.
  • The best ways to manage big data.
  • The use of machine learning in big data.

Is Your Big Data Thesis Giving You Problems?

These are some of the best topics that you can use to prosper in your studies. Not only are they easy to research but also reflect on real-time issues. Whether in University or college, you need to put enough effort into your studies to prosper. However, if you have time constraints, we can provide professional writing help. Are you looking for online expert writers? Look no further, we will provide quality work at a cheap price.

pros and cons topics

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Comment * Error message

Name * Error message

Email * Error message

Save my name, email, and website in this browser for the next time I comment.

As Putin continues killing civilians, bombing kindergartens, and threatening WWIII, Ukraine fights for the world's peaceful future.

Ukraine Live Updates

iNetTutor.com

Online Programming Lessons, Tutorials and Capstone Project guide

40 List of DBMS Project Topics and Ideas

Introduction

A Capstone project is the last project of an IT degree program. It is made up of one or more research projects in which students create prototypes, services, and/or products. The projects are organized around an issue that needs to be handled in real-world scenarios. When IT departments want to test new ideas or concepts that will be adopted into their daily operations, they implement these capstone projects within their services.

In this article, our team has compiled a list of Database Management System Project Topics and Ideas. The capstone projects listed below will assist future researchers in deciding which capstone project idea to pursue. Future researchers may find the information in this page useful in coming up with unique capstone project ideas.

  • Telemedicine Online Platform Database Design

  “Telemedicine Online Platform” is designed to allow doctors to deliver clinical support to patients remotely. Doctors can communicate with their patients in real-time for consultations, diagnoses, monitoring, and medical supply prescriptions. The project will be developed using the SDLC method by the researchers. The researchers will also compile a sample of hospital doctors and patients who will act as study participants. A panel of IT specialists will review, test, and assess the project.

  • Virtual and Remote Guidance Counselling System Database Design

Counseling is a vital component of a person’s life since it aids in the improvement of interpersonal relationships. Humans must cease ignoring this issue because it is essential for the development of mental wellness. The capstone project “Virtual and Remote Guidance Counselling System,” which covers the gap in giving counseling in stressful situations, was built for this reason. It answers to the requirement to fill in the gaps in the traditional technique and make it more effective and immersive in this way.

Virtual and Remote Guidance Counselling System Database Design - Relationship

  • COVID-19 Facilities Management Information System Database Design

COVID – 19 has put people in fear due to its capability of transmission when exposed to the virus. The health sectors and the government provide isolation facilities for COVID-19 patients to mitigate the spread and transmission of the virus. However, proper communication for the availability of the facilities is inefficient resulting to surge of patients in just one facility and some are transferred multiple times due to unavailability. The COVID-19 respondents must have an advance tools to manage the COVID-19 facilities where respondents can easily look for available facilities to cater more patients.

  • Document Tracking System Database Design

The capstone project, “Document Tracking System” is purposely designed for companies and organizations that allow them to electronically store and track documents. The system will track the in/out of the documents across different departments. The typical way of tracking documents is done using the manual approach. The staff will call or personally ask for updates about the documents which are time-consuming and inefficient.

  • Face Recognition Application Database Design

Technology has grown so fast; it changes the way we do our daily tasks. Technology has made our daily lives easier. The capstone project, entitled “Face Recognition Attendance System” is designed to automate checking and recording of students’ attendance during school events using face recognition technology. The system will work by storing the student’s information along with their photographs in a server and the system will detect the faces of the students during school events and match it and verify to record the presence or absence of the student.

Face Recognition Application Database Design - List of Tables

  • Digital Wallet Solution Database Design

The capstone project, named “Digital Wallet Solution,” is intended to allow people to store money online and make payments online. The digital wallet transactions accept a variety of currencies and provide a variety of payment gateways via which the user can pay for products and services. The system allows users to conduct secure and convenient online financial transactions. It will speed up payment and other financial processes, reducing the amount of time and effort required to complete them.

  • Virtual Online Tour Application Database Design

The usage of technology is an advantage in the business industry, especially during this challenging pandemic. It allows businesses to continue to operate beyond physicality. The capstone project entitled “Virtual Online Tour Application” is designed as a platform to streamline virtual tours for clients. Any business industry can use the system to accommodate and provide their clients with a virtual experience of their business. For example, the tourist industry and real estate agencies can use the system to provide a virtual tour to their clients about the tourist locations and designs of properties, respectively.

  • Invoice Management System Database Design

The researchers will create a system that will make it easier for companies to manage and keep track of their invoice information. The company’s sales records, payables, and total invoice records will all be electronically managed using this project. Technology is highly used for business operations and transactions automation. The capstone project, entitled “Invoice Management System” is designed to automate the management of the company’s invoice records. The said project will help companies to have an organized, accurate, and reliable record that will help them track their sales and finances.

Invoice Management System Database Design - List of Tables

  • Vehicle Repair and Maintenance Management System Database Design

Information Technology has become an integral part of any kind of business in terms of automating business operations and transactions. The capstone project, entitled “Vehicle Repair and Maintenance Management System” is designed for vehicle repair and maintenance management automation. The said project will automate the vehicle garage’s operations and daily transactions. The system will automate operations such as managing vehicle repair and maintenance records, invoice records, customer records, transaction records, billing and payment records, and transaction records.

  • Transcribe Medical Database Design

Information technology has made everything easier and simpler, including transcribing the medical diagnosis of patients. The capstone project, entitled “Medical Transcription Platform,” is designed to allow medical transcriptionists to transcribe audio of medical consultations and diagnose patients in a centralized manner. A medical transcriptionist is vital to keep accurate and credible medical records of patients and can be used by other doctors to know the patients’ medical history. The said project will serve as a platform where transcribed medical audios are stored for safekeeping and easy retrieval.

  • Multi-branch Travel Agency and Booking System Database Design

The capstone project, entitled “Multi-Branch Travel Agency and Booking System,” is designed as a centralized platform wherein multiple travel agency branches are registered to ease and simplify inquiries and booking of travels and tour packages by clients. The said project will allow travel agencies to operate a business in an easy, fast manner considering the convenience and safety of their clients. The system will enable travel agencies and their clients to have a seamless online transaction.

  • Pharmacy Stocks Management Database Design

The capstone project “Pharmacy Stocks Management System” allows pharmacies to manage and monitor their stocks of drugs electronically. The Pharmacy Stocks Management System will automate inventory to help ensure that the pharmacy has enough stock of medications and supplies to serve the needs of the patients.

  • Loan Management with SMS Database Design

The capstone project entitled “ Loan Management System with SMS ” is an online platform that allows members to apply and request loan. In addition, they can also monitor their balance in their respective dashboard. Management of cooperative will review first the application for approval or disapproval of the request. Notification will be send through the SMS or short messaging service feature of the system.

Loan Management System with SMS Database Design - List of Tables

  • Service Call Management System Database Design

The capstone project, entitled ” Service Call Management System,” is designed to transform service calls to a centralized platform. The said project would allow clients to log in and lodge calls to the tech support if they encountered issues and difficulties with their purchased products. The tech support team will diagnose the issue and provide them with the necessary actions to perform via a call to solve the problem and achieve satisfaction.

  • File Management with Approval Process Database Design

The File Management System provides a platform for submitting, approving, storing, and retrieving files. Specifically, the capstone project is for the file management of various business organizations. This is quite beneficial in the management and organization of the files of every department. Installation of the system on an intranet is possible, as is uploading the system to a live server, from which the platform can be viewed online and through the use of a browser.

  • Beauty Parlor Management System Database Design

The capstone project entitled “Beauty Parlour Management System” is an example of transactional processing system that focuses on the records and process of a beauty parlour. This online application will help the management to keep and manage their transactions in an organize, fast and efficient manner.

  • Exam Management System Database Design

Information technology plays a significant role in the teaching and learning process of teachers and students, respectively. IT offers a more efficient and convenient way for teachers and students to learn and assess learnings. The capstone project, “Exam Management System,” is designed to allow electronic management of all the information about the exam questions, courses and subjects, and teachers and students. The said project is an all-in-one platform for student exam management.

Exam Management System Database Design - List of Tables

  • Student and Faculty Clearance Database Design

The capstone project, entitled “Student and Faculty Clearance System,” is designed to automate students and faculty clearance processes. The approach is intended to make the clearance procedure easier while also guaranteeing that approvals are accurate and complete. The project works by giving every Department involved access to the application. The proposed scheme can eliminate the specified challenges, streamline the process, and verify the integrity and correctness of the data.

  • Vehicle Parking Management System Database Design

The capstone project entitled “ Vehicle Parking Management System ” is an online platform that allows vehicle owners to request or reserve a slot for parking space. Management can accept and decline the request of reservation. In addition, payment option is also part of the system feature but is limited to on-site payment.

  • Hospital Resources and Room Utilization Database Design

The capstone project, “Hospital Resources and Room Utilization Management System” is a system designed to streamline the process of managing hospital resources and room utilization. The said project is critical especially now that we are facing a pandemic, there is a need for efficient management of hospital resources and room management. The management efficiency will prevent a shortage in supplies and overcrowding of patients in the hospitals.

Hospital Resources and Room Utilization Database Design

  • Church Event Management System Database Design

The capstone project entitled “Church Event Management System” is designed to be used by church organizations in creating and managing different church events. The conventional method of managing church events is done manually where members of organizations will face difficulties due to physical barriers and time constraints.

  • CrowdFunding Platform Database Design

Business financing is critical for new business ventures. In this study, the researchers concentrate on designing and developing a business financing platform that is effective for new startups. This capstone project, entitled “Crowdfunding Platform” is a website that allows entrepreneurs to campaign their new business venture to attract investors and crowdfund.

  • Vehicle Franchising and Drivers Offense Software Database Design

The proposed software will be used to electronically process and manage vehicle and franchising and driver’s offenses. The proposed software will eliminate the manual method which involves a lot of paper works and consumes valuable amount of time. The proposed project will serve as a centralized platform was recording and paying for the offenses committed by the drivers will be processed. The system will quicken the process of completing transaction between the enforcers and the drivers. Vehicle franchising and managing driver offenses will be easy, fast and convenient using the system.

  • Student Tracking Performance Database Design

The capstone project entitled “Student Academic Performance Tracking and Monitoring System” allows academic institutions to monitor and gather data about the academic performance of students where decisions are derived to further improve the students learning outcomes. Tracking and monitoring student’s performance serves a vital role in providing information that is used to assist students, teachers, administrators, and policymakers in making decisions that will further improve the academic performance of students.

  • Webinar Course Management System Database Design

The capstone project, entitled “Webinar Course Management System,” is designed to automate managing webinar courses. The project aims to eliminate the current method, which is inefficient and inconvenient for parties involved in the webinar. A software development life cycle (SDLC) technique will be used by the researchers in order to build this project. They will gather a sample size of participating webinar members and facilitators to serve as respondents of the study.

  • Online Birth Certificate Processing System with SMS Notification Database Design

The capstone project, “Online Birth Certificate Processing System with SMS Notification “ is an IT-based solution that aims to automate the process of requesting, verifying, and approving inquiries for original birth records. The system will eliminate the traditional method and transition the birth certificate processing into an easy, convenient, and efficient manner. The researchers will develop the project following the Software Development Life Cycle (SDLC) technique.

  • Food Donation Services Database Design

Information technology plays a significant role in automating the operations of many companies to boost efficiency. One of these is the automation of food donation and distribution management. “Food Donation Services,” the capstone project, is intended to serve as a platform for facilitating transactions between food groups, donors, and recipients. Food banks will be able to respond to various food donations and food assistance requests in a timely and effective manner as a result of the project.

  • COVID Profiling Database Design

The capstone project “City COVID-19 Profiling System with Decision Support” is designed to automate the process of profiling COVID-19 patients. The project will empower local health officers in electronically recording and managing COVID-19 patient information such as symptoms, travel history, and other critical details needed to identify patients. Manual profiling is prone to human mistakes, necessitates a lot of paperwork, and needs too much time and effort from the employees.

  • Evacuation Center Database Design

Calamities can have a significant impact on society. It may result in an enormous number of people being evacuated. The local government unit assigned evacuation centers to provide temporary shelter for people during disasters. Evacuation centers are provided to give temporary shelter for the people during and after a calamity. Evacuation centers can be churches, sports stadium community centers, and much more that are capable to provide emergency shelter.

  • QR Code Fare Payment System Database Design

The capstone project, “QR Code Fare Payment System” is designed to automate the procedure of paying for a fare when riding a vehicle. Passengers will register in the system to receive their own QR code, which they will use to pay for their fares by scanning in the system’s QR code scanning page. The project will enable cashless fare payment.

  • Web Based Psychopathology Diagnosis System Database Design

The capstone project entitled “Web-Based Psychopathology Diagnosis System” is designed for patients and medical staff in the field of psychopathology. The system will be a centralized platform to be used by patients and psychopathologists for consultations. The said project will also keep all the records electronically. Mental health is important. Each individual must give importance to their mental health by paying attention to it and seek medical advice if symptoms of mental disorders and unusual behavior occur.

  • Service Marketplace System Database Design

The capstone project, “Services Marketplace System” is designed to serve as a centralized platform for marketing and inquiring about different services. The system will serve as a platform where different service providers and customers will have an automated transaction. Technology made it easier for people to accomplish daily tasks and activities. In the conventional method, customers avail themselves of services by visiting the shop that offers their desired services personally.

40 List of DBMS Project Topics and Ideas

  • Fish Catch System Database Design

The capstone project, entitled “Fish Catch Monitoring System” will automate the process of recording and monitoring fish catches. The said project is intended to be used by fisherman and fish markets to accurately record fish catches and will also keep the records electronically safe and secure.

  • Complaints Handling Management System Free Template Database Design

The capstone project, “Complaint Handling Management System” is a system designed to help educational institutions to handle and manage complaints electronically. The system will improve the response time of the school’s management in addressing the complaints of the students, parents, staff, and other stakeholders.

  • Senior Citizen Information System Free Template Database Design

The system will replace the manual method of managing information and records of the senior citizen to an electronic one. The system will serve as a repository of the record of the senior citizen within the scope of a specific local government unit. By using the system, paper works will be lessened and human errors in file handling will be avoided. The system is efficient enough to aid in managing and keeping the records of the senior citizens in the different barangay.

  • Online and SMS-Based Salary Notification Database Design

The “Online and SMS Based Salary Notification” is a capstone project intended to be used by companies and employees to automate the process of notifying salary details. The application will work by allowing the designated company encoder to encode details of salary and the employees to log in to his/her account in the application and have access to the details of his/her salary. One of the beauties of being employed is being paid. Employers manage the employee’s salary and are responsible to discuss with the employees the system of the salary and deductions.

  • Maternal Records Management Database Design

The capstone project, “Maternal Records Management System” is a system that automates the process of recording and keeping maternal records. The said project will allow maternity clinics to track and monitor their patients’ records from pregnancy to their baby’s immunization records.

  • Online Complaint Management System Database Design

Online Complaint Management System is a capstone project that is design to serve as a platform to address complaints and resolve disputes. The system provides an online way of resolving problems faced by the public or people within the organization. The system will make complaints easier to coordinate, monitor, track and resolve.

  • Online Donation Database Design

The capstone project ,  “Online Donation Platform for DSWD” is an online platform for giving and asking donations in the Department of Social Welfare and Development (DSWD). The system will be managed by the staffs of the DSWD to verify donors and legible beneficiaries electronically. The system will have an SMS feature to notify the donors and beneficiaries about the status of their request.

  • OJT Timesheet Monitoring System using QR Code Database Design

The capstone project, “OJT Timesheet Monitoring System using QR Code” allows employer to automate timesheet of each trainee for easy monitoring. The system will be used by the on-the-job trainees to serve as their daily time in and out using the QR code generated by the system. The entire system will be managed by the administrator.

Technology is attributed with driving change in a wide range of enterprises and institutions. Because of information technology, the world has altered dramatically. It is difficult to imagine an industry or organization that has not benefited from technology advances. In these businesses, the most common role of IT has been to automate numerous procedures and transactions in order to increase efficiency and improve people’s overall experience and satisfaction. The aforementioned capstone project ideas will be useful in a range of sectors. It will aid in enhancing operational efficiency as well as the services provided to the project’s users.

You may visit our  Facebook page for more information, inquiries, and comments. Please subscribe also to our YouTube Channel to receive  free capstone projects resources and computer programming tutorials.

Hire our team to do the project.

Related Topics and Articles:

  • List of Completed Capstone Projects with Source code
  • 27 Free Capstone Project Ideas and Tutorials
  • 16 Lists of Free Capstone Project Ideas in Flutter
  • 39 Capstone Project Ideas for IT Related Courses
  • 50+ Free Download Web Based System Template in Bootstrap
  • COVID-19 Capstone and Research Free Project Ideas 2022
  • Capstone Project Ideas for IT and IS January 2022
  • Capstone Project Ideas for IT and IS December 2021
  • IT and IS Capstone Project Free Resources November 2021
  • List of 45 IT Capstone Project on Crime and Disaster Management

Post navigation

  • QR Code Generator in PHP Free Source code and Tutorial

Similar Articles

Backup mysql database on wamp, mysql tutorial – creating a table in mysql.

Taxi Mobile an Android Based Taxi Booking Application

Taxi Mobile an Android Based Taxi Booking Application

Logo for Pressbooks@MSL

Chapter 9: The Research Process

9.3 Basic Guidelines for Research in Academic Databases

Emilie Zickel

Many of your professors will expect you to use academic research databases for research papers in college. Getting used to doing research in an academic database can be challenging, especially if you have only used Google for research. Becoming familiar with the way that research databases work can take some time. However, with some understanding of what academic research databases can do for you, and with some practice and tinkering around, you will soon be more comfortable doing your research in these databases instead of Google.

The guidelines offered in the videos below offer basic but important information about using research databases effectively. While the content on the rest of this page applies most specifically to Academic Search Complete (also called EBSCO), the tips are relevant to any research database.

How Can You Use an Academic Research Database Effectively?

  • Avoid typing your whole research question into the search field. Use only keywords, in various combinations
  • Use several keywords at once, and be willing to change each word for a synonym if you hit a dead end with one set of words
  • Use “AND” or “OR” to retrieve more results or to limit your results
  • Use the database’s own Subject Terms to help you to refine your searches within that database

The video below explains what doing all of those things means in a practical sense. 

“Tracking Down Articles” by Research Therapists

What is Academic Search Complete?

Academic Search Complete is one of the more user-friendly databases for conducting college research. It is a great “starter” database for several reasons. In  Academic Search Complete, you can find popular articles from some of the more credible newspapers and magazines. You can also locate scholarly articles from a variety of academic disciplines. Academic Search Complete provides a wide array of information on a range of topics, and chances are that you will find something useful for your project there.

When you realize how many filters you can apply to your search query so that you only get certain types of information, you will see how valuable this database (or database researching in general) can be.

The video below offers a quick overview of how you can use Academic Search Complete to

  • Limit your search results to only get peer reviewed (scholarly) articles
  • Limit your search results to get articles that are accessible via download
  • Refine your searches so that you get the information most relevant to your research project
  • Refine your search to specific dates so that only articles from a certain time period are found
  • Access articles that you find
  • Locate article abstracts
  • Find subject terms and understand how they can be useful to your research strategy

“Academic Search Complete Database in 3 Minutes” by Seminole State Library is licensed under CC BY

A Note about Google Scholar vs Academic Search Complete

Many students report using and liking Google Scholar. If Google Scholar works for you – and it certainly can work well – then continue to use it along with Academic Search Complete. What may happen, however, is that while you can find article titles via Google Scholar searches, you may not get access to the full article, particularly if you have not linked your Google Scholar account to your university library.

Academic Search Complete, and the many, many other academic research databases that can be accessed from the university library “ Research Databases ” page, will give you access to most articles. If you find a title via Google Scholar that you cannot access, try looking for it in Academic Search Complete or another database.

A Guide to Rhetoric, Genre, and Success in First-Year Writing by Emilie Zickel is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Feedback/Errata

Comments are closed.

PrepScholar

Choose Your Test

Sat / act prep online guides and tips, 113 great research paper topics.

author image

General Education

feature_pencilpaper

One of the hardest parts of writing a research paper can be just finding a good topic to write about. Fortunately we've done the hard work for you and have compiled a list of 113 interesting research paper topics. They've been organized into ten categories and cover a wide range of subjects so you can easily find the best topic for you.

In addition to the list of good research topics, we've included advice on what makes a good research paper topic and how you can use your topic to start writing a great paper.

What Makes a Good Research Paper Topic?

Not all research paper topics are created equal, and you want to make sure you choose a great topic before you start writing. Below are the three most important factors to consider to make sure you choose the best research paper topics.

#1: It's Something You're Interested In

A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject. Even if a certain research paper topic is getting a lot of buzz right now or other people seem interested in writing about it, don't feel tempted to make it your topic unless you genuinely have some sort of interest in it as well.

#2: There's Enough Information to Write a Paper

Even if you come up with the absolute best research paper topic and you're so excited to write about it, you won't be able to produce a good paper if there isn't enough research about the topic. This can happen for very specific or specialized topics, as well as topics that are too new to have enough research done on them at the moment. Easy research paper topics will always be topics with enough information to write a full-length paper.

Trying to write a research paper on a topic that doesn't have much research on it is incredibly hard, so before you decide on a topic, do a bit of preliminary searching and make sure you'll have all the information you need to write your paper.

#3: It Fits Your Teacher's Guidelines

Don't get so carried away looking at lists of research paper topics that you forget any requirements or restrictions your teacher may have put on research topic ideas. If you're writing a research paper on a health-related topic, deciding to write about the impact of rap on the music scene probably won't be allowed, but there may be some sort of leeway. For example, if you're really interested in current events but your teacher wants you to write a research paper on a history topic, you may be able to choose a topic that fits both categories, like exploring the relationship between the US and North Korea. No matter what, always get your research paper topic approved by your teacher first before you begin writing.

113 Good Research Paper Topics

Below are 113 good research topics to help you get you started on your paper. We've organized them into ten categories to make it easier to find the type of research paper topics you're looking for.

Arts/Culture

  • Discuss the main differences in art from the Italian Renaissance and the Northern Renaissance .
  • Analyze the impact a famous artist had on the world.
  • How is sexism portrayed in different types of media (music, film, video games, etc.)? Has the amount/type of sexism changed over the years?
  • How has the music of slaves brought over from Africa shaped modern American music?
  • How has rap music evolved in the past decade?
  • How has the portrayal of minorities in the media changed?

music-277279_640

Current Events

  • What have been the impacts of China's one child policy?
  • How have the goals of feminists changed over the decades?
  • How has the Trump presidency changed international relations?
  • Analyze the history of the relationship between the United States and North Korea.
  • What factors contributed to the current decline in the rate of unemployment?
  • What have been the impacts of states which have increased their minimum wage?
  • How do US immigration laws compare to immigration laws of other countries?
  • How have the US's immigration laws changed in the past few years/decades?
  • How has the Black Lives Matter movement affected discussions and view about racism in the US?
  • What impact has the Affordable Care Act had on healthcare in the US?
  • What factors contributed to the UK deciding to leave the EU (Brexit)?
  • What factors contributed to China becoming an economic power?
  • Discuss the history of Bitcoin or other cryptocurrencies  (some of which tokenize the S&P 500 Index on the blockchain) .
  • Do students in schools that eliminate grades do better in college and their careers?
  • Do students from wealthier backgrounds score higher on standardized tests?
  • Do students who receive free meals at school get higher grades compared to when they weren't receiving a free meal?
  • Do students who attend charter schools score higher on standardized tests than students in public schools?
  • Do students learn better in same-sex classrooms?
  • How does giving each student access to an iPad or laptop affect their studies?
  • What are the benefits and drawbacks of the Montessori Method ?
  • Do children who attend preschool do better in school later on?
  • What was the impact of the No Child Left Behind act?
  • How does the US education system compare to education systems in other countries?
  • What impact does mandatory physical education classes have on students' health?
  • Which methods are most effective at reducing bullying in schools?
  • Do homeschoolers who attend college do as well as students who attended traditional schools?
  • Does offering tenure increase or decrease quality of teaching?
  • How does college debt affect future life choices of students?
  • Should graduate students be able to form unions?

body_highschoolsc

  • What are different ways to lower gun-related deaths in the US?
  • How and why have divorce rates changed over time?
  • Is affirmative action still necessary in education and/or the workplace?
  • Should physician-assisted suicide be legal?
  • How has stem cell research impacted the medical field?
  • How can human trafficking be reduced in the United States/world?
  • Should people be able to donate organs in exchange for money?
  • Which types of juvenile punishment have proven most effective at preventing future crimes?
  • Has the increase in US airport security made passengers safer?
  • Analyze the immigration policies of certain countries and how they are similar and different from one another.
  • Several states have legalized recreational marijuana. What positive and negative impacts have they experienced as a result?
  • Do tariffs increase the number of domestic jobs?
  • Which prison reforms have proven most effective?
  • Should governments be able to censor certain information on the internet?
  • Which methods/programs have been most effective at reducing teen pregnancy?
  • What are the benefits and drawbacks of the Keto diet?
  • How effective are different exercise regimes for losing weight and maintaining weight loss?
  • How do the healthcare plans of various countries differ from each other?
  • What are the most effective ways to treat depression ?
  • What are the pros and cons of genetically modified foods?
  • Which methods are most effective for improving memory?
  • What can be done to lower healthcare costs in the US?
  • What factors contributed to the current opioid crisis?
  • Analyze the history and impact of the HIV/AIDS epidemic .
  • Are low-carbohydrate or low-fat diets more effective for weight loss?
  • How much exercise should the average adult be getting each week?
  • Which methods are most effective to get parents to vaccinate their children?
  • What are the pros and cons of clean needle programs?
  • How does stress affect the body?
  • Discuss the history of the conflict between Israel and the Palestinians.
  • What were the causes and effects of the Salem Witch Trials?
  • Who was responsible for the Iran-Contra situation?
  • How has New Orleans and the government's response to natural disasters changed since Hurricane Katrina?
  • What events led to the fall of the Roman Empire?
  • What were the impacts of British rule in India ?
  • Was the atomic bombing of Hiroshima and Nagasaki necessary?
  • What were the successes and failures of the women's suffrage movement in the United States?
  • What were the causes of the Civil War?
  • How did Abraham Lincoln's assassination impact the country and reconstruction after the Civil War?
  • Which factors contributed to the colonies winning the American Revolution?
  • What caused Hitler's rise to power?
  • Discuss how a specific invention impacted history.
  • What led to Cleopatra's fall as ruler of Egypt?
  • How has Japan changed and evolved over the centuries?
  • What were the causes of the Rwandan genocide ?

main_lincoln

  • Why did Martin Luther decide to split with the Catholic Church?
  • Analyze the history and impact of a well-known cult (Jonestown, Manson family, etc.)
  • How did the sexual abuse scandal impact how people view the Catholic Church?
  • How has the Catholic church's power changed over the past decades/centuries?
  • What are the causes behind the rise in atheism/ agnosticism in the United States?
  • What were the influences in Siddhartha's life resulted in him becoming the Buddha?
  • How has media portrayal of Islam/Muslims changed since September 11th?

Science/Environment

  • How has the earth's climate changed in the past few decades?
  • How has the use and elimination of DDT affected bird populations in the US?
  • Analyze how the number and severity of natural disasters have increased in the past few decades.
  • Analyze deforestation rates in a certain area or globally over a period of time.
  • How have past oil spills changed regulations and cleanup methods?
  • How has the Flint water crisis changed water regulation safety?
  • What are the pros and cons of fracking?
  • What impact has the Paris Climate Agreement had so far?
  • What have NASA's biggest successes and failures been?
  • How can we improve access to clean water around the world?
  • Does ecotourism actually have a positive impact on the environment?
  • Should the US rely on nuclear energy more?
  • What can be done to save amphibian species currently at risk of extinction?
  • What impact has climate change had on coral reefs?
  • How are black holes created?
  • Are teens who spend more time on social media more likely to suffer anxiety and/or depression?
  • How will the loss of net neutrality affect internet users?
  • Analyze the history and progress of self-driving vehicles.
  • How has the use of drones changed surveillance and warfare methods?
  • Has social media made people more or less connected?
  • What progress has currently been made with artificial intelligence ?
  • Do smartphones increase or decrease workplace productivity?
  • What are the most effective ways to use technology in the classroom?
  • How is Google search affecting our intelligence?
  • When is the best age for a child to begin owning a smartphone?
  • Has frequent texting reduced teen literacy rates?

body_iphone2

How to Write a Great Research Paper

Even great research paper topics won't give you a great research paper if you don't hone your topic before and during the writing process. Follow these three tips to turn good research paper topics into great papers.

#1: Figure Out Your Thesis Early

Before you start writing a single word of your paper, you first need to know what your thesis will be. Your thesis is a statement that explains what you intend to prove/show in your paper. Every sentence in your research paper will relate back to your thesis, so you don't want to start writing without it!

As some examples, if you're writing a research paper on if students learn better in same-sex classrooms, your thesis might be "Research has shown that elementary-age students in same-sex classrooms score higher on standardized tests and report feeling more comfortable in the classroom."

If you're writing a paper on the causes of the Civil War, your thesis might be "While the dispute between the North and South over slavery is the most well-known cause of the Civil War, other key causes include differences in the economies of the North and South, states' rights, and territorial expansion."

#2: Back Every Statement Up With Research

Remember, this is a research paper you're writing, so you'll need to use lots of research to make your points. Every statement you give must be backed up with research, properly cited the way your teacher requested. You're allowed to include opinions of your own, but they must also be supported by the research you give.

#3: Do Your Research Before You Begin Writing

You don't want to start writing your research paper and then learn that there isn't enough research to back up the points you're making, or, even worse, that the research contradicts the points you're trying to make!

Get most of your research on your good research topics done before you begin writing. Then use the research you've collected to create a rough outline of what your paper will cover and the key points you're going to make. This will help keep your paper clear and organized, and it'll ensure you have enough research to produce a strong paper.

What's Next?

Are you also learning about dynamic equilibrium in your science class? We break this sometimes tricky concept down so it's easy to understand in our complete guide to dynamic equilibrium .

Thinking about becoming a nurse practitioner? Nurse practitioners have one of the fastest growing careers in the country, and we have all the information you need to know about what to expect from nurse practitioner school .

Want to know the fastest and easiest ways to convert between Fahrenheit and Celsius? We've got you covered! Check out our guide to the best ways to convert Celsius to Fahrenheit (or vice versa).

Need more help with this topic? Check out Tutorbase!

Our vetted tutor database includes a range of experienced educators who can help you polish an essay for English or explain how derivatives work for Calculus. You can use dozens of filters and search criteria to find the perfect person for your needs.

Connect With a Tutor Now

These recommendations are based solely on our knowledge and experience. If you purchase an item through one of our links, PrepScholar may receive a commission.

author image

Christine graduated from Michigan State University with degrees in Environmental Biology and Geography and received her Master's from Duke University. In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist. She has taught English and biology in several countries.

Student and Parent Forum

Our new student and parent forum, at ExpertHub.PrepScholar.com , allow you to interact with your peers and the PrepScholar staff. See how other students and parents are navigating high school, college, and the college admissions process. Ask questions; get answers.

Join the Conversation

Ask a Question Below

Have any questions about this article or other topics? Ask below and we'll reply!

Improve With Our Famous Guides

  • For All Students

The 5 Strategies You Must Be Using to Improve 160+ SAT Points

How to Get a Perfect 1600, by a Perfect Scorer

Series: How to Get 800 on Each SAT Section:

Score 800 on SAT Math

Score 800 on SAT Reading

Score 800 on SAT Writing

Series: How to Get to 600 on Each SAT Section:

Score 600 on SAT Math

Score 600 on SAT Reading

Score 600 on SAT Writing

Free Complete Official SAT Practice Tests

What SAT Target Score Should You Be Aiming For?

15 Strategies to Improve Your SAT Essay

The 5 Strategies You Must Be Using to Improve 4+ ACT Points

How to Get a Perfect 36 ACT, by a Perfect Scorer

Series: How to Get 36 on Each ACT Section:

36 on ACT English

36 on ACT Math

36 on ACT Reading

36 on ACT Science

Series: How to Get to 24 on Each ACT Section:

24 on ACT English

24 on ACT Math

24 on ACT Reading

24 on ACT Science

What ACT target score should you be aiming for?

ACT Vocabulary You Must Know

ACT Writing: 15 Tips to Raise Your Essay Score

How to Get Into Harvard and the Ivy League

How to Get a Perfect 4.0 GPA

How to Write an Amazing College Essay

What Exactly Are Colleges Looking For?

Is the ACT easier than the SAT? A Comprehensive Guide

Should you retake your SAT or ACT?

When should you take the SAT or ACT?

Stay Informed

database topics for research paper

Get the latest articles and test prep tips!

Looking for Graduate School Test Prep?

Check out our top-rated graduate blogs here:

GRE Online Prep Blog

GMAT Online Prep Blog

TOEFL Online Prep Blog

Holly R. "I am absolutely overjoyed and cannot thank you enough for helping me!”

Reference management. Clean and simple.

The top list of academic research databases

best research databases

2. Web of Science

5. ieee xplore, 6. sciencedirect, 7. directory of open access journals (doaj), frequently asked questions about academic research databases, related articles.

Whether you are writing a thesis , dissertation, or research paper it is a key task to survey prior literature and research findings. More likely than not, you will be looking for trusted resources, most likely peer-reviewed research articles.

Academic research databases make it easy to locate the literature you are looking for. We have compiled the top list of trusted academic resources to help you get started with your research:

Scopus is one of the two big commercial, bibliographic databases that cover scholarly literature from almost any discipline. Beside searching for research articles, Scopus also provides academic journal rankings, author profiles, and an h-index calculator .

  • Coverage: 90.6 million core records
  • References: N/A
  • Discipline: Multidisciplinary
  • Access options: Limited free preview, full access by institutional subscription only
  • Provider: Elsevier

Search interface of Scopus

Web of Science also known as Web of Knowledge is the second big bibliographic database. Usually, academic institutions provide either access to Web of Science or Scopus on their campus network for free.

  • Coverage: approx. 100 million items
  • References: 1.4 billion
  • Access options: institutional subscription only
  • Provider: Clarivate (formerly Thomson Reuters)

Web of Science landing page

PubMed is the number one resource for anyone looking for literature in medicine or biological sciences. PubMed stores abstracts and bibliographic details of more than 30 million papers and provides full text links to the publisher sites or links to the free PDF on PubMed Central (PMC) .

  • Coverage: approx. 35 million items
  • Discipline: Medicine and Biological Sciences
  • Access options: free
  • Provider: NIH

Search interface of PubMed

For education sciences, ERIC is the number one destination. ERIC stands for Education Resources Information Center, and is a database that specifically hosts education-related literature.

  • Coverage: approx. 1.6 million items
  • Discipline: Education
  • Provider: U.S. Department of Education

Search interface of ERIC academic database

IEEE Xplore is the leading academic database in the field of engineering and computer science. It's not only journal articles, but also conference papers, standards and books that can be search for.

  • Coverage: approx. 6 million items
  • Discipline: Engineering
  • Provider: IEEE (Institute of Electrical and Electronics Engineers)

Search interface of IEEE Xplore

ScienceDirect is the gateway to the millions of academic articles published by Elsevier, 1.4 million of which are open access. Journals and books can be searched via a single interface.

  • Coverage: approx. 19.5 million items

Search interface of ScienceDirect

The DOAJ is an open-access academic database that can be accessed and searched for free.

  • Coverage: over 8 million records
  • Provider: DOAJ

Search interface of DOAJ database

JSTOR is another great resource to find research papers. Any article published before 1924 in the United States is available for free and JSTOR also offers scholarships for independent researchers.

  • Coverage: more than 12 million items
  • Provider: ITHAKA

Search interface of JSTOR

PubMed is the number one resource for anyone looking for literature in medicine or biological sciences. PubMed stores abstracts and bibliographic details of more than 30 million papers and provides full text links to the publisher sites or links to the free PDF on PubMed Central (PMC)

database topics for research paper

Robert L. Bogomolny Library

What's happening at the library and items of interest to the UB community

Using Databases to Find a Research Paper Topic

It’s almost mid-semester and you still haven’t picked a topic for your research paper. No worries! The RLB Library has a few tips and tools that can help you find a topic.

Your topic can be on something you’d like to learn more about, or about an issue that is relevant today. It helps to choose a topic that is broad enough to allow research on several aspects of an issue, but not too broad that you find yourself going off on tangents. The topic should be interesting to you and perhaps meaningful in some way to today’s society. In addition, you should be able to support your ideas with research from appropriate sources.

A good way to look for topics is to  read lots of stuff  in the general subject areas that interest you. The RLB Library has tools for you to find reading material online. These tools include:

1. Research Starters

Go to the Library’s homepage library.ubalt.edu and type in some keywords in the gray box under the “library search” tab. For example, the keyword “inflation” will result in a “Research Starter” display at the top of the search results. Research Starters are a good way to get an overview of a topic. Clicking on “more” will take you to a detailed article on the topic.

2. Credo Reference

This database is another great place to read background information on many topics. You can access Credo Reference by going to the library homepage and clicking on “Databases” beneath the search box. When you get to the list of A-Z Databases, click on the letter C and scroll down for “Credo Reference.”

In Credo Reference, you can browse by subjects. On the right side there are useful “Research Quick Tips.” You can also use “mind maps” to explore related concepts.

3. Academic OneFile (Gale)

This database includes a Topic Finder. When you input a search term, a diagram appears with “tiles” that you can click on to narrow your search and pull up relevant articles. You can access Academic OneFile through the A-Z Databases list under “A.”

4. Opposing Viewpoints (Gale in Context)

If you are interested in contemporary issues, the database Opposing Viewpoints is a good starting point to read about current social issues, with articles exploring contrasting viewpoints. This database can also be accessed from the A-Z Databases list under “O.”

In summary, finding a topic for your research paper or project can be made easier by reading background material. The four resources mentioned above can help you find those background articles that point you to an interesting and compelling topic. But don’t procrastinate! You need to set aside time to read.   Ask a Librarian if you want more information on the research process or on how to pick a good topic.

**For a really good tutorial demonstrating how to find a topic, check out this video from NC State University Libraries.**

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

logo

  • SAT BootCamp
  • SAT MasterClass
  • SAT Private Tutoring
  • SAT Proctored Practice Test
  • ACT Private Tutoring
  • Academic Subjects
  • College Essay Workshop
  • Academic Writing Workshop
  • AP English FRQ BootCamp
  • 1:1 College Essay Help
  • Online Instruction
  • Free Resources

500 Good Research Paper Topics

Bonus Material: Essential essay checklist

Writing a research paper for a class and not sure how to start?

One of the most important steps to creating a great paper is finding a good topic! 

Here’s a hand-drafted list from a Princeton grad who has helped professors at Harvard and Yale edit their papers for publication and taught college writing at the University of Notre Dame and .

What’s more, we give you some foolproof formulas for creating your own paper topic to fit the requirements of your class.

Using these simple formulas, we’ve helped hundreds of students turn a B- paper topic into an A+ paper topic.

Keep reading for our list of 500 vetted research paper topics and our magic formulas for creating your own topic!

Of course, if you want help learning to write research papers tailored to your individual needs, check out our one-on-one writing coaching or academic writing workshop . Set up a free consultation to see how we can help you learn to write A+ papers!

Jump to paper topics in:

European & Mediterranean History

African history, asian history, history of the pre-columbian americas.

  • Latin American History

History of Science

Politics & public policy, education & education policy, political theory, science policy.

  • Health Sciences & Psychology

Download the essential essay checklist

What is a research paper?

In order to write a good research paper, it’s important to know what it is! 

In general, we can divide academic writing into three broad categories:

  • Analytical: analyze the tools an author uses to make their point
  • Research: delve deeply into a research topic and share your findings
  • Persuasive : argue a specific and nuanced position backed by evidence

What’s the difference between an analytical paper and a research paper? For an analytical paper, it’s okay to just use one or two sources (a book, poem, work of art, piece of music, etc.) and examine them in detail. For a research paper, however, the expectation is that you do, well . . . research .

student writing research paper

The depth of research that you’re expected to do will depend on your age and the type of class you’re taking.

In elementary or middle school, a “research paper” might mean finding information from a few general books or encyclopedias in your school library. 

In high school, your teachers might expect you to start using information from academic articles and more specific books. You might use encyclopedias and general works as a starting point, but you’ll be expected to go beyond them and do more work to synthesize information from different perspectives or different types of sources. You may also be expected to do “primary research,” where you study the source material yourself, instead of synthesizing what other people have written about the source material.

In college, you’ll be required to use academic journals and scholarly books, and your professors will now expect that you be more critical of these secondary sources, noticing the methodology and perspectives of whatever articles and books you’re using. 

In more advanced college courses, you’ll be expected to do more exhaustive surveys of the existing literature on a topic. You’ll need to conduct primary research that makes an original contribution to the field—the kind that could be published in a journal article itself.

For a walkthrough of the 12 essential steps to writing a good paper, check out our step-by-step guide .

student writing research paper

Working on a research paper? Grab our free checklist to make sure your essay has everything it needs to earn an A grade.

Get the essential essay checklist

What makes a good research paper topic?

One of the most important features of a research paper topic is that it has a clear, narrow focus. 

For example, your teacher may assign you to write a research paper related to the US Revolutionary War. Does that mean that your topic should be “the US Revolutionary War”? 

Definitely not! There’s no way to craft a good paper with in-depth research with such a broad topic. (Unless you’re in elementary or middle school, in which case it’s okay to have a more general topic for your research paper.)

Instead, you need to find a more specific topic within this broader one. There are endless ways that you can make this narrower! Some ideas generated from this one broader topic might be:

  • Causes of the US Revolutionary War
  • Changes in military strategy during the Revolutionary War
  • The experiences of Loyalists to England who remained in the American colonies during the Revolutionary War
  • How the Revolutionary War was pivotal for the career of Alexander Hamilton
  • The role of alliances with France during the US Revolutionary War
  • The experiences of people of color during the Revolutionary War
  • How George Washington’s previous military career paved the way for his leadership in the Revolutionary War
  • The main types of weaponry during the Revolutionary War
  • Changes in clothing and fashion over the courses of the Revolutionary War
  • How Valley Forge was a key moment in the Revolutionary War
  • How women contributed to the Revolutionary War
  • What happened in Amherst, Massachusetts during the Revolutionary War
  • Field medicine during the Revolutionary War
  • How the Battle of Saratoga was a turning point in the Revolutionary War
  • How different opinions about the Revolutionary War were reflected in poetry written during that time
  • Debates over abolition during the Revolutionary War
  • The importance of supply chains during the Revolutionary War
  • Reactions to the US Revolutionary war in Europe
  • How the US Revolutionary war impacted political theory in England and France
  • Similarities and differences between the US Revolutionary War and the French Revolution
  • Famous paintings inspired by the US Revolutionary War
  • Different ways that the US Revolutionary War has been depicted in modern contemporary culture
  • The appropriation of the “Boston Tea Party” by US politicians in the 2010s

This list could go on forever!

good research paper topics about the US Revolution

In fact, any of these topics could become even more specific. For example, check out the evolution of this topic:

  • Economic causes of the Revolutionary war
  • The way that tax policies helped lead to the Revolutionary War
  • How tax laws enacted 1763–1775 helped lead to the Revolutionary War
  • How the tax-free status of the British East India Company helped lead to the Revolutionary War
  • How the 1773 tax-free status of the British East India Company helped lead to the Revolutionary War, as reflected in letters written 1767–1775
  • How the 1773 tax-free status of the British East India Company helped lead to the Revolutionary War, as reflected in letters written by members of the Sons of Liberty 1767–1775

As you advance in your educational career, you’ll need to make your topic more and more specific. Steps 1–3 of this topic might be okay in high school, but for a college research paper steps 4–7 would be more appropriate!

As you craft your research paper topic, you should also keep in mind the availability of research materials on your subject. There are millions of topics that would make interesting research papers, but for which you yourself might not be able to investigate with the primary and secondary sources to which you have access.

Access to research materials might look like:

  • To the best of our knowledge, the sources exist somewhere
  • The source isn’t behind a paywall (or you or your school can pay for it)
  • Your school or local library has a copy of the source
  • Your school or local library can order a copy of the source for you
  • The source is in a language that you speak
  • The source has been published already (there’s tons of amazing research that hasn’t been published yet, a frustrating problem!)
  • You can access the archive, museum, or database where the primary source is held—this might mean online access or travel! To access a source in an archive or museum you’ll often need permission, which often requires a letter of support from your school.

If you’re not sure about access to source materials, talk to a librarian! They’re professionals for this question.

Finally, pick a research topic that interests you! Given that there are unlimited research topics in the world and many ways to adapt a broad topic, there should absolutely be a way to modify a research topic to fit your interests.

student writing research paper

Want help learning to write an amazing research paper? Work one-on-one with an experienced Ivy-League tutor to improve your writing skills or sign up for our bestselling academic writing workshop .

Insider tips to generate your own research paper topic

Use these formulas to generate your own research paper topics:

  • How did X change over a period of time (year, decade, century)?
  • What is the impact (or consequences) of X?
  • What led to X?
  • What is the role of X in Y?
  • How did X influence Y?
  • How did X become Y?
  • How was X different from Y?
  • How is X an example of Y?
  • How did X affect Y?
  • What were some reactions to X?
  • What are the most effective policies to produce X result?
  • What are some risks of X?
  • How is our current understanding of X incorrect? (advanced)
  • What happens if we look at X through the lens of Y theory or perspective? (advanced)

A good research paper topic often starts with the question words—why, how, what, who, and where. Remember to make it as specific as possible!

student writing research paper

Good research paper topics

These research paper topics have been vetted by a Princeton grad and academic book editor!

  • How did European rivalries (British vs French) impact North American history?
  • What was the role of British and French alliances with indigneous tribes during the Seven Years’ War?
  • Reactions to the 1754 Albany Congress among North American intellectual figures
  • How the Albany Plan served as a model for future attempts at union among the North American colonies
  • How did different religious identities (Calvinist, Catholic, etc.) play a role in the aftermath of the Seven Years’ War?
  • What were the consequences of the 1763 Treaty of Paris?
  • How did the Seven Years’ War impact British debt and colonial economics?
  • What were some causes of the US Revolutionary War?
  • How did military strategy change during the Revolutionary War?
  • What were the experiences of Loyalists to England who remained in the American colonies during the Revolutionary War?
  • How was the Revolutionary War pivotal for the career of Alexander Hamilton?
  • What was the role of alliances with France during the US Revolutionary War?
  • What were the experiences of people of color during the Revolutionary War?
  • How did George Washington’s previous military career pave the way for his leadership in the Revolutionary War?
  • What were the main types of weaponry during the Revolutionary War? How did that affect the options for military strategies?
  • How did clothing and fashion change over the courses of the Revolutionary War?
  • How was Valley Forge a key moment in the Revolutionary War?
  • How did women contribute to the Revolutionary War?
  • What happened in Amherst, Massachusetts (or any other specific location) during the Revolutionary War?
  • What was field medicine like during the Revolutionary War? 
  • How was the Battle of Saratoga a turning point in the Revolutionary War?
  • How were different opinions about the Revolutionary War reflected in poetry written during that time?
  • What were the debates over abolition during the Revolutionary War?
  • What was the role of supply chains during the Revolutionary War?
  • What were reactions to the US Revolutionary war like in Europe? What does that tell us about politics in England, France, the Netherlands, etc?
  • How did the US Revolutionary war impact political theory in England and France?
  • What are similarities and differences between the US Revolutionary War and the French Revolution?
  • What are some famous paintings inspired by the US Revolutionary War? What do differences between these paintings tell us about how the artists who created them saw the war?
  • What are some different ways that the US Revolutionary War has been depicted in modern contemporary culture? What does that tell us?
  • How was the story of the “Boston Tea Party” appropriated by US politicians in the 2010s, and why?
  • What was the difference between the Federalists and the Jeffersonians?
  • How did the 1797 XYZ Affair lead to the Quasi-War with France?
  • How were loans from European countries and companies (France, Spain, Dutch bankers) key to the early US?
  • What were reactions to the Constitutional Convention of 1787?
  • Why did the US remain neutral during the French Revolution?
  • How did the Alien and Sedition acts contribute to the election of Thomas Jefferson as president?
  • What was the US’s reaction to the Haitian revolution? Why did the US not recognize Haitian independence until 1862?
  • What were the reactions to John Jay’s Treaty of 1794?
  • How have the remarks made by George Washington in his Farewell Address inspired isolationist policies?
  • How did interpretations of the Monroe Doctrine change over the decades since its creation? 
  • How did the Roosevelt Corollary and Lodge Corollary change and expand the Monroe Doctrine?
  • How did the presence of US companies like the United Fruit Company affect US military interventions in Latin America? 
  • How was the Monroe Doctrine invoked in the Cuban Missile Crisis of 1962? 
  • How was US culture shaped by the Cold War?
  • How did ecology play a role in the rise of Ancient Egypt?
  • How did water management technologies impact Ancient Egypt?
  • How did bureaucracies function in Ancient Egypt?
  • How did Egyptian art influence Ancient Greek art?
  • Who could be a citizen in Athens in the 5th century BCE? What does this tell us about classical Athenian society?
  • What was the impact of the Peloponnesian War?
  • What was the impact of Alexander the Great’s attempt to create an empire?
  • How does the way that Alexander the Great is represented in art demonstrate conceptions about the relationship between the human and the divine?
  • Was there a conception of race in the ancient world? How were these ideas different from our own modern conceptions of race?
  • What was the role of debt slavery in the Roman republic? How were these policies ended, and what is the significance of the end of debt slavery? What kinds of slavery remained?
  • To what degree does the movie Gladiator accurately the Roman Empire in 176–192 CE?
  • What was the role of slavery in managing the large latifundia ?
  • How and why did the emperor Constantine I adopt Christianity?
  • How did patterns of urbanism in the latter Roman empire change? What does this tell us about challenges being faced at that time?
  • What do reactions to the Byzantine empress Theodora tell us about ideas of gender in 6th-century Byzantium?
  • How did scientific advancements in Islamic Spain influence the rest of Europe?
  • What was the relationship between Muslim, Christian, and Jewish populations in Islamic Spain? How does this compare to the experience of Muslim and Jewish populations in Christian Spain?
  • How did medieval troubadour poetry represent a new idea of romantic relationships?
  • What are similarities and differences between medieval troubadour poetry and lyric poetry in Ancient Greece? 
  • What do letters between women and popes tell us about gender, power, and religion in medieval Europe?
  • In what ways was Hildegard of Bingen groundbreaking for her time?
  • Who produced beer in medieval England, and what does this tell us about society?
  • How did the adoption of hops affect the production and distribution of beer?
  • How did beer production allow some women a way to be financially independent?
  • How was clothing used to mark religious and cultural identities in 15th- and 16th-century Spain?
  • How did print culture change relationships and courting in Georgian England?
  • How did churches function as social gathering spaces in Georgian England?
  • To what degree is Netflix’s Bridgerton series historically accurate?
  • How did ideas of love change in the 18th century? How did philosophy play a role in this?
  • When were Valentine cards first commercially available? What does that show us about cultural ideas of love and courtship?
  • What were the consequences of the desertification of the Sahara?
  • How did trade links on the Red Sea influence Nubian culture?
  • How did Carthage build power in Northern Africa around 600–500 BCE?
  • What was the impact of the Mercenary War (241–238 BCE) in Carthage?
  • How did the Roman province of Africa play a key role in financing the Roman Empire?
  • What were the consequences of the Donatist division in the 300s in Northern Africa?
  • What was the impact of the large-scale movement of Bedouins from the Arabian peninsula into the Maghreb?
  • How was Mande society organized in the Mali Empire? 
  • What was the role of the book trade in Timbuktu? What does this tell us about culture and learning in the Mali Empire?
  • How did Aksum use trade to build wealth and power? 
  • What do Nok terracotta sculptures tell us about Nok culture?
  • How did the Luba Empire create a centralized political system? How did the idea of spiritual kins ( balopwe ) play a role in this system?
  • How did tax collection work in the Lunda empire?
  • What does it mean to say that the Ajuran Empire was a hydraulic empire? How did control over water resources allow the Ajuran Empire to build and consolidate power?
  • What is the significance of diplomatic ties between the Somai Ajuran Empire and Ming dynasty China? 
  • How did the tribute system in the Kingdom of Kongo help to stimulate interregional trade?
  • What was the impact of the introduction of maize and cassava to the Kingdom of Kongo?
  • How did women wield influence in the Kingdom of Benin?
  • How did the Industrial Revolution in Europe help lead to the Scramble for Africa 1878–1898?
  • What were the consequences of the Second Boer War?
  • What happened in the Year of Africa (1960)?
  • How did the Han dynasty consolidate power in frontier regions? 
  • How and why did the Han dynasty nationalize the private salt and iron industries in 117 BCE?
  • What are the earliest records of papermaking, and what is the significance of this invention?
  • What was the role of Daoist religious societies in rebellions at the end of the Han dynasty (Yellow Turban Rebellion, Five Pecks of Rice Rebellion)?
  • What do tomb paintings tell us about ancient Chinese society?
  • What was the impact of the Sui dynasty’s standardization and re-unification of the coinage?
  • What was the role of standardized testing in Sui dynasty and Tang dynasty China?
  • Why is the Tang dynasty often regarded as a golden age of cosmopolitan culture in Chinese history?
  • What was the role of slavery in imperial China? 
  • How did the rise of jiedushi (regional military governments) undermine the civil-service system? What were the consequences of this?
  • How did Tang dynasty China exert power over Japan and Korea?
  • What was the Three Departments and Six Ministries system in imperial China and how did it work?
  • What does the appearance of Inca, Maya, and Aztec goods in North America (Utah, Canada) and the appearance of goods from the Great Lakes region in Maya and Aztec ruins tell us about trade in the Pre-Columbian Americas?
  • How did celebration of maize play a central role in Mesoamerican cultures?
  • How did the Aztec empire use relationships with client city-states to establish power? How did the Aztec empire use taxation to exert power?
  • How did the luxury good trade impact Aztec political power? 
  • How did the building of roads play a key role in the Aztec empire?
  • How and why has archaeology played a pivotal role in expanding our understanding of the pre-Columbian Americas?
  • What are some common misconceptions about the Americas in the year 1491? Why do these misconceptions exist?

Latin American History (post-1492)

  • How and why did the Spanish appropriate Aztec sites of significance (e.g. Mexico City at the site of Tenochtitlan)?
  • What were reactions among Latin American intellectuals (e.g. Luis María Drago, Alejandro Álvarez and Baltasar Brum) to the Monroe Doctrine?
  • How was the US’s involvement in the Venezuela Crisis of 1902–1903 a pivotal turning point in the relationship between the US and Latin American countries?
  • What were the effects of the US’s involvement in the Cuban War for Independence?
  • How did the Roosevelt Corollary of 1904 benefit the US?
  • How did Simon Bolivar’s time in Europe affect his ideas about Latin American independence?
  • How did 19th century academic societies play a role in the advancement of scientific discoveries? Who was excluded from these societies?
  • How was music connected to the sciences in medieval thinking?
  • When was the concept of zero first used, and how was it instrumental for advancements in math?
  • What role did Islamic Spain play in the spread of scientific advancements in medieval Europe?
  • What role has translation between languages played in the development of sciences?
  • Why were Galileo’s ideas about astronomy controversial at the time?
  • What was the connection between art and advancements in human anatomy?
  • Why were Darwin’s ideas about natural selection controversial at the time?
  • To what degree does the film Master and Commander accurately depict the voyages of Charles Darwin?
  • How did the discovery of quinine and other medical innovations help to facilitate the European colonization of Africa?
  • How and why was the internet invented?
  • Does Virgil’s Aeneid celebrate the new Roman Empire or subvert it?
  • Why was the poet Ovid exiled from Rome?
  • What are the pagan influences in Beowulf ? What are the Christian elements in Beowulf ? What does that tell us about late Anglo-Saxon England?
  • How does Chaucer’s Canterbury Tales reflect gender roles in late medieval England?
  • How does Dante’s Inferno draw on book IV of Virgil’s Aeneid ? 
  • How are gender roles presented and subverted in Shakespeare’s plays?
  • To what degree did Henry David Thoreau live out the ideals he described in Walden in his own life?
  • How did the serialized publication of novels affect the way that they were written?
  • Does Dickens’ novel A Tale of Two Cities accurately portray the French Revolution?
  • How did 18th-century novels propagate the idea of marrying for love?
  • What did contemporary readers think about Jane Austen and her novels?
  • To what degree do Jane Austen’s novels reflect economic realities for women in Regency England? What do they leave out?
  • How did Lord Byron’s personal life affect his poetry?
  • What do we know about the romantic life of Emily Dickinson?
  • What were the religious movements that influenced the writer George Eliot, and how do those influences appear in her novels?
  • In what ways were Walt Whitman’s writings new or different?
  • How did British poets react to the horrors of Word War I?
  • What do Tolkien’s letters reveal about the ways in which the two world wars influenced his writings?
  • How did the friendship between CS Lewis and Tolkien affect their respective writings?
  • What are the arguments for and against Catalonian independence from Spain?
  • What are the arguments for and against Scottish independence from the United Kingdom?
  • What are some risks of contact sports, especially for children?
  • What are the most effective policies for combating childhood obesity?
  • What are the most effective policies for reducing gun violence?
  • Which countries have the longest life expectancy and why?
  • What are some differences between the healthcare system in the US and in European countries? Which country has the most similar system to the US?
  • What policies for parental leave exist in different countries? What are some effects of these policies?
  • Has the drinking age in the US always been 21? What have been some different policies, and what were some consequences of them?
  • What is the debate around museum artifacts like the Elgin Marbles in London or the Benin Bronzes in Berlin?
  • How have politicians attempted to control population growth in different countries, either directly or indirectly? What have been some effects of these policies?
  • Which countries have the most gender parity reflected in national governments? How have they accomplished this?
  • How has public funding of K-12 education changed since the 1930s in the US? 
  • How has public funding of higher education changed in the US?
  • What is early childhood education like in different countries?
  • What are some effects of free or reduced-cost meals in schools?
  • How does access to menstrual products affect education outcomes for girls in different countries?
  • What was the impact of Rousseau’s writings on education?
  • How did Plato’s ideal forms of government reflect contemporary Athenian concerns about the unruly masses ( demos )?
  • How did Aristotle justify slavery?
  • How has wealth inequality increased in recent decades?
  • How is inflation calculated, and what are the implications of this methodology?
  • How have genetically-engineered crops changed the way that the planet feeds itself?
  • How has animal testing changed since 2000?
  • How is animal testing regulated differently in different countries?

Health Sciences and Psychology

  • How do different societies reflect the natural circadian rhythms of the human body?
  • How does secondhand smoke affect the human body?
  • How does lack of sleep affect the body?
  • How does stress affect the body?
  • What are some ways to reduce stress?
  • How have cancer treatments changed in the past 30 years?
  • Why is it hard to find a “cure” for cancer?
  • How has the Human Genome Project changed medical science?
  • How were the Covid vaccines developed so quickly? What is the difference between the various Covid vaccines that have been developed?

Ready to start working on your research paper?

Our Ivy-League tutors can provide one-on-one writing coaching . Get expert help in selecting a topic that fits your assignment, finding research sources, creating an outline, drafting your paper, and revising for clarity.

Our writing coaches have helped students turn B- papers to A+ papers with just a few sessions together. We have experience working with students of all ages and writing abilities, from middle school students to college students at the nation’s top universities. What’s more, we’ll teach you how to write so that it’s easier the next time around!

A few times per year we also offer our bestselling academic writing workshop . Save your spot here !

Related posts

99 Great Handpicked Ideas for Argumentative Essays 12 Essential Steps for Writing an Argumentative Essay The 13 SAT and ACT Grammar Rules to Know 16 Essential Literary Devices to Know

database topics for research paper

Emily graduated  summa cum laude  from Princeton University and holds an MA from the University of Notre Dame. She was a National Merit Scholar and has won numerous academic prizes and fellowships. A veteran of the publishing industry, she has helped professors at Harvard, Yale, and Princeton revise their books and articles. Over the last decade, Emily has successfully mentored hundreds of students in all aspects of the college admissions process, including the SAT, ACT, and college application essay. 

CHECK OUT THESE RELATED POSTS

database topics for research paper

Can Chat GPT Write your College Essay?

February 21, 2024

Writing your college application essays? More and more students are trying to see if ChatGPT can help with their Common App essays. In this guide, we’ll break down how to use ChatGPT, if it’s actually helpful, and …

database topics for research paper

PSAT to digital SAT Score Conversion

February 19, 2024

Want to use your PSAT score to predict how you’ll do on the SAT? Our post uses the most updated date to help you convert your PSAT score into an SAT score.

database topics for research paper

Your Guide to Writing a Letter of Continued Interest to Colleges

February 13, 2024

Deferred or waitlisted from your dream school? You can still increase your chances of admission by writing a letter of continued interest, which …

SAT Math_ What to Expect (1)

SAT Math: What You Need to Know

February 8, 2024

There are two math sections on the SAT. Your performance on these contributes to 50% of your SAT composite score. Find strategies, SAT Math content, and more in this detailed post!

SAT Reading_PrepMaven

5 Digital SAT Reading Tips for a Top Score

February 1, 2024

What do you need to know to earn a high score on SAT Reading? We've got the expert answers and the strategies right here.

database topics for research paper

Digital SAT Score Range Breakdown

Wondering about what the SAT score range is, or what it means? Want to know how to put your score in context? In this guide, we’ll cover what the SAT score range is, how to interpret …

database topics for research paper

Guide to Digital SAT Scoring

Add excerpt here. Can reuse meta description.

database topics for research paper

What’s on the SAT in 2024?

January 23, 2024

Our comprehensive guide breaks down all content areas you need to know for the most recent version of the SAT, including math concepts, grammar, and …

database topics for research paper

12 SAT Grammar Rules for a Perfect Score

On the digital SAT, grammar questions make up almost a quarter of your total Reading and Writing score. In this post, we break down every grammar concept you need to know…

database topics for research paper

Getting A Perfect SAT Score: What You Need to Know

What does it take to get a perfect SAT score? Is there really a difference between a 1590 and a 1600? In this post, we explain what you need to know about…

Privacy Preference Center

Privacy preferences.

Research Paper Guide

Research Paper Topics

Nova A.

Interesting Research Paper Topics for 2024

20 min read

Published on: Dec 5, 2017

Last updated on: Jan 11, 2024

Research Paper Topics

People also read

Research Paper Writing - A Step by Step Guide

Research Paper Examples - Free Sample Papers for Different Formats!

Guide to Creating Effective Research Paper Outline

Research Proposal Writing - A Step-by-Step Guide

How to Start a Research Paper - 7 Easy Steps

How to Write an Abstract for a Research Paper - A Step by Step Guide

Writing a Literature Review For a Research Paper - A Comprehensive Guide

Qualitative Research - Methods, Types, and Examples

8 Types of Qualitative Research - Overview & Examples

Qualitative vs Quantitative Research - Learning the Basics

Psychology Research Topics - 220+ Ideas

How to Write a Hypothesis In 7 simple Steps: Examples and Tips!

20+ Types of Research With Examples - A Detailed Guide

Understanding Quantitative Research - Types & Data Collection Techniques

230+ Sociology Research Topics & Ideas for Students

How to Cite a Research Paper - A Complete Guide

Excellent History Research Paper Topics- 300+ Ideas

A Guide on Writing the Method Section of a Research Paper - Examples & Tips

How To Write an Introduction Paragraph For a Research Paper: Learn with Examples

Crafting a Winning Research Paper Title: A Complete Guide

Writing a Research Paper Conclusion - Step-by-Step Guide

Writing a Thesis For a Research Paper - A Comprehensive Guide

How To Write A Discussion For A Research Paper | Examples & Tips

How To Write The Results Section of A Research Paper | Steps & Examples

Writing a Problem Statement for a Research Paper - A Comprehensive Guide

Finding Sources For a Research Paper: A Complete Guide

Share this article

When it comes to writing a research paper, choosing a good topic is the first challenge students face.

Sometimes, instructors assign a topic or provide you with a range of topics for your research paper . But most of the time, you need to come up with a topic yourself.

It can be stressful. But don’t worry, this blog is here to help!

Here, we have listed more than 300 research paper ideas for a variety of subjects. These topics can help you get creative and find the inspiration you need.  So read on!

On This Page On This Page -->

What are Good Topics for a Research Paper? 

An interesting research topic is the one that has the following characteristics:

  • Specific and Clear . The topic should cover a specific aspect or question within a broader subject area. A focused topic allows for in-depth exploration.
  • Original and Unique - Great research topics are original. They explore a unique angle or perspective on a subject.
  • Significant - Good topics have academic or real-world significance. They contribute to existing knowledge or address a problem with practical implications.
  • Relevant - Topics that are timely and related to the current issues and debates in your field of study are better for research.

Research Paper Topics for Your Academic Level

All students get research writing assignments, whether they are in high school, college, or higher. Here are some engaging ideas suitable for different academic levels.

High School Research Essay Topics

  • Examine the impact of social media on teenagers' well-being.
  • Assess the effects of climate change and its consequences.
  • Analyze the dynamics of cyberbullying and online safety.
  • Explore the influence of music on adolescents.
  • Investigate the importance of financial literacy education.
  • Assess gender inequality in high school sports programs.
  • Examine the impact of technology on the education system.
  • Analyze youth voting trends and political engagement.
  • Investigate the role of video games in cognitive development.
  • Assess teenage substance abuse and prevention programs.

College Research Paper Topics 

  • IELTS vs. TOEFL - Discuss the similarities and differences.
  • College admission policies and criteria in the United States.
  • How to plan to pay college tuition?
  • Elaborate on ACT vs. SAT.
  • Benefits of Distance Learning.
  • Impacts of China's one-child policy.
  • Do college students learn better in same-sex classrooms?
  • Effect of the No Child Left Behind Act.
  • Analyze the history of the relationship between the United States and North Korea.
  • Should people be able to donate organs in exchange for money?

Graduate Research Paper Topics

  • The Impact of Artificial Intelligence on Business Operations and Strategy
  • Environmental Sustainability in Supply Chain Management: Strategies for Global Corporations
  • The Ethical Implications of Gene Editing Technologies: CRISPR-Cas9 and Beyond
  • Financial Derivatives and Risk Management: Advanced Strategies for Portfolio Optimization
  • The Role of Big Data Analytics in Healthcare: Improving Patient Care and Outcomes
  • Cybersecurity Threats and Mitigation in Critical Infrastructure: A Comprehensive Analysis
  • The Intersection of International Trade and Intellectual Property Rights: Trade Agreements and Dispute Resolution
  • Exploring the Impacts of Climate Change on Urban Planning and Infrastructure
  • Educational Leadership and School Reform in the 21st Century: Innovative Approaches and Challenges
  • Theoretical Advances in Quantum Computing: Applications, Limitations, and Future Prospects

Research Paper Topics for Science & Technology

Looking for research paper ideas in your discipline? The list of topics below covers a variety of subjects and disciplines to help you out.

Research Paper Topics for Computer Science 

  • Quantum Computing: Current State and Future Prospects
  • Artificial Intelligence in Healthcare: Diagnosis and Treatment
  • Blockchain Technology and Its Applications Beyond Cryptocurrency
  • Cybersecurity in the Age of IoT: Challenges and Solutions
  • The Ethical Implications of Machine Learning Algorithms
  • Natural Language Processing for Sentiment Analysis in Social Media
  • The Role of Computer Vision in Autonomous Vehicles
  • Big Data Analytics for Business Intelligence and Decision-Making
  • Human-Computer Interaction: Enhancing User Experience
  • The Evolution of Cloud Computing: Trends and Innovations

Research Paper Topics in Machine Learning

  • Explainable AI (XAI): Techniques and Challenges in Interpretable Machine Learning Models
  • Federated Learning: Privacy-Preserving Machine Learning Across Decentralized Data Sources
  • Transfer Learning in Deep Neural Networks: Methods, Applications, and Limitations
  • Reinforcement Learning: Recent Advances and Real-World Applications
  • Bias and Fairness in Machine Learning: Detection, Mitigation, and Ethical Considerations
  • Multi-Modal Learning: Integrating Data from Multiple Sources for Improved Performance
  • Generative Adversarial Networks (GANs): Innovations in Image Generation and Beyond
  • Natural Language Processing (NLP) for Healthcare: Applications in Clinical Data Analysis and Diagnosis
  • AutoML (Automated Machine Learning): Tools, Challenges, and Implications for Non-Experts
  • Quantum Machine Learning: Harnessing Quantum Computing for Advanced Data Analysis

Research Paper Topics in Chemistry

  • Green Chemistry: Sustainable Approaches to Chemical Synthesis
  • Nanotechnology in Drug Delivery: Innovations and Challenges
  • Chemical Analysis of Environmental Pollutants and Their Remediation
  • Advancements in Organic Synthesis: New Methods and Strategies
  • The Role of Catalysis in Industrial Chemical Processes
  • Chemical Kinetics: Studying Reaction Rates and Mechanisms
  • Analytical Chemistry Techniques for Food Safety and Quality Control
  • Supramolecular Chemistry: Self-assembly and Molecular Recognition
  • The Chemistry of Renewable Energy Sources
  • Chemical Bonding in Complex Molecules: Insights from Quantum Chemistry

Information Technology Research Paper Topics

  • The Impact of Artificial Intelligence on Information Technology
  • Blockchain Technology: Security and Privacy Implications
  • Data Governance and Compliance in the Digital Age
  • Cloud Computing Adoption Strategies for Small and Medium Enterprises
  • Internet of Things (IoT) Security Challenges and Solutions
  • E-Government: Advancements and Challenges in Digital Transformation
  • The Role of Machine Learning in Healthcare Data Management
  • Cybersecurity Threat Intelligence: Trends and Best Practices
  • Digital Twins and their Applications in Industry 4.0
  • Human-Centric IT: Designing Systems with User Well-being in Mind

Research Paper Topics Environmental Science

  • Climate Change and Its Impact on Global Ecosystems
  • Biodiversity Conservation and Habitat Restoration
  • Sustainable Agriculture Practices for Food Security
  • Air Pollution Control Strategies in Urban Environments
  • The Effects of Deforestation on Watersheds and Biodiversity
  • Waste Management and Recycling: Towards a Circular Economy
  • Ocean Acidification and Coral Reef Conservation
  • Environmental Impacts of Renewable Energy Technologies
  • Eco-friendly Transportation Solutions: Promoting Sustainable Mobility
  • Human Health and Environmental Pollution: Assessing Risks and Mitigation

Research Paper Topics for Medical Students

  • The Role of Telemedicine in Improving Healthcare Access and Delivery
  • Epidemiology and Management of Infectious Diseases: A Focus on Emerging Pathogens
  • Precision Medicine and Personalized Healthcare: Advancements and Challenges
  • Ethical Considerations in Medical Research: Informed Consent and Human Rights
  • Mental Health in Medical Education: Strategies for Reducing Burnout and Promoting Well-being
  • Global Health Disparities: Analyzing Causes and Strategies for Health Equity
  • Advancements in Surgical Techniques and Robotics in Medicine
  • The Opioid Epidemic: Causes, Consequences, and Solutions
  • Healthcare for Underserved Populations: Access, Barriers, and Innovations
  • Medical Innovations in Diagnostic Imaging: Impact on Patient Care and Diagnosis

Research Paper Topics in Zoology

  • The Impact of Climate Change on Wildlife Migration Patterns and Habitats
  • Behavioral Ecology of Apex Predators: From Wolves to Tigers
  • Zoonotic Diseases: Investigating the Transmission of Diseases Between Animals and Humans
  • Marine Biology and Conservation: Coral Reefs, Ocean Acidification, and Marine Biodiversity
  • The Role of Zoos in Conservation and Species Preservation
  • Invasive Species: Ecological Impacts and Management Strategies
  • Bird Migration and Navigation: Mechanisms and Conservation Implications
  • Animal Communication and Language: Insights from Studies on Dolphins and Primates
  • Endangered Species Recovery Programs: Successes, Failures, and Lessons Learned
  • Evolutionary Biology: The Coevolution of Predators and Prey

Research Paper Topics For Social Sciences

Are you a student of social sciences? The list of research paper topics below is for you!

History Research Paper Topics

  • The Causes and Consequences of the American Civil War
  • The Impact of the Industrial Revolution on Society and Labor
  • The Rise and Fall of the Roman Empire: Lessons from History
  • Women's Suffrage Movements Around the World
  • The Cold War: Origins, Conflicts, and Effects on Global Politics
  • The Role of Religion in Ancient Civilizations: Egypt, Mesopotamia, and Greece
  • The Renaissance Era: Art, Science, and Cultural Transformation
  • The Development of Culture in Mughal India
  • The Decolonization of Africa and Asia: Struggles for Independence
  • The Civil Rights Movement in the United States: Progress and Challenges

Research Paper Topics for Education

  • The Impact of Technology in the Classroom: Enhancing Learning or Distracting Students?
  • Inclusive Education: Strategies for Supporting Students with Disabilities
  • The Role of Parental Involvement in Student Academic Achievement
  • Education and Socioeconomic Inequality: Bridging the Gap
  • The Effectiveness of Online Learning: Pros and Cons
  • Early Childhood Education: The Importance of Preschool Programs
  • Teacher Burnout and Strategies for Teacher Well-being
  • The Influence of Standardized Testing on Curriculum and Instruction
  • Culturally Responsive Teaching: Promoting Diversity and Inclusion
  • Education Policy Reform: Challenges and Impacts on Student Success

Sociology Research Paper Topics 

  • The Impact of Social Media on Social Interaction and Relationships
  • Gender Inequality in the Workplace: Causes, Consequences, and Solutions
  • Racial Profiling and Policing: Examining Bias and Discrimination
  • The Sociology of Deviance: Understanding Criminal Behavior
  • Income Inequality and Its Effects on Society
  • The Influence of Family Structure on Child Development
  • Migration and the Social Integration of Immigrants
  • Environmental Sociology: Exploring the Relationship Between Society and the Environment
  • The Role of Religion in Shaping Societal Norms and Values
  • Health Disparities in Marginalized Communities: A Sociological Perspective

Psychology Research Paper Topics

  • The Impact of Childhood Trauma on Adult Mental Health
  • Psychological Effects of Social Media Use on Adolescents
  • Stress and Coping Mechanisms: Strategies for Resilience
  • The Psychology of Decision-Making: Biases and Heuristics
  • The Role of Attachment Theory in Parent-Child Relationships
  • Mental Health Stigma: Barriers to Seeking and Receiving Treatment
  • The Effects of Sleep Deprivation on Cognitive Functioning
  • Psychological Factors in Addiction and Recovery
  • Cognitive Development in Infants: Theories and Milestones
  • The Psychology of Happiness and Well-being: Factors and Interventions

Research Paper Topics On Media And Communication

  • The Influence of Social Media on Political Discourse and Public Opinion
  • Media Bias: Examining News Coverage and Its Impact on Perception
  • The Evolution of Journalism in the Digital Age: Challenges and Opportunities
  • The Effects of Advertising on Consumer Behavior and Purchasing Decisions
  • Media Literacy Education: Preparing Citizens for a Digital World
  • The Role of Media in Shaping Gender Stereotypes and Representation
  • Fake News and Misinformation: Causes, Consequences, and Solutions
  • Cultural Appropriation in Media: Analyzing Its Implications
  • Media and Crisis Communication: Case Studies and Best Practices
  • Media Effects on Body Image and Self-esteem: Exploring the Impact of Beauty Standards

Political Science Research Paper Topics

  • The Role of Political Parties in Shaping Government Policies
  • Electoral Systems and Their Impact on Representation and Governance
  • The Rise of Populism: Causes and Consequences
  • The Influence of Lobbying and Interest Groups on Policy-Making
  • Comparative Analysis of Political Systems: Democracies vs. Authoritarian Regimes
  • Foreign Policy Decision-Making: Case Studies and Models
  • Political Polarization: Understanding the Divisions in Contemporary Politics
  • Human Rights and International Relations: Challenges and Solutions
  • Environmental Politics and Climate Change Agreements
  • The Role of Social Media in Shaping Political Discourse and Activism

Research Paper Topics for International Relations

  • The Impact of Globalization on International Security
  • International Human Rights Law: Challenges and Progress
  • Diplomacy and Conflict Resolution: Case Studies in Successful Negotiations
  • The Role of International Organizations in Promoting Peace and Cooperation
  • Nuclear Proliferation: Examining the Threats and Non-Proliferation Efforts
  • Cybersecurity in International Relations: Challenges and Strategies
  • Global Economic Governance: The Role of International Financial Institutions
  • The Refugee Crisis: International Responses and the Humanitarian Challenge
  • Climate Change Diplomacy: Agreements, Obstacles, and Climate Justice
  • The Geopolitics of Energy: Resource Competition and Security Issues

Research Paper Topics On Culture

  • Cultural Appropriation: Understanding the Controversy and Implications
  • Cultural Relativism vs. Universalism: Debates in Anthropology and Ethics
  • Cultural Expressions in Art: Analyzing Cultural Identity Through Creative Works
  • Globalization and Its Impact on Cultural Homogenization vs. Cultural Diversity
  • Cultural Influences on Gender Roles and Identity
  • The Role of Culture in Shaping Dietary Habits and Food Traditions
  • Cultural Heritage Preservation: Challenges and Strategies
  • Language and Culture: The Relationship Between Linguistic Diversity and Cultural Identity
  • Cultural Rituals and Their Significance in Different Societies
  • Intercultural Communication: Navigating Cultural Differences in a Globalized World

Research Paper Topics for Humanities

Here are some engaging ideas for research paper topics in humanities disciplines.

Research Paper Topics for English Literature

  • Exploring the Themes of Love and Desire in Shakespeare's Sonnets
  • Postcolonial Literature: Analyzing the Works of Chimamanda Ngozi Adichie
  • The Role of Symbolism in F. Scott Fitzgerald's "The Great Gatsby"
  • Feminist Critique of Classic Literature: Reevaluating Jane Austen's Heroines
  • The Gothic Tradition in Literature: A Comparative Study of Edgar Allan Poe and Mary Shelley
  • Dystopian Literature: Examining Social Commentary in George Orwell's "1984"
  • The Evolution of Science Fiction: From H.G. Wells to Contemporary Authors
  • The Modernist Movement in Poetry: T.S. Eliot and "The Waste Land"
  • Literary Representations of War: Analysis of Ernest Hemingway's Works
  • The Influence of Mythology in Literature: A Study of Greek and Roman Epics

Research Paper Topics for Linguistics 

  • Language Acquisition: Exploring the Critical Period Hypothesis
  • The Evolution of Language: Tracing the Origins and Development
  • Bilingualism and Cognitive Benefits: Analyzing the Effects on Brain Function
  • The Role of Gender in Language: A Sociolinguistic Examination
  • Phonological Variation in Regional Dialects: Case Studies and Implications
  • Language and Identity: How Language Reflects and Shapes Cultural Identity
  • The Influence of Technology on Language: Texting, Social Media, and Communication Styles
  • Language Preservation and Endangered Languages: Strategies and Challenges
  • Syntax and Semantics: The Relationship Between Sentence Structure and Meaning
  • Language Contact and Creole Languages: Origins and Linguistic Features

Research Paper Topics on Arts

  • The Influence of Renaissance Art on Modern Visual Culture
  • The Evolution of Street Art: From Vandalism to Urban Beautification
  • Gender and Identity in Contemporary Performance Art
  • The Role of Public Art in Shaping Urban Spaces and Communities
  • Censorship in the Arts: Balancing Expression and Sensitivity
  • The Intersection of Technology and Art: Digital Media and New Frontiers
  • Art as a Form of Political Protest: Examining Contemporary Activist Art
  • The Psychology of Art Appreciation: Understanding Aesthetic Experiences
  • Art Conservation and Preservation: Challenges and Ethical Considerations
  • Art Therapy: Exploring the Healing Power of Creativity

Research Paper Topics on Religion

  • Religious Pluralism and Interfaith Dialogue: Promoting Understanding and Tolerance
  • The Role of Religion in Shaping Moral Values and Ethics
  • Religion and Politics: Examining the Influence of Faith on Governance
  • Religious Rituals and Their Significance in Different Cultures
  • Secularism and Its Impact on Religious Practice and Belief
  • Religion and Science: Exploring the Compatibility and Conflict
  • The Influence of Religion on Gender Roles and Equality
  • Religious Fundamentalism and Its Implications for Society
  • Religion and Environmental Ethics: Perspectives on Stewardship
  • Religious Conversion and the Psychology Behind Faith Changes

Philosophy Research Paper Topics

  • The Philosophy of Ethics: Exploring Different Ethical Theories
  • The Problem of Free Will and Determinism: Philosophical Perspectives
  • Existentialism in Literature: A Philosophical Analysis
  • The Philosophy of Mind: Dualism vs. Materialism
  • The Nature of Reality: Metaphysical Approaches and Debates
  • Moral Dilemmas and Ethical Decision-Making: A Philosophical Examination
  • Philosophy of Technology: Ethical Implications of Advancements
  • Political Philosophy: Theories of Justice and Social Contracts
  • Philosophy of Religion: The Existence of God and Theodicy
  • Environmental Ethics: Philosophical Perspectives on Nature and Sustainability

Research Paper Topics for Ethics

  • Ethical Dilemmas in Medical Decision-Making: Balancing Autonomy and Beneficence
  • The Ethics of Artificial Intelligence: Accountability and Bias in AI Systems
  • Corporate Ethics: Ethical Responsibility of Multinational Corporations
  • Ethical Considerations in Environmental Conservation: Sustainability and Future Generations
  • The Ethics of Genetic Engineering and Designer Babies
  • The Intersection of Ethics and Technology: Privacy, Surveillance, and Data Ethics
  • Ethical Implications of End-of-Life Care and Euthanasia
  • Animal Rights and Ethical Treatment of Animals in Research
  • The Role of Ethics in Criminal Justice: Police Conduct and Criminal Punishment
  • The Ethics of Whistleblowing: Balancing Loyalty and Accountability

Law Research Paper Topics

  • The Evolution of Privacy Rights in the Digital Age: Legal and Ethical Considerations
  • Criminal Justice Reform: Assessing the Impact of Changes in Sentencing and Policing
  • Intellectual Property Rights in the Digital Era: Copyright, Trademarks, and Patents
  • The Role of International Law in Addressing Global Human Rights Violations
  • Environmental Law and Sustainable Development: Balancing Conservation and Economic Interests
  • Legal Aspects of Cybersecurity: Privacy, Data Protection, and Cybercrime
  • The Legalization of Marijuana: Implications for Criminal Justice and Public Health
  • Corporate Governance and Ethics: Analyzing Legal Frameworks for Accountability
  • Family Law and Child Custody Disputes: Examining Best Interests and Parental Rights
  • The Intersection of Law and Bioethics: Ethical Dilemmas in Medical and Scientific Research

Research Paper Topics on Criminal Justice 

  • Racial Disparities in the Criminal Justice System: Causes and Consequences
  • Police Use of Force: Policies, Accountability, and Community Relations
  • Criminal Profiling and Its Effectiveness in Solving Crimes
  • Mental Illness in the Criminal Justice System: Diversion Programs and Treatment
  • The Impact of Mass Incarceration on Communities and Rehabilitation Efforts
  • Forensic Science and Criminal Investigations: Advances, Challenges, and Ethics
  • Cybercrime and Digital Forensics: Investigative Techniques and Legal Implications
  • Juvenile Justice: Rehabilitation vs. Punishment and the Recidivism Rate
  • The Death Penalty: Ethical, Legal, and Policy Considerations
  • Victim Rights and Restorative Justice Programs: Balancing the Scales of Justice

Research Paper Topics on Economics

  • Income Inequality: Causes, Consequences, and Policy Solutions
  • The Impact of Economic Globalization on Developing Countries
  • Behavioral Economics: Exploring Psychological Factors in Decision-Making
  • The Economics of Climate Change: Mitigation and Adaptation Strategies
  • Monetary Policy and Its Effects on Economic Stability
  • Trade Wars and Tariffs: Economic Effects and Global Trade Relations
  • Healthcare Economics: Examining Healthcare Costs, Access, and Reform
  • The Economics of Education: Investment in Human Capital and Economic Growth
  • Urban Economics: Challenges and Solutions in Sustainable City Development
  • Labor Market Trends: Gig Economy, Automation, and Future of Work

Research Paper Topics Related to Marketing

  • Influencer Marketing: Effectiveness, Ethics, and the Role of Social Media
  • Consumer Behavior in the Digital Age: Online Shopping Trends and Decision-Making
  • Brand Loyalty and Customer Retention Strategies in Competitive Markets
  • Neuromarketing: Understanding the Psychology of Consumer Choices
  • The Impact of Social Media Marketing on Brand Image and Customer Engagement
  • E-commerce and Marketplaces: Strategies for Success in Online Retail
  • Content Marketing: Creating and Measuring the Value of Branded Content
  • Marketing to Generation Z: Preferences, Values, and Communication Channels
  • The Role of Sustainability and Corporate Social Responsibility (CSR) in Marketing
  • Crisis Marketing and Reputation Management: Strategies for Navigating Challenges

Best Research Paper Topics 2023

Here are some impressive and easy research paper topics to write an extraordinary paper.

Argumentative Research Paper Topics 

  • Should the Minimum Wage be Raised?
  • The Impact of Social Media on Mental Health: Harmful or Beneficial?
  • Is Genetic Engineering Ethical? Examining the Pros and Cons of Genetic Modification
  • The Death Penalty: Should it be Abolished or Retained?
  • Gun Control: Balancing Second Amendment Rights and Public Safety
  • Universal Healthcare: Is it a Right or a Privilege?
  • The Role of Government in Regulating Big Tech Companies
  • Climate Change: Is Human Activity the Primary Cause?
  • Online Privacy: Balancing Security and Civil Liberties
  • The Legalization of Recreational Marijuana: Weighing the Social and Economic Impacts

US History Research Paper Topics

  • The American Revolution: Causes, Key Figures, and Impact on the Nation
  • The Abolitionist Movement: Strategies, Leaders, and the Fight Against Slavery
  • The Reconstruction Era: Challenges, Achievements, and Failures
  • The Women's Suffrage Movement: Struggles and Triumphs in the Fight for Voting Rights
  • The Civil Rights Movement: Leaders, Events, and the Struggle for Equality
  • The Great Depression: Causes, Effects, and Government Responses
  • The Vietnam War: Origins, Controversies, and Legacy
  • The Space Race: The Cold War Competition for Supremacy Beyond Earth
  • The Civil War: Battlefronts, Political Divisions, and the Emancipation Proclamation
  • The American Westward Expansion: Manifest Destiny, Conflicts, and Impacts on Native Americans

Persuasive Research Paper Topics 

  • The Importance of Comprehensive Sex Education in Schools
  • Banning Single-Use Plastics: Protecting the Environment and Marine Life
  • Promoting Renewable Energy: Transitioning to a Sustainable Future
  • Mandatory Vaccination: Protecting Public Health and Herd Immunity
  • The Benefits of Telecommuting: A Win-Win for Employers and Employees
  • Promoting Healthy Eating Habits: The Case for Implementing Sugar Taxes
  • The Need for Stricter Animal Welfare Laws: Preventing Animal Cruelty
  • Accessible Education for All: The Case for Affordable College Tuition
  • Promoting Voting Rights: Ensuring a Fair and Inclusive Democracy
  • The Importance of Mental Health Awareness and Support: Breaking the Stigma

Easy Research Paper Topics 

  • The Benefits of Regular Exercise for Physical and Mental Health
  • The History and Impact of Social Media on Society
  • The Basics of Climate Change: Causes, Effects, and Solutions
  • The Life and Achievements of a Notable Inventor or Scientist
  • The Importance of Recycling and Waste Reduction in Daily Life
  • The Impact of Fast Food on Diet and Health
  • The History and Significance of a Local Landmark or Historical Site
  • The Role of Pets in Reducing Stress and Promoting Well-being
  • The Basics of Internet Safety: Protecting Personal Information Online
  • Exploring a Popular Book, Movie, or TV Series and Its Cultural Influence

Research Paper Topics on Current Affairs 

  • The Impact of COVID-19 on Global Health Systems and Preparedness
  • Climate Change and Extreme Weather Events: Mitigation and Adaptation Strategies
  • The Future of Work: Remote Work Trends and Implications
  • Economic Recovery Post-Pandemic: Challenges and Opportunities
  • Vaccine Hesitancy: Understanding Causes and Addressing Concerns
  • Cybersecurity in the Digital Age: Threats, Vulnerabilities, and Defense
  • Immigration Policies and Border Security: A Global Perspective
  • The Role of Social Media in Political Movements and Disinformation
  • Global Supply Chain Disruptions: Causes and Strategies for Resilience
  • Racial and Social Justice Movements: Progress and Ongoing Challenges

Controversial Research Paper Topics 

  • The Legalization of Assisted Suicide and Euthanasia: Ethical and Legal Considerations
  • Gun Control Laws: Balancing Second Amendment Rights and Public Safety
  • The Death Penalty: Is it an Effective Deterrent or a Violation of Human Rights?
  • Animal Testing: Ethical Issues and Alternatives for Scientific Research
  • The Legalization of Recreational Drugs: Assessing Risks and Benefits
  • Abortion: Examining the Ethical, Legal, and Medical Aspects
  • Freedom of Speech vs. Hate Speech: Protecting Civil Liberties in a Digital Age
  • Climate Change Denial: Analyzing the Science and Skepticism
  • School Vouchers and School Choice: The Future of Public Education
  • Genetically Modified Organisms (GMOs): Safety, Labeling, and Environmental Concerns

Nursing Research Paper Topics 

  • The Impact of Nurse-to-Patient Ratios on Patient Outcomes
  • Nursing Shortages: Causes, Consequences, and Solutions
  • Evidence-Based Practice in Nursing: Implementing Research into Clinical Care
  • Nursing Ethics: Ethical Dilemmas and Decision-Making in Patient Care
  • Palliative Care and End-of-Life Nursing: Improving Quality of Life for Patients
  • Nursing Informatics: Advancements in Healthcare Technology and Data Management
  • The Role of Cultural Competence in Nursing: Providing Culturally Sensitive Care
  • Nursing Burnout and Staff Well-being: Strategies for Prevention and Support
  • The Impact of Nurse Leadership on Patient Safety and Quality of Care
  • Pediatric Nursing: Specialized Care for Children and Families

How to Choose a Good Research Paper Topic?

Now that you have a plethora of ideas for your research paper, which one should you choose? Here are some steps you need to follow to choose a good research paper topic: 

  • Identify Your Interests: Start by considering your own interests and passions. Research is much more enjoyable when you're exploring a topic you're genuinely curious about. Think about subjects, issues, or questions that intrigue you.
  • Brainstorm and Mind Map: Write down potential topics or research questions and create a mind map to visualize how they connect to one another. This can help you see the relationships between different ideas and narrow down your options.
  • Do Some Preliminary Research: Conduct initial research to see what resources are available on potential topics. This will help you gauge whether there is enough information and credible sources to support your research.
  • Consider Your Audience: Think about who will be reading your research paper. Tailor your topic to your target audience's interests and knowledge level. You should also comply with the instructor's requirements. Make sure your topic gets approved before you begin with the writing process.
  • Discuss with Others: Talk to your peers, professors, or mentors about your potential topics. They may offer valuable insights, suggest relevant resources, or help you refine your ideas.

To conclude,

Selecting a research paper topic is the first and most important step of your research journey. Your decision should be guided by your interests, the assignment requirements, and the availability of credible resources. 

With this list of potential research paper topics and tips on how to choose a good topic, you are able to select a topic that is both engaging for you and relevant to your audience.

Remember that staying current and conducting preliminary research will help you make an informed choice. Seek feedback from peers and mentors, and don't shy away from challenging or controversial topics when appropriate. 

Want research experts to help you out? Look no further! MyPerfectWords.com can help you out!

At our paper writing service online , we have subject specialists and research writers with advanced knowledge and expertise. They will help you craft a great topic and can help you write an amazing research paper.

So place your order today to get a  custom research paper !

Nova A. (Literature, Marketing)

Nova Allison is a Digital Content Strategist with over eight years of experience. Nova has also worked as a technical and scientific writer. She is majorly involved in developing and reviewing online content plans that engage and resonate with audiences. Nova has a passion for writing that engages and informs her readers.

Paper Due? Why Suffer? That’s our Job!

Get Help

Keep reading

Research Paper Topics

We value your privacy

We use cookies to improve your experience and give you personalized content. Do you agree to our cookie policy?

Website Data Collection

We use data collected by cookies and JavaScript libraries.

Are you sure you want to cancel?

Your preferences have not been saved.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • View all journals
  • My Account Login
  • Explore content
  • About the journal
  • Publish with us
  • Sign up for alerts
  • Open access
  • Published: 19 February 2024

Genomic data in the All of Us Research Program

The all of us research program genomics investigators.

Nature ( 2024 ) Cite this article

34k Accesses

523 Altmetric

Metrics details

  • Genetic variation
  • Genome-wide association studies

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics 1 , 2 , 3 , 4 . The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health 5 , 6 . Here we describe the programme’s genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.

Comprehensively identifying genetic variation and cataloguing its contribution to health and disease, in conjunction with environmental and lifestyle factors, is a central goal of human health research 1 , 2 . A key limitation in efforts to build this catalogue has been the historic under-representation of large subsets of individuals in biomedical research including individuals from diverse ancestries, individuals with disabilities and individuals from disadvantaged backgrounds 3 , 4 . The All of Us Research Program (All of Us) aims to address this gap by enrolling and collecting comprehensive health data on at least one million individuals who reflect the diversity across the USA 5 , 6 . An essential component of All of Us is the generation of whole-genome sequence (WGS) and genotyping data on one million participants. All of Us is committed to making this dataset broadly useful—not only by democratizing access to this dataset across the scientific community but also to return value to the participants themselves by returning individual DNA results, such as genetic ancestry, hereditary disease risk and pharmacogenetics according to clinical standards, to those who wish to receive these research results.

Here we describe the release of WGS data from 245,388 All of Us participants and demonstrate the impact of this high-quality data in genetic and health studies. We carried out a series of data harmonization and quality control (QC) procedures and conducted analyses characterizing the properties of the dataset including genetic ancestry and relatedness. We validated the data by replicating well-established genotype–phenotype associations including low-density lipoprotein cholesterol (LDL-C) and 117 additional diseases. These data are available through the All of Us Researcher Workbench, a cloud platform that embodies and enables programme priorities, facilitating equitable data and compute access while ensuring responsible conduct of research and protecting participant privacy through a passport data access model.

The All of Us Research Program

To accelerate health research, All of Us is committed to curating and releasing research data early and often 6 . Less than five years after national enrolment began in 2018, this fifth data release includes data from more than 413,000 All of Us participants. Summary data are made available through a public Data Browser, and individual-level participant data are made available to researchers through the Researcher Workbench (Fig. 1a and Data availability).

figure 1

a , The All of Us Research Hub contains a publicly accessible Data Browser for exploration of summary phenotypic and genomic data. The Researcher Workbench is a secure cloud-based environment of participant-level data in a Controlled Tier that is widely accessible to researchers. b , All of Us participants have rich phenotype data from a combination of physical measurements, survey responses, EHRs, wearables and genomic data. Dots indicate the presence of the specific data type for the given number of participants. c , Overall summary of participants under-represented in biomedical research (UBR) with data available in the Controlled Tier. The All of Us logo in a is reproduced with permission of the National Institutes of Health’s All of Us Research Program.

Participant data include a rich combination of phenotypic and genomic data (Fig. 1b ). Participants are asked to complete consent for research use of data, sharing of electronic health records (EHRs), donation of biospecimens (blood or saliva, and urine), in-person provision of physical measurements (height, weight and blood pressure) and surveys initially covering demographics, lifestyle and overall health 7 . Participants are also consented for recontact. EHR data, harmonized using the Observational Medical Outcomes Partnership Common Data Model 8 ( Methods ), are available for more than 287,000 participants (69.42%) from more than 50 health care provider organizations. The EHR dataset is longitudinal, with a quarter of participants having 10 years of EHR data (Extended Data Fig. 1 ). Data include 245,388 WGSs and genome-wide genotyping on 312,925 participants. Sequenced and genotyped individuals in this data release were not prioritized on the basis of any clinical or phenotypic feature. Notably, 99% of participants with WGS data also have survey data and physical measurements, and 84% also have EHR data. In this data release, 77% of individuals with genomic data identify with groups historically under-represented in biomedical research, including 46% who self-identify with a racial or ethnic minority group (Fig. 1c , Supplementary Table 1 and Supplementary Note ).

Scaling the All of Us infrastructure

The genomic dataset generated from All of Us participants is a resource for research and discovery and serves as the basis for return of individual health-related DNA results to participants. Consequently, the US Food and Drug Administration determined that All of Us met the criteria for a significant risk device study. As such, the entire All of Us genomics effort from sample acquisition to sequencing meets clinical laboratory standards 9 .

All of Us participants were recruited through a national network of partners, starting in 2018, as previously described 5 . Participants may enrol through All of Us - funded health care provider organizations or direct volunteer pathways and all biospecimens, including blood and saliva, are sent to the central All of Us Biobank for processing and storage. Genomics data for this release were generated from blood-derived DNA. The programme began return of actionable genomic results in December 2022. As of April 2023, approximately 51,000 individuals were sent notifications asking whether they wanted to view their results, and approximately half have accepted. Return continues on an ongoing basis.

The All of Us Data and Research Center maintains all participant information and biospecimen ID linkage to ensure that participant confidentiality and coded identifiers (participant and aliquot level) are used to track each sample through the All of Us genomics workflow. This workflow facilitates weekly automated aliquot and plating requests to the Biobank, supplies relevant metadata for the sample shipments to the Genome Centers, and contains a feedback loop to inform action on samples that fail QC at any stage. Further, the consent status of each participant is checked before sample shipment to confirm that they are still active. Although all participants with genomic data are consented for the same general research use category, the programme accommodates different preferences for the return of genomic data to participants and only data for those individuals who have consented for return of individual health-related DNA results are distributed to the All of Us Clinical Validation Labs for further evaluation and health-related clinical reporting. All participants in All of Us that choose to get health-related DNA results have the option to schedule a genetic counselling appointment to discuss their results. Individuals with positive findings who choose to obtain results are required to schedule an appointment with a genetic counsellor to receive those findings.

Genome sequencing

To satisfy the requirements for clinical accuracy, precision and consistency across DNA sample extraction and sequencing, the All of Us Genome Centers and Biobank harmonized laboratory protocols, established standard QC methodologies and metrics, and conducted a series of validation experiments using previously characterized clinical samples and commercially available reference standards 9 . Briefly, PCR-free barcoded WGS libraries were constructed with the Illumina Kapa HyperPrep kit. Libraries were pooled and sequenced on the Illumina NovaSeq 6000 instrument. After demultiplexing, initial QC analysis is performed with the Illumina DRAGEN pipeline (Supplementary Table 2 ) leveraging lane, library, flow cell, barcode and sample level metrics as well as assessing contamination, mapping quality and concordance to genotyping array data independently processed from a different aliquot of DNA. The Genome Centers use these metrics to determine whether each sample meets programme specifications and then submits sequencing data to the Data and Research Center for further QC, joint calling and distribution to the research community ( Methods ).

This effort to harmonize sequencing methods, multi-level QC and use of identical data processing protocols mitigated the variability in sequencing location and protocols that often leads to batch effects in large genomic datasets 9 . As a result, the data are not only of clinical-grade quality, but also consistent in coverage (≥30× mean) and uniformity across Genome Centers (Supplementary Figs. 1 – 5 ).

Joint calling and variant discovery

We carried out joint calling across the entire All of Us WGS dataset (Extended Data Fig. 2 ). Joint calling leverages information across samples to prune artefact variants, which increases sensitivity, and enables flagging samples with potential issues that were missed during single-sample QC 10 (Supplementary Table 3 ). Scaling conventional approaches to whole-genome joint calling beyond 50,000 individuals is a notable computational challenge 11 , 12 . To address this, we developed a new cloud variant storage solution, the Genomic Variant Store (GVS), which is based on a schema designed for querying and rendering variants in which the variants are stored in GVS and rendered to an analysable variant file, as opposed to the variant file being the primary storage mechanism (Code availability). We carried out QC on the joint call set on the basis of the approach developed for gnomAD 3.1 (ref.  13 ). This included flagging samples with outlying values in eight metrics (Supplementary Table 4 , Supplementary Fig. 2 and Methods ).

To calculate the sensitivity and precision of the joint call dataset, we included four well-characterized samples. We sequenced the National Institute of Standards and Technology reference materials (DNA samples) from the Genome in a Bottle consortium 13 and carried out variant calling as described above. We used the corresponding published set of variant calls for each sample as the ground truth in our sensitivity and precision calculations 14 . The overall sensitivity for single-nucleotide variants was over 98.7% and precision was more than 99.9%. For short insertions or deletions, the sensitivity was over 97% and precision was more than 99.6% (Supplementary Table 5 and Methods ).

The joint call set included more than 1 billion genetic variants. We annotated the joint call dataset on the basis of functional annotation (for example, gene symbol and protein change) using Illumina Nirvana 15 . We defined coding variants as those inducing an amino acid change on a canonical ENSEMBL transcript and found 272,051,104 non-coding and 3,913,722 coding variants that have not been described previously in dbSNP 16 v153 (Extended Data Table 1 ). A total of 3,912,832 (99.98%) of the coding variants are rare (allelic frequency < 0.01) and the remaining 883 (0.02%) are common (allelic frequency > 0.01). Of the coding variants, 454 (0.01%) are common in one or more of the non-European computed ancestries in All of Us, rare among participants of European ancestry, and have an allelic number greater than 1,000 (Extended Data Table 2 and Extended Data Fig. 3 ). The distributions of pathogenic, or likely pathogenic, ClinVar variant counts per participant, stratified by computed ancestry, filtered to only those variants that are found in individuals with an allele count of <40 are shown in Extended Data Fig. 4 . The potential medical implications of these known and new variants with respect to variant pathogenicity by ancestry are highlighted in a companion paper 17 . In particular, we find that the European ancestry subset has the highest rate of pathogenic variation (2.1%), which was twice the rate of pathogenic variation in individuals of East Asian ancestry 17 .The lower frequency of variants in East Asian individuals may be partially explained by the fact the sample size in that group is small and there may be knowledge bias in the variant databases that is reducing the number of findings in some of the less-studied ancestry groups.

Genetic ancestry and relatedness

Genetic ancestry inference confirmed that 51.1% of the All of Us WGS dataset is derived from individuals of non-European ancestry. Briefly, the ancestry categories are based on the same labels used in gnomAD 18 . We trained a classifier on a 16-dimensional principal component analysis (PCA) space of a diverse reference based on 3,202 samples and 151,159 autosomal single-nucleotide polymorphisms. We projected the All of Us samples into the PCA space of the training data, based on the same single-nucleotide polymorphisms from the WGS data, and generated categorical ancestry predictions from the trained classifier ( Methods ). Continuous genetic ancestry fractions for All of Us samples were inferred using the same PCA data, and participants’ patterns of ancestry and admixture were compared to their self-identified race and ethnicity (Fig. 2 and Methods ). Continuous ancestry inference carried out using genome-wide genotypes yields highly concordant estimates.

figure 2

a , b , Uniform manifold approximation and projection (UMAP) representations of All of Us WGS PCA data with self-described race ( a ) and ethnicity ( b ) labels. c , Proportion of genetic ancestry per individual in six distinct and coherent ancestry groups defined by Human Genome Diversity Project and 1000 Genomes samples.

Kinship estimation confirmed that All of Us WGS data consist largely of unrelated individuals with about 85% (215,107) having no first- or second-degree relatives in the dataset (Supplementary Fig. 6 ). As many genomic analyses leverage unrelated individuals, we identified the smallest set of samples that are required to be removed from the remaining individuals that had first- or second-degree relatives and retained one individual from each kindred. This procedure yielded a maximal independent set of 231,442 individuals (about 94%) with genome sequence data in the current release ( Methods ).

Genetic determinants of LDL-C

As a measure of data quality and utility, we carried out a single-variant genome-wide association study (GWAS) for LDL-C, a trait with well-established genomic architecture ( Methods ). Of the 245,388 WGS participants, 91,749 had one or more LDL-C measurements. The All of Us LDL-C GWAS identified 20 well-established genome-wide significant loci, with minimal genomic inflation (Fig. 3 , Extended Data Table 3 and Supplementary Fig. 7 ). We compared the results to those of a recent multi-ethnic LDL-C GWAS in the National Heart, Lung, and Blood Institute (NHLBI) TOPMed study that included 66,329 ancestrally diverse (56% non-European ancestry) individuals 19 . We found a strong correlation between the effect estimates for NHLBI TOPMed genome-wide significant loci and those of All of Us ( R 2  = 0.98, P  < 1.61 × 10 −45 ; Fig. 3 , inset). Notably, the per-locus effect sizes observed in All of Us are decreased compared to those in TOPMed, which is in part due to differences in the underlying statistical model, differences in the ancestral composition of these datasets and differences in laboratory value ascertainment between EHR-derived data and epidemiology studies. A companion manuscript extended this work to identify common and rare genetic associations for three diseases (atrial fibrillation, coronary artery disease and type 2 diabetes) and two quantitative traits (height and LDL-C) in the All of Us dataset and identified very high concordance with previous efforts across all of these diseases and traits 20 .

figure 3

Manhattan plot demonstrating robust replication of 20 well-established LDL-C genetic loci among 91,749 individuals with 1 or more LDL-C measurements. The red horizontal line denotes the genome wide significance threshold of P = 5 × 10 –8 . Inset, effect estimate ( β ) comparison between NHLBI TOPMed LDL-C GWAS ( x  axis) and All of Us LDL-C GWAS ( y  axis) for the subset of 194 independent variants clumped (window 250 kb, r2 0.5) that reached genome-wide significance in NHLBI TOPMed.

Genotype-by-phenotype associations

As another measure of data quality and utility, we tested replication rates of previously reported phenotype–genotype associations in the five predicted genetic ancestry populations present in the Phenotype/Genotype Reference Map (PGRM): AFR, African ancestry; AMR, Latino/admixed American ancestry; EAS, East Asian ancestry; EUR, European ancestry; SAS, South Asian ancestry. The PGRM contains published associations in the GWAS catalogue in these ancestry populations that map to International Classification of Diseases-based phenotype codes 21 . This replication study specifically looked across 4,947 variants, calculating replication rates for powered associations in each ancestry population. The overall replication rates for associations powered at 80% were: 72.0% (18/25) in AFR, 100% (13/13) in AMR, 46.6% (7/15) in EAS, 74.9% (1,064/1,421) in EUR, and 100% (1/1) in SAS. With the exception of the EAS ancestry results, these powered replication rates are comparable to those of the published PGRM analysis where the replication rates of several single-site EHR-linked biobanks ranges from 76% to 85%. These results demonstrate the utility of the data and also highlight opportunities for further work understanding the specifics of the All of Us population and the potential contribution of gene–environment interactions to genotype–phenotype mapping and motivates the development of methods for multi-site EHR phenotype data extraction, harmonization and genetic association studies.

More broadly, the All of Us resource highlights the opportunities to identify genotype–phenotype associations that differ across diverse populations 22 . For example, the Duffy blood group locus ( ACKR1 ) is more prevalent in individuals of AFR ancestry and individuals of AMR ancestry than in individuals of EUR ancestry. Although the phenome-wide association study of this locus highlights the well-established association of the Duffy blood group with lower white blood cell counts both in individuals of AFR and AMR ancestry 23 , 24 , it also revealed genetic-ancestry-specific phenotype patterns, with minimal phenotypic associations in individuals of EAS ancestry and individuals of EUR ancestry (Fig. 4 and Extended Data Table 4 ). Conversely, rs9273363 in the HLA-DQB1 locus is associated with increased risk of type 1 diabetes 25 , 26 and diabetic complications across ancestries, but only associates with increased risk of coeliac disease in individuals of EUR ancestry (Extended Data Fig. 5 ). Similarly, the TCF7L2 locus 27 strongly associates with increased risk of type 2 diabetes and associated complications across several ancestries (Extended Data Fig. 6 ). Association testing results are available in Supplementary Dataset 1 .

figure 4

Results of genetic-ancestry-stratified phenome-wide association analysis among unrelated individuals highlighting ancestry-specific disease associations across the four most common genetic ancestries of participant. Bonferroni-adjusted phenome-wide significance threshold (<2.88 × 10 −5 ) is plotted as a red horizontal line. AFR ( n  = 34,037, minor allele fraction (MAF) 0.82); AMR ( n  = 28,901, MAF 0.10); EAS ( n  = 32,55, MAF 0.003); EUR ( n  = 101,613, MAF 0.007).

The cloud-based Researcher Workbench

All of Us genomic data are available in a secure, access-controlled cloud-based analysis environment: the All of Us Researcher Workbench. Unlike traditional data access models that require per-project approval, access in the Researcher Workbench is governed by a data passport model based on a researcher’s authenticated identity, institutional affiliation, and completion of self-service training and compliance attestation 28 . After gaining access, a researcher may create a new workspace at any time to conduct a study, provided that they comply with all Data Use Policies and self-declare their research purpose. This information is regularly audited and made accessible publicly on the All of Us Research Projects Directory. This streamlined access model is guided by the principles that: participants are research partners and maintaining their privacy and data security is paramount; their data should be made as accessible as possible for authorized researchers; and we should continually seek to remove unnecessary barriers to accessing and using All of Us data.

For researchers at institutions with an existing institutional data use agreement, access can be gained as soon as they complete the required verification and compliance steps. As of August 2023, 556 institutions have agreements in place, allowing more than 5,000 approved researchers to actively work on more than 4,400 projects. The median time for a researcher from initial registration to completion of these requirements is 28.6 h (10th percentile: 48 min, 90th percentile: 14.9 days), a fraction of the weeks to months it can take to assemble a project-specific application and have it reviewed by an access board with conventional access models.

Given that the size of the project’s phenotypic and genomic dataset is expected to reach 4.75 PB in 2023, the use of a central data store and cloud analysis tools will save funders an estimated US$16.5 million per year when compared to the typical approach of allowing researchers to download genomic data. Storing one copy per institution of this data at 556 registered institutions would cost about US$1.16 billion per year. By contrast, storing a central cloud copy costs about US$1.14 million per year, a 99.9% saving. Importantly, cloud infrastructure also democratizes data access particularly for researchers who do not have high-performance local compute resources.

Here we present the All of Us Research Program’s approach to generating diverse clinical-grade genomic data at an unprecedented scale. We present the data release of about 245,000 genome sequences as part of a scalable framework that will grow to include genetic information and health data for one million or more people living across the USA. Our observations permit several conclusions.

First, the All of Us programme is making a notable contribution to improving the study of human biology through purposeful inclusion of under-represented individuals at scale 29 , 30 . Of the participants with genomic data in All of Us, 45.92% self-identified as a non-European race or ethnicity. This diversity enabled identification of more than 275 million new genetic variants across the dataset not previously captured by other large-scale genome aggregation efforts with diverse participants that have submitted variation to dbSNP v153, such as NHLBI TOPMed 31 freeze 8 (Extended Data Table 1 ). In contrast to gnomAD, All of Us permits individual-level genotype access with detailed phenotype data for all participants. Furthermore, unlike many genomics resources, All of Us is uniformly consented for general research use and enables researchers to go from initial account creation to individual-level data access in as little as a few hours. The All of Us cohort is significantly more diverse than those of other large contemporary research studies generating WGS data 32 , 33 . This enables a more equitable future for precision medicine (for example, through constructing polygenic risk scores that are appropriately calibrated to diverse populations 34 , 35 as the eMERGE programme has done leveraging All of Us data 36 , 37 ). Developing new tools and regulatory frameworks to enable analyses across multiple biobanks in the cloud to harness the unique strengths of each is an active area of investigation addressed in a companion paper to this work 38 .

Second, the All of Us Researcher Workbench embodies the programme’s design philosophy of open science, reproducible research, equitable access and transparency to researchers and to research participants 26 . Importantly, for research studies, no group of data users should have privileged access to All of Us resources based on anything other than data protection criteria. Although the All of Us Researcher Workbench initially targeted onboarding US academic, health care and non-profit organizations, it has recently expanded to international researchers. We anticipate further genomic and phenotypic data releases at regular intervals with data available to all researcher communities. We also anticipate additional derived data and functionality to be made available, such as reference data, structural variants and a service for array imputation using the All of Us genomic data.

Third, All of Us enables studying human biology at an unprecedented scale. The programmatic goal of sequencing one million or more genomes has required harnessing the output of multiple sequencing centres. Previous work has focused on achieving functional equivalence in data processing and joint calling pipelines 39 . To achieve clinical-grade data equivalence, All of Us required protocol equivalence at both sequencing production level and data processing across the sequencing centres. Furthermore, previous work has demonstrated the value of joint calling at scale 10 , 18 . The new GVS framework developed by the All of Us programme enables joint calling at extreme scales (Code availability). Finally, the provision of data access through cloud-native tools enables scalable and secure access and analysis to researchers while simultaneously enabling the trust of research participants and transparency underlying the All of Us data passport access model.

The clinical-grade sequencing carried out by All of Us enables not only research, but also the return of value to participants through clinically relevant genetic results and health-related traits to those who opt-in to receiving this information. In the years ahead, we anticipate that this partnership with All of Us participants will enable researchers to move beyond large-scale genomic discovery to understanding the consequences of implementing genomic medicine at scale.

The All of Us cohort

All of Us aims to engage a longitudinal cohort of one million or more US participants, with a focus on including populations that have historically been under-represented in biomedical research. Details of the All of Us cohort have been described previously 5 . Briefly, the primary objective is to build a robust research resource that can facilitate the exploration of biological, clinical, social and environmental determinants of health and disease. The programme will collect and curate health-related data and biospecimens, and these data and biospecimens will be made broadly available for research uses. Health data are obtained through the electronic medical record and through participant surveys. Survey templates can be found on our public website: https://www.researchallofus.org/data-tools/survey-explorer/ . Adults 18 years and older who have the capacity to consent and reside in the USA or a US territory at present are eligible. Informed consent for all participants is conducted in person or through an eConsent platform that includes primary consent, HIPAA Authorization for Research use of EHRs and other external health data, and Consent for Return of Genomic Results. The protocol was reviewed by the Institutional Review Board (IRB) of the All of Us Research Program. The All of Us IRB follows the regulations and guidance of the NIH Office for Human Research Protections for all studies, ensuring that the rights and welfare of research participants are overseen and protected uniformly.

Data accessibility through a ‘data passport’

Authorization for access to participant-level data in All of Us is based on a ‘data passport’ model, through which authorized researchers do not need IRB review for each research project. The data passport is required for gaining data access to the Researcher Workbench and for creating workspaces to carry out research projects using All of Us data. At present, data passports are authorized through a six-step process that includes affiliation with an institution that has signed a Data Use and Registration Agreement, account creation, identity verification, completion of ethics training, and attestation to a data user code of conduct. Results reported follow the All of Us Data and Statistics Dissemination Policy disallowing disclosure of group counts under 20 to protect participant privacy without seeking prior approval 40 .

At present, All of Us gathers EHR data from about 50 health care organizations that are funded to recruit and enrol participants as well as transfer EHR data for those participants who have consented to provide them. Data stewards at each provider organization harmonize their local data to the Observational Medical Outcomes Partnership (OMOP) Common Data Model, and then submit it to the All of Us Data and Research Center (DRC) so that it can be linked with other participant data and further curated for research use. OMOP is a common data model standardizing health information from disparate EHRs to common vocabularies and organized into tables according to data domains. EHR data are updated from the recruitment sites and sent to the DRC quarterly. Updated data releases to the research community occur approximately once a year. Supplementary Table 6 outlines the OMOP concepts collected by the DRC quarterly from the recruitment sites.

Biospecimen collection and processing

Participants who consented to participate in All of Us donated fresh whole blood (4 ml EDTA and 10 ml EDTA) as a primary source of DNA. The All of Us Biobank managed by the Mayo Clinic extracted DNA from 4 ml EDTA whole blood, and DNA was stored at −80 °C at an average concentration of 150 ng µl −1 . The buffy coat isolated from 10 ml EDTA whole blood has been used for extracting DNA in the case of initial extraction failure or absence of 4 ml EDTA whole blood. The Biobank plated 2.4 µg DNA with a concentration of 60 ng µl −1 in duplicate for array and WGS samples. The samples are distributed to All of Us Genome Centers weekly, and a negative (empty well) control and National Institute of Standards and Technology controls are incorporated every two months for QC purposes.

Genome Center sample receipt, accession and QC

On receipt of DNA sample shipments, the All of Us Genome Centers carry out an inspection of the packaging and sample containers to ensure that sample integrity has not been compromised during transport and to verify that the sample containers correspond to the shipping manifest. QC of the submitted samples also includes DNA quantification, using routine procedures to confirm volume and concentration (Supplementary Table 7 ). Any issues or discrepancies are recorded, and affected samples are put on hold until resolved. Samples that meet quality thresholds are accessioned in the Laboratory Information Management System, and sample aliquots are prepared for library construction processing (for example, normalized with respect to concentration and volume).

WGS library construction, sequencing and primary data QC

The DNA sample is first sheared using a Covaris sonicator and is then size-selected using AMPure XP beads to restrict the range of library insert sizes. Using the PCR Free Kapa HyperPrep library construction kit, enzymatic steps are completed to repair the jagged ends of DNA fragments, add proper A-base segments, and ligate indexed adapter barcode sequences onto samples. Excess adaptors are removed using AMPure XP beads for a final clean-up. Libraries are quantified using quantitative PCR with the Illumina Kapa DNA Quantification Kit and then normalized and pooled for sequencing (Supplementary Table 7 ).

Pooled libraries are loaded on the Illumina NovaSeq 6000 instrument. The data from the initial sequencing run are used to QC individual libraries and to remove non-conforming samples from the pipeline. The data are also used to calibrate the pooling volume of each individual library and re-pool the libraries for additional NovaSeq sequencing to reach an average coverage of 30×.

After demultiplexing, WGS analysis occurs on the Illumina DRAGEN platform. The DRAGEN pipeline consists of highly optimized algorithms for mapping, aligning, sorting, duplicate marking and haplotype variant calling and makes use of platform features such as compression and BCL conversion. Alignment uses the GRCh38dh reference genome. QC data are collected at every stage of the analysis protocol, providing high-resolution metrics required to ensure data consistency for large-scale multiplexing. The DRAGEN pipeline produces a large number of metrics that cover lane, library, flow cell, barcode and sample-level metrics for all runs as well as assessing contamination and mapping quality. The All of Us Genome Centers use these metrics to determine pass or fail for each sample before submitting the CRAM files to the All of Us DRC. For mapping and variant calling, all Genome Centers have harmonized on a set of DRAGEN parameters, which ensures consistency in processing (Supplementary Table 2 ).

Every step through the WGS procedure is rigorously controlled by predefined QC measures. Various control mechanisms and acceptance criteria were established during WGS assay validation. Specific metrics for reviewing and releasing genome data are: mean coverage (threshold of ≥30×), genome coverage (threshold of ≥90% at 20×), coverage of hereditary disease risk genes (threshold of ≥95% at 20×), aligned Q30 bases (threshold of ≥8 × 10 10 ), contamination (threshold of ≤1%) and concordance to independently processed array data.

Array genotyping

Samples are processed for genotyping at three All of Us Genome Centers (Broad, Johns Hopkins University and University of Washington). DNA samples are received from the Biobank and the process is facilitated by the All of Us genomics workflow described above. All three centres used an identical array product, scanners, resource files and genotype calling software for array processing to reduce batch effects. Each centre has its own Laboratory Information Management System that manages workflow control, sample and reagent tracking, and centre-specific liquid handling robotics.

Samples are processed using the Illumina Global Diversity Array (GDA) with Illumina Infinium LCG chemistry using the automated protocol and scanned on Illumina iSCANs with Automated Array Loaders. Illumina IAAP software converts raw data (IDAT files; 2 per sample) into a single GTC file per sample using the BPM file (defines strand, probe sequences and illumicode address) and the EGT file (defines the relationship between intensities and genotype calls). Files used for this data release are: GDA-8v1-0_A5.bpm, GDA-8v1-0_A1_ClusterFile.egt, gentrain v3, reference hg19 and gencall cutoff 0.15. The GDA array assays a total of 1,914,935 variant positions including 1,790,654 single-nucleotide variants, 44,172 indels, 9,935 intensity-only probes for CNV calling, and 70,174 duplicates (same position, different probes). Picard GtcToVcf is used to convert the GTC files to VCF format. Resulting VCF and IDAT files are submitted to the DRC for ingestion and further processing. The VCF file contains assay name, chromosome, position, genotype calls, quality score, raw and normalized intensities, B allele frequency and log R ratio values. Each genome centre is running the GDA array under Clinical Laboratory Improvement Amendments-compliant protocols. The GTC files are parsed and metrics are uploaded to in-house Laboratory Information Management System systems for QC review.

At batch level (each set of 96-well plates run together in the laboratory at one time), each genome centre includes positive control samples that are required to have >98% call rate and >99% concordance to existing data to approve release of the batch of data. At the sample level, the call rate and sex are the key QC determinants 41 . Contamination is also measured using BAFRegress 42 and reported out as metadata. Any sample with a call rate below 98% is repeated one time in the laboratory. Genotyped sex is determined by plotting normalized x versus normalized y intensity values for a batch of samples. Any sample discordant with ‘sex at birth’ reported by the All of Us participant is flagged for further detailed review and repeated one time in the laboratory. If several sex-discordant samples are clustered on an array or on a 96-well plate, the entire array or plate will have data production repeated. Samples identified with sex chromosome aneuploidies are also reported back as metadata (XXX, XXY, XYY and so on). A final processing status of ‘pass’, ‘fail’ or ‘abandon’ is determined before release of data to the All of Us DRC. An array sample will pass if the call rate is >98% and the genotyped sex and sex at birth are concordant (or the sex at birth is not applicable). An array sample will fail if the genotyped sex and the sex at birth are discordant. An array sample will have the status of abandon if the call rate is <98% after at least two attempts at the genome centre.

Data from the arrays are used for participant return of genetic ancestry and non-health-related traits for those who consent, and they are also used to facilitate additional QC of the matched WGS data. Contamination is assessed in the array data to determine whether DNA re-extraction is required before WGS. Re-extraction is prompted by level of contamination combined with consent status for return of results. The arrays are also used to confirm sample identity between the WGS data and the matched array data by assessing concordance at 100 unique sites. To establish concordance, a fingerprint file of these 100 sites is provided to the Genome Centers to assess concordance with the same sites in the WGS data before CRAM submission.

Genomic data curation

As seen in Extended Data Fig. 2 , we generate a joint call set for all WGS samples and make these data available in their entirety and by sample subsets to researchers. A breakdown of the frequencies, stratified by computed ancestries for which we had more than 10,000 participants can be found in Extended Data Fig. 3 . The joint call set process allows us to leverage information across samples to improve QC and increase accuracy.

Single-sample QC

If a sample fails single-sample QC, it is excluded from the release and is not reported in this document. These tests detect sample swaps, cross-individual contamination and sample preparation errors. In some cases, we carry out these tests twice (at both the Genome Center and the DRC), for two reasons: to confirm internal consistency between sites; and to mark samples as passing (or failing) QC on the basis of the research pipeline criteria. The single-sample QC process accepts a higher contamination rate than the clinical pipeline (0.03 for the research pipeline versus 0.01 for the clinical pipeline), but otherwise uses identical thresholds. The list of specific QC processes, passing criteria, error modes addressed and an overview of the results can be found in Supplementary Table 3 .

Joint call set QC

During joint calling, we carry out additional QC steps using information that is available across samples including hard thresholds, population outliers, allele-specific filters, and sensitivity and precision evaluation. Supplementary Table 4 summarizes both the steps that we took and the results obtained for the WGS data. More detailed information about the methods and specific parameters can be found in the All of Us Genomic Research Data Quality Report 36 .

Batch effect analysis

We analysed cross-sequencing centre batch effects in the joint call set. To quantify the batch effect, we calculated Cohen’s d (ref.  43 ) for four metrics (insertion/deletion ratio, single-nucleotide polymorphism count, indel count and single-nucleotide polymorphism transition/transversion ratio) across the three genome sequencing centres (Baylor College of Medicine, Broad Institute and University of Washington), stratified by computed ancestry and seven regions of the genome (whole genome, high-confidence calling, repetitive, GC content of >0.85, GC content of <0.15, low mappability, the ACMG59 genes and regions of large duplications (>1 kb)). Using random batches as a control set, all comparisons had a Cohen’s d of <0.35. Here we report any Cohen’s d results >0.5, which we chose before this analysis and is conventionally the threshold of a medium effect size 44 .

We found that there was an effect size in indel counts (Cohen’s d of 0.53) in the entire genome, between Broad Institute and University of Washington, but this was being driven by repetitive and low-mappability regions. We found no batch effects with Cohen’s d of >0.5 in the ratio metrics or in any metrics in the high-confidence calling, low or high GC content, or ACMG59 regions. A complete list of the batch effects with Cohen’s d of >0.5 are found in Supplementary Table 8 .

Sensitivity and precision evaluation

To determine sensitivity and precision, we included four well-characterized control samples (four National Institute of Standards and Technology Genome in a Bottle samples (HG-001, HG-003, HG-004 and HG-005). The samples were sequenced with the same protocol as All of Us. Of note, these samples were not included in data released to researchers. We used the corresponding published set of variant calls for each sample as the ground truth in our sensitivity and precision calculations. We use the high-confidence calling region, defined by Genome in a Bottle v4.2.1, as the source of ground truth. To be called a true positive, a variant must match the chromosome, position, reference allele, alternate allele and zygosity. In cases of sites with multiple alternative alleles, each alternative allele is considered separately. Sensitivity and precision results are reported in Supplementary Table 5 .

Genetic ancestry inference

We computed categorical ancestry for all WGS samples in All of Us and made these available to researchers. These predictions are also the basis for population allele frequency calculations in the Genomic Variants section of the public Data Browser. We used the high-quality set of sites to determine an ancestry label for each sample. The ancestry categories are based on the same labels used in gnomAD 18 , the Human Genome Diversity Project (HGDP) 45 and 1000 Genomes 1 : African (AFR); Latino/admixed American (AMR); East Asian (EAS); Middle Eastern (MID); European (EUR), composed of Finnish (FIN) and Non-Finnish European (NFE); Other (OTH), not belonging to one of the other ancestries or is an admixture; South Asian (SAS).

We trained a random forest classifier 46 on a training set of the HGDP and 1000 Genomes samples variants on the autosome, obtained from gnomAD 11 . We generated the first 16 principal components (PCs) of the training sample genotypes (using the hwe_normalized_pca in Hail) at the high-quality variant sites for use as the feature vector for each training sample. We used the truth labels from the sample metadata, which can be found alongside the VCFs. Note that we do not train the classifier on the samples labelled as Other. We use the label probabilities (‘confidence’) of the classifier on the other ancestries to determine ancestry of Other.

To determine the ancestry of All of Us samples, we project the All of Us samples into the PCA space of the training data and apply the classifier. As a proxy for the accuracy of our All of Us predictions, we look at the concordance between the survey results and the predicted ancestry. The concordance between self-reported ethnicity and the ancestry predictions was 87.7%.

PC data from All of Us samples and the HGDP and 1000 Genomes samples were used to compute individual participant genetic ancestry fractions for All of Us samples using the Rye program. Rye uses PC data to carry out rapid and accurate genetic ancestry inference on biobank-scale datasets 47 . HGDP and 1000 Genomes reference samples were used to define a set of six distinct and coherent ancestry groups—African, East Asian, European, Middle Eastern, Latino/admixed American and South Asian—corresponding to participant self-identified race and ethnicity groups. Rye was run on the first 16 PCs, using the defined reference ancestry groups to assign ancestry group fractions to individual All of Us participant samples.

Relatedness

We calculated the kinship score using the Hail pc_relate function and reported any pairs with a kinship score above 0.1. The kinship score is half of the fraction of the genetic material shared (ranges from 0.0 to 0.5). We determined the maximal independent set 41 for related samples. We identified a maximally unrelated set of 231,442 samples (94%) for kinship scored greater than 0.1.

LDL-C common variant GWAS

The phenotypic data were extracted from the Curated Data Repository (CDR, Control Tier Dataset v7) in the All of Us Researcher Workbench. The All of Us Cohort Builder and Dataset Builder were used to extract all LDL cholesterol measurements from the Lab and Measurements criteria in EHR data for all participants who have WGS data. The most recent measurements were selected as the phenotype and adjusted for statin use 19 , age and sex. A rank-based inverse normal transformation was applied for this continuous trait to increase power and deflate type I error. Analysis was carried out on the Hail MatrixTable representation of the All of Us WGS joint-called data including removing monomorphic variants, variants with a call rate of <95% and variants with extreme Hardy–Weinberg equilibrium values ( P  < 10 −15 ). A linear regression was carried out with REGENIE 48 on variants with a minor allele frequency >5%, further adjusting for relatedness to the first five ancestry PCs. The final analysis included 34,924 participants and 8,589,520 variants.

Genotype-by-phenotype replication

We tested replication rates of known phenotype–genotype associations in three of the four largest populations: EUR, AFR and EAS. The AMR population was not included because they have no registered GWAS. This method is a conceptual extension of the original GWAS × phenome-wide association study, which replicated 66% of powered associations in a single EHR-linked biobank 49 . The PGRM is an expansion of this work by Bastarache et al., based on associations in the GWAS catalogue 50 in June 2020 (ref.  51 ). After directly matching the Experimental Factor Ontology terms to phecodes, the authors identified 8,085 unique loci and 170 unique phecodes that compose the PGRM. They showed replication rates in several EHR-linked biobanks ranging from 76% to 85%. For this analysis, we used the EUR-, and AFR-based maps, considering only catalogue associations that were P  < 5 × 10 −8 significant.

The main tools used were the Python package Hail for data extraction, plink for genomic associations, and the R packages PheWAS and pgrm for further analysis and visualization. The phenotypes, participant-reported sex at birth, and year of birth were extracted from the All of Us CDR (Controlled Tier Dataset v7). These phenotypes were then loaded into a plink-compatible format using the PheWAS package, and related samples were removed by sub-setting to the maximally unrelated dataset ( n  = 231,442). Only samples with EHR data were kept, filtered by selected loci, annotated with demographic and phenotypic information extracted from the CDR and ancestry prediction information provided by All of Us, ultimately resulting in 181,345 participants for downstream analysis. The variants in the PGRM were filtered by a minimum population-specific allele frequency of >1% or population-specific allele count of >100, leaving 4,986 variants. Results for which there were at least 20 cases in the ancestry group were included. Then, a series of Firth logistic regression tests with phecodes as the outcome and variants as the predictor were carried out, adjusting for age, sex (for non-sex-specific phenotypes) and the first three genomic PC features as covariates. The PGRM was annotated with power calculations based on the case counts and reported allele frequencies. Power of 80% or greater was considered powered for this analysis.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The All of Us Research Hub has a tiered data access data passport model with three data access tiers. The Public Tier dataset contains only aggregate data with identifiers removed. These data are available to the public through Data Snapshots ( https://www.researchallofus.org/data-tools/data-snapshots/ ) and the public Data Browser ( https://databrowser.researchallofus.org/ ). The Registered Tier curated dataset contains individual-level data, available only to approved researchers on the Researcher Workbench. At present, the Registered Tier includes data from EHRs, wearables and surveys, as well as physical measurements taken at the time of participant enrolment. The Controlled Tier dataset contains all data in the Registered Tier and additionally genomic data in the form of WGS and genotyping arrays, previously suppressed demographic data fields from EHRs and surveys, and unshifted dates of events. At present, Registered Tier and Controlled Tier data are available to researchers at academic institutions, non-profit institutions, and both non-profit and for-profit health care institutions. Work is underway to begin extending access to additional audiences, including industry-affiliated researchers. Researchers have the option to register for Registered Tier and/or Controlled Tier access by completing the All of Us Researcher Workbench access process, which includes identity verification and All of Us-specific training in research involving human participants ( https://www.researchallofus.org/register/ ). Researchers may create a new workspace at any time to conduct any research study, provided that they comply with all Data Use Policies and self-declare their research purpose. This information is made accessible publicly on the All of Us Research Projects Directory at https://allofus.nih.gov/protecting-data-and-privacy/research-projects-all-us-data .

Code availability

The GVS code is available at https://github.com/broadinstitute/gatk/tree/ah_var_store/scripts/variantstore . The LDL GWAS pipeline is available as a demonstration project in the Featured Workspace Library on the Researcher Workbench ( https://workbench.researchallofus.org/workspaces/aou-rw-5981f9dc/aouldlgwasregeniedsubctv6duplicate/notebooks ).

The 1000 Genomes Project Consortium et al. A global reference for human genetic variation. Nature 526 , 68–74 (2015).

Article   Google Scholar  

Claussnitzer, M. et al. A brief history of human disease genetics. Nature 577 , 179–189 (2020).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Wojcik, G. L. et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature 570 , 514–518 (2019).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Lewis, A. C. F. et al. Getting genetic ancestry right for science and society. Science 376 , 250–252 (2022).

All of Us Program Investigators. The “All of Us” Research Program. N. Engl. J. Med. 381 , 668–676 (2019).

Ramirez, A. H., Gebo, K. A. & Harris, P. A. Progress with the All of Us Research Program: opening access for researchers. JAMA 325 , 2441–2442 (2021).

Article   PubMed   Google Scholar  

Ramirez, A. H. et al. The All of Us Research Program: data quality, utility, and diversity. Patterns 3 , 100570 (2022).

Article   PubMed   PubMed Central   Google Scholar  

Overhage, J. M., Ryan, P. B., Reich, C. G., Hartzema, A. G. & Stang, P. E. Validation of a common data model for active safety surveillance research. J. Am. Med. Inform. Assoc. 19 , 54–60 (2012).

Venner, E. et al. Whole-genome sequencing as an investigational device for return of hereditary disease risk and pharmacogenomic results as part of the All of Us Research Program. Genome Med. 14 , 34 (2022).

Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536 , 285–291 (2016).

Tiao, G. & Goodrich, J. gnomAD v3.1 New Content, Methods, Annotations, and Data Availability ; https://gnomad.broadinstitute.org/news/2020-10-gnomad-v3-1-new-content-methods-annotations-and-data-availability/ .

Chen, S. et al. A genomic mutational constraint map using variation in 76,156 human genomes. Nature 625 , 92–100 (2022).

Zook, J. M. et al. An open resource for accurately benchmarking small variant and reference calls. Nat. Biotechnol. 37 , 561–566 (2019).

Krusche, P. et al. Best practices for benchmarking germline small-variant calls in human genomes. Nat. Biotechnol. 37 , 555–560 (2019).

Stromberg, M. et al. Nirvana: clinical grade variant annotator. In Proc. 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics 596 (Association for Computing Machinery, 2017).

Sherry, S. T. et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res. 29 , 308–311 (2001).

Venner, E. et al. The frequency of pathogenic variation in the All of Us cohort reveals ancestry-driven disparities. Commun. Biol. https://doi.org/10.1038/s42003-023-05708-y (2024).

Karczewski, S. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581 , 434–443 (2020).

Selvaraj, M. S. et al. Whole genome sequence analysis of blood lipid levels in >66,000 individuals. Nat. Commun. 13 , 5995 (2022).

Wang, X. et al. Common and rare variants associated with cardiometabolic traits across 98,622 whole-genome sequences in the All of Us research program. J. Hum. Genet. 68 , 565–570 (2023).

Bastarache, L. et al. The phenotype-genotype reference map: improving biobank data science through replication. Am. J. Hum. Genet. 110 , 1522–1533 (2023).

Bianchi, D. W. et al. The All of Us Research Program is an opportunity to enhance the diversity of US biomedical research. Nat. Med. https://doi.org/10.1038/s41591-023-02744-3 (2024).

Van Driest, S. L. et al. Association between a common, benign genotype and unnecessary bone marrow biopsies among African American patients. JAMA Intern. Med. 181 , 1100–1105 (2021).

Chen, M.-H. et al. Trans-ethnic and ancestry-specific blood-cell genetics in 746,667 individuals from 5 global populations. Cell 182 , 1198–1213 (2020).

Chiou, J. et al. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics. Nature 594 , 398–402 (2021).

Hu, X. et al. Additive and interaction effects at three amino acid positions in HLA-DQ and HLA-DR molecules drive type 1 diabetes risk. Nat. Genet. 47 , 898–905 (2015).

Grant, S. F. A. et al. Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes. Nat. Genet. 38 , 320–323 (2006).

Article   CAS   PubMed   Google Scholar  

All of Us Research Program. Framework for Access to All of Us Data Resources v1.1 (2021); https://www.researchallofus.org/wp-content/themes/research-hub-wordpress-theme/media/data&tools/data-access-use/AoU_Data_Access_Framework_508.pdf .

Abul-Husn, N. S. & Kenny, E. E. Personalized medicine and the power of electronic health records. Cell 177 , 58–69 (2019).

Mapes, B. M. et al. Diversity and inclusion for the All of Us research program: A scoping review. PLoS ONE 15 , e0234962 (2020).

Taliun, D. et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature 590 , 290–299 (2021).

Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562 , 203–209 (2018).

Halldorsson, B. V. et al. The sequences of 150,119 genomes in the UK Biobank. Nature 607 , 732–740 (2022).

Kurniansyah, N. et al. Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups. Nat. Commun. 14 , 3202 (2023).

Hou, K. et al. Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals. Nat. Genet. 55 , 549– 558 (2022).

Linder, J. E. et al. Returning integrated genomic risk and clinical recommendations: the eMERGE study. Genet. Med. 25 , 100006 (2023).

Lennon, N. J. et al. Selection, optimization and validation of ten chronic disease polygenic risk scores for clinical implementation in diverse US populations. Nat. Med. https://doi.org/10.1038/s41591-024-02796-z (2024).

Deflaux, N. et al. Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis. Nat. Commun. 14 , 5419 (2023).

Regier, A. A. et al. Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects. Nat. Commun. 9 , 4038 (2018).

Article   ADS   PubMed   PubMed Central   Google Scholar  

All of Us Research Program. Data and Statistics Dissemination Policy (2020); https://www.researchallofus.org/wp-content/themes/research-hub-wordpress-theme/media/2020/05/AoU_Policy_Data_and_Statistics_Dissemination_508.pdf .

Laurie, C. C. et al. Quality control and quality assurance in genotypic data for genome-wide association studies. Genet. Epidemiol. 34 , 591–602 (2010).

Jun, G. et al. Detecting and estimating contamination of human DNA samples in sequencing and array-based genotype data. Am. J. Hum. Genet. 91 , 839–848 (2012).

Cohen, J. Statistical Power Analysis for the Behavioral Sciences (Routledge, 2013).

Andrade, C. Mean difference, standardized mean difference (SMD), and their use in meta-analysis. J. Clin. Psychiatry 81 , 20f13681 (2020).

Cavalli-Sforza, L. L. The Human Genome Diversity Project: past, present and future. Nat. Rev. Genet. 6 , 333–340 (2005).

Ho, T. K. Random decision forests. In Proc. 3rd International Conference on Document Analysis and Recognition (IEEE Computer Society Press, 2002).

Conley, A. B. et al. Rye: genetic ancestry inference at biobank scale. Nucleic Acids Res. 51 , e44 (2023).

Mbatchou, J. et al. Computationally efficient whole-genome regression for quantitative and binary traits. Nat. Genet. 53 , 1097–1103 (2021).

Denny, J. C. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat. Biotech. 31 , 1102–1111 (2013).

Buniello, A. et al. The NHGRI-EBI GWAS catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47 , D1005–D1012 (2019).

Bastarache, L. et al. The Phenotype-Genotype Reference Map: improving biobank data science through replication. Am. J. Hum. Genet. 10 , 1522–1533 (2023).

Download references

Acknowledgements

The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers (OT2 OD026549; OT2 OD026554; OT2 OD026557; OT2 OD026556; OT2 OD026550; OT2 OD 026552; OT2 OD026553; OT2 OD026548; OT2 OD026551; OT2 OD026555); Inter agency agreement AOD 16037; Federally Qualified Health Centers HHSN 263201600085U; Data and Research Center: U2C OD023196; Genome Centers (OT2 OD002748; OT2 OD002750; OT2 OD002751); Biobank: U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: U24 OD023163; Communications and Engagement: OT2 OD023205; OT2 OD023206; and Community Partners (OT2 OD025277; OT2 OD025315; OT2 OD025337; OT2 OD025276). In addition, the All of Us Research Program would not be possible without the partnership of its participants. All of Us and the All of Us logo are service marks of the US Department of Health and Human Services. E.E.E. is an investigator of the Howard Hughes Medical Institute. We acknowledge the foundational contributions of our friend and colleague, the late Deborah A. Nickerson. Debbie’s years of insightful contributions throughout the formation of the All of Us genomics programme are permanently imprinted, and she shares credit for all of the successes of this programme.

Author information

Authors and affiliations.

Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

Alexander G. Bick & Henry R. Condon

Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA

Ginger A. Metcalf, Eric Boerwinkle, Richard A. Gibbs, Donna M. Muzny, Eric Venner, Kimberly Walker, Jianhong Hu, Harsha Doddapaneni, Christie L. Kovar, Mullai Murugan, Shannon Dugan, Ziad Khan & Eric Boerwinkle

Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA

Kelsey R. Mayo, Jodell E. Linder, Melissa Basford, Ashley Able, Ashley E. Green, Robert J. Carroll, Jennifer Zhang & Yuanyuan Wang

Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA

Lee Lichtenstein, Anthony Philippakis, Sophie Schwartz, M. Morgan T. Aster, Kristian Cibulskis, Andrea Haessly, Rebecca Asch, Aurora Cremer, Kylee Degatano, Akum Shergill, Laura D. Gauthier, Samuel K. Lee, Aaron Hatcher, George B. Grant, Genevieve R. Brandt, Miguel Covarrubias, Eric Banks & Wail Baalawi

Verily, South San Francisco, CA, USA

Shimon Rura, David Glazer, Moira K. Dillon & C. H. Albach

Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA

Robert J. Carroll, Paul A. Harris & Dan M. Roden

All of Us Research Program, National Institutes of Health, Bethesda, MD, USA

Anjene Musick, Andrea H. Ramirez, Sokny Lim, Siddhartha Nambiar, Bradley Ozenberger, Anastasia L. Wise, Chris Lunt, Geoffrey S. Ginsburg & Joshua C. Denny

School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA

I. King Jordan, Shashwat Deepali Nagar & Shivam Sharma

Neuroscience Institute, Institute of Translational Genomic Medicine, Morehouse School of Medicine, Atlanta, GA, USA

Robert Meller

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

Mine S. Cicek, Stephen N. Thibodeau & Mine S. Cicek

Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

Kimberly F. Doheny, Michelle Z. Mawhinney, Sean M. L. Griffith, Elvin Hsu, Hua Ling & Marcia K. Adams

Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA

Evan E. Eichler, Joshua D. Smith, Christian D. Frazar, Colleen P. Davis, Karynne E. Patterson, Marsha M. Wheeler, Sean McGee, Mitzi L. Murray, Valeria Vasta, Dru Leistritz, Matthew A. Richardson, Aparna Radhakrishnan & Brenna W. Ehmen

Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA

Evan E. Eichler

Broad Institute of MIT and Harvard, Cambridge, MA, USA

Stacey Gabriel, Heidi L. Rehm, Niall J. Lennon, Christina Austin-Tse, Eric Banks, Michael Gatzen, Namrata Gupta, Katie Larsson, Sheli McDonough, Steven M. Harrison, Christopher Kachulis, Matthew S. Lebo, Seung Hoan Choi & Xin Wang

Division of Medical Genetics, Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA

Gail P. Jarvik & Elisabeth A. Rosenthal

Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

Dan M. Roden

Department of Pharmacology, Vanderbilt University Medical Center, Nashville, TN, USA

Center for Individualized Medicine, Biorepository Program, Mayo Clinic, Rochester, MN, USA

Stephen N. Thibodeau, Ashley L. Blegen, Samantha J. Wirkus, Victoria A. Wagner, Jeffrey G. Meyer & Mine S. Cicek

Color Health, Burlingame, CA, USA

Scott Topper, Cynthia L. Neben, Marcie Steeves & Alicia Y. Zhou

School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA

Eric Boerwinkle

Laboratory for Molecular Medicine, Massachusetts General Brigham Personalized Medicine, Cambridge, MA, USA

Christina Austin-Tse, Emma Henricks & Matthew S. Lebo

Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA

Christina M. Lockwood, Brian H. Shirts, Colin C. Pritchard, Jillian G. Buchan & Niklas Krumm

Manuscript Writing Group

  • Alexander G. Bick
  • , Ginger A. Metcalf
  • , Kelsey R. Mayo
  • , Lee Lichtenstein
  • , Shimon Rura
  • , Robert J. Carroll
  • , Anjene Musick
  • , Jodell E. Linder
  • , I. King Jordan
  • , Shashwat Deepali Nagar
  • , Shivam Sharma
  •  & Robert Meller

All of Us Research Program Genomics Principal Investigators

  • Melissa Basford
  • , Eric Boerwinkle
  • , Mine S. Cicek
  • , Kimberly F. Doheny
  • , Evan E. Eichler
  • , Stacey Gabriel
  • , Richard A. Gibbs
  • , David Glazer
  • , Paul A. Harris
  • , Gail P. Jarvik
  • , Anthony Philippakis
  • , Heidi L. Rehm
  • , Dan M. Roden
  • , Stephen N. Thibodeau
  •  & Scott Topper

Biobank, Mayo

  • Ashley L. Blegen
  • , Samantha J. Wirkus
  • , Victoria A. Wagner
  • , Jeffrey G. Meyer
  •  & Stephen N. Thibodeau

Genome Center: Baylor-Hopkins Clinical Genome Center

  • Donna M. Muzny
  • , Eric Venner
  • , Michelle Z. Mawhinney
  • , Sean M. L. Griffith
  • , Elvin Hsu
  • , Marcia K. Adams
  • , Kimberly Walker
  • , Jianhong Hu
  • , Harsha Doddapaneni
  • , Christie L. Kovar
  • , Mullai Murugan
  • , Shannon Dugan
  • , Ziad Khan
  •  & Richard A. Gibbs

Genome Center: Broad, Color, and Mass General Brigham Laboratory for Molecular Medicine

  • Niall J. Lennon
  • , Christina Austin-Tse
  • , Eric Banks
  • , Michael Gatzen
  • , Namrata Gupta
  • , Emma Henricks
  • , Katie Larsson
  • , Sheli McDonough
  • , Steven M. Harrison
  • , Christopher Kachulis
  • , Matthew S. Lebo
  • , Cynthia L. Neben
  • , Marcie Steeves
  • , Alicia Y. Zhou
  • , Scott Topper
  •  & Stacey Gabriel

Genome Center: University of Washington

  • Gail P. Jarvik
  • , Joshua D. Smith
  • , Christian D. Frazar
  • , Colleen P. Davis
  • , Karynne E. Patterson
  • , Marsha M. Wheeler
  • , Sean McGee
  • , Christina M. Lockwood
  • , Brian H. Shirts
  • , Colin C. Pritchard
  • , Mitzi L. Murray
  • , Valeria Vasta
  • , Dru Leistritz
  • , Matthew A. Richardson
  • , Jillian G. Buchan
  • , Aparna Radhakrishnan
  • , Niklas Krumm
  •  & Brenna W. Ehmen

Data and Research Center

  • Lee Lichtenstein
  • , Sophie Schwartz
  • , M. Morgan T. Aster
  • , Kristian Cibulskis
  • , Andrea Haessly
  • , Rebecca Asch
  • , Aurora Cremer
  • , Kylee Degatano
  • , Akum Shergill
  • , Laura D. Gauthier
  • , Samuel K. Lee
  • , Aaron Hatcher
  • , George B. Grant
  • , Genevieve R. Brandt
  • , Miguel Covarrubias
  • , Melissa Basford
  • , Alexander G. Bick
  • , Ashley Able
  • , Ashley E. Green
  • , Jennifer Zhang
  • , Henry R. Condon
  • , Yuanyuan Wang
  • , Moira K. Dillon
  • , C. H. Albach
  • , Wail Baalawi
  •  & Dan M. Roden

All of Us Research Demonstration Project Teams

  • Seung Hoan Choi
  • , Elisabeth A. Rosenthal

NIH All of Us Research Program Staff

  • Andrea H. Ramirez
  • , Sokny Lim
  • , Siddhartha Nambiar
  • , Bradley Ozenberger
  • , Anastasia L. Wise
  • , Chris Lunt
  • , Geoffrey S. Ginsburg
  •  & Joshua C. Denny

Contributions

The All of Us Biobank (Mayo Clinic) collected, stored and plated participant biospecimens. The All of Us Genome Centers (Baylor-Hopkins Clinical Genome Center; Broad, Color, and Mass General Brigham Laboratory for Molecular Medicine; and University of Washington School of Medicine) generated and QCed the whole-genomic data. The All of Us Data and Research Center (Vanderbilt University Medical Center, Broad Institute of MIT and Harvard, and Verily) generated the WGS joint call set, carried out quality assurance and QC analyses and developed the Researcher Workbench. All of Us Research Demonstration Project Teams contributed analyses. The other All of Us Genomics Investigators and NIH All of Us Research Program Staff provided crucial programmatic support. Members of the manuscript writing group (A.G.B., G.A.M., K.R.M., L.L., S.R., R.J.C. and A.M.) wrote the first draft of this manuscript, which was revised with contributions and feedback from all authors.

Corresponding author

Correspondence to Alexander G. Bick .

Ethics declarations

Competing interests.

D.M.M., G.A.M., E.V., K.W., J.H., H.D., C.L.K., M.M., S.D., Z.K., E. Boerwinkle and R.A.G. declare that Baylor Genetics is a Baylor College of Medicine affiliate that derives revenue from genetic testing. Eric Venner is affiliated with Codified Genomics, a provider of genetic interpretation. E.E.E. is a scientific advisory board member of Variant Bio, Inc. A.G.B. is a scientific advisory board member of TenSixteen Bio. The remaining authors declare no competing interests.

Peer review

Peer review information.

Nature thanks Timothy Frayling and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended data fig. 1 historic availability of ehr records in all of us v7 controlled tier curated data repository (n = 413,457)..

For better visibility, the plot shows growth starting in 2010.

Extended Data Fig. 2 Overview of the Genomic Data Curation Pipeline for WGS samples.

The Data and Research Center (DRC) performs additional single sample quality control (QC) on the data as it arrives from the Genome Centers. The variants from samples that pass this QC are loaded into the Genomic Variant Store (GVS), where we jointly call the variants and apply additional QC. We apply a joint call set QC process, which is stored with the call set. The entire joint call set is rendered as a Hail Variant Dataset (VDS), which can be accessed from the analysis notebooks in the Researcher Workbench. Subsections of the genome are extracted from the VDS and rendered in different formats with all participants. Auxiliary data can also be accessed through the Researcher Workbench. This includes variant functional annotations, joint call set QC results, predicted ancestry, and relatedness. Auxiliary data are derived from GVS (arrow not shown) and the VDS. The Cohort Builder directly queries GVS when researchers request genomic data for subsets of samples. Aligned reads, as cram files, are available in the Researcher Workbench (not shown). The graphics of the dish, gene and computer and the All of Us logo are reproduced with permission of the National Institutes of Health’s All of Us Research Program.

Extended Data Fig. 3 Proportion of allelic frequencies (AF), stratified by computed ancestry with over 10,000 participants.

Bar counts are not cumulative (eg, “pop AF < 0.01” does not include “pop AF < 0.001”).

Extended Data Fig. 4 Distribution of pathogenic, and likely pathogenic ClinVar variants.

Stratified by ancestry filtered to only those variants that are found in allele count (AC) < 40 individuals for 245,388 short read WGS samples.

Extended Data Fig. 5 Ancestry specific HLA-DQB1 ( rs9273363 ) locus associations in 231,442 unrelated individuals.

Phenome-wide (PheWAS) associations highlight ancestry specific consequences across ancestries.

Extended Data Fig. 6 Ancestry specific TCF7L2 ( rs7903146 ) locus associations in 231,442 unrelated individuals.

Phenome-wide (PheWAS) associations highlight diabetic consequences across ancestries.

Supplementary information

Supplementary information.

Supplementary Figs. 1–7, Tables 1–8 and Note.

Reporting Summary

Supplementary dataset 1.

Associations of ACKR1, HLA-DQB1 and TCF7L2 loci with all Phecodes stratified by genetic ancestry.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

The All of Us Research Program Genomics Investigators. Genomic data in the All of Us Research Program. Nature (2024). https://doi.org/10.1038/s41586-023-06957-x

Download citation

Received : 22 July 2022

Accepted : 08 December 2023

Published : 19 February 2024

DOI : https://doi.org/10.1038/s41586-023-06957-x

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

  • Explore articles by subject
  • Guide to authors
  • Editorial policies

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

database topics for research paper

database security Recently Published Documents

Total documents.

  • Latest Documents
  • Most Cited Documents
  • Contributed Authors
  • Related Sources
  • Related Keywords

NETWORK DATABASE SECURITY WITH INTELLECTUAL ACCESS SUPERVISION USING OUTLIER DETECTION TECHNIQUES

Comparison of performance rot13 and caesar cipher method for registration database of vessels berthed at p.t. samudera indonesia.

Database security is a very important aspect of an information system. A general information is onlyintended for certain groups. Therefore, it is very important for a company to prevent database leakage sothat the information contained in it does not fall to unauthorized people. Cryptographic technique is an alternative solution that can be used in database security. One way to maintain the security of the database is to use encryption techniques. The method used to secure the database is encryption using the ROTI3 and Caesar Cipher methods. Both of these methods have advantages in processing speed. For thisreason, the author will compare the use of the two algorithms above in terms of the encryption and decryption process time

A Novel Framework for Efficient Multiple Signature on Certificate with Database Security

Abstract PKI gives undeniable degree of safety by transferring the key pair framework among the clients. By constructing, a PKI we combine digital identities with the digital signatures, which give an end-to-end trust model. Basically, PKI is an attempt, which can simulate the real-world human analyzation of identity and reliability in a computerized fashion. In any case, the existing applications are centered on a tight trust model which makes them inadequate as an overall device for trust examination. After years of research, development and deployment, PKI still facing strong technical and organizational challenges such as attacks against Certificate Authorities (CA). CAs are the primitive component of PKIs which plays powerful role in the PKI model. CA must be diligent, creditable and legitimate. In any case, a technocrat who picks up control on a CA can use CA's certificate to issue bogus certificate and impersonate any site, such as - DigiNotar, GobalSign, Comodo and DigiCert Malaysia. In this paper we proposed an approach to reduce the damage of compromised CA/CA’s key by imposing Multiple Signatures (MS) after verifying/authenticating user’s information. One single compromised CA is not able to issue a certificate to any domain as multiple signatures are required. Private key and other perceptive information are stored in the form of object/blob. Without knowing the structure of class no one can access the object and object output stream. Proposed MS achieve better performance over existing MS schemes and control fraudulent certificate issuance with more database security. The proposed scheme also avoids MITM attack against CA who is issuing certificate to whom which is using the following parameters such as identity of Sender, Receiver, Timestamp and Aadhar number.

A guiding framework for enhancing database security in state-owned universities in Zimbabwe

Technique for evaluating the security of relational databases based on the enhanced clements–hoffman model.

Obtaining convincing evidence of database security, as the basic corporate resource, is extremely important. However, in order to verify the conclusions about the degree of security, it must be measured. To solve this challenge, the authors of the paper enhanced the Clements–Hoffman model, determined the integral security metric and, on this basis, developed a technique for evaluating the security of relational databases. The essence of improving the Clements–Hoffmann model is to expand it by including a set of object vulnerabilities. Vulnerability is considered as a separate objectively existing category. This makes it possible to evaluate both the likelihood of an unwanted incident and the database security as a whole more adequately. The technique for evaluating the main components of the security barriers and the database security as a whole, proposed by the authors, is based on the theory of fuzzy sets and risk. As an integral metric of database security, the reciprocal of the total residual risk is used, the constituent components of which are presented in the form of certain linguistic variables. In accordance with the developed technique, the authors presented the results of a quantitative evaluation of the effectiveness of the protection of databases built on the basis of the schema with the universal basis of relations and designed in accordance with the traditional technology of relational databases.

Hybrid Security Approach for Database Security using Diffusion based cryptography and Diffie-Hellman key exchange Algorithm

Application of network database security technology based on big data technology, database security in a dynamic it world.

Databases are vulnerable. Public statements by Target, Home Depot, and Anthem following their extremely advertised data breaches are each uniform and succinct on how their breaches unfolded: unauthorized access to those systems that ultimately led to the extraction of sensitive information. A comprehensive strategy to secure a database is over data security. Usually, security events will be related to the later action: illegitimate access to data confidentiality damage, injury to the integrity of knowledge, loss of data accessibility (Discover). Loss of privacy of data, creating them accessible to others without a right of access is not visible within the database and does not need changes deductible database. This paper addresses these events to confirm database security.

A Review of Database Security Concepts, Risks, and Problems

Currently, data production is as quick as possible; however, databases are collections of well-organized data that can be accessed, maintained, and updated quickly. Database systems are critical to your company because they convey data about sales transactions, product inventories, customer profiles, and marketing activities. To accomplish data manipulation and maintenance activities the Database Management System considered. Databases differ because their conclusions based on countless rules about what an invulnerable database constitutes. As a result, database protection seekers encounter difficulties in terms of a fantastic figure selection to maintain their database security. The main goal of this study is to identify the risk and how we can secure databases, encrypt sensitive data, modify system databases, and update database systems, as well as to evaluate some of the methods to handle these problems in security databases. However, because information plays such an important role in any organization, understanding the security risk and preventing it from occurring in any database system require a high level of knowledge. As a result, through this paper, all necessary information for any organization has been explained; in addition, also a new technological tool that plays an essential role in database security was discussed.

Database protection model based on security system with full overlap

Security is one of the most important characteristics of the quality of information systems in general and databases, as their main component, in particular. Therefore, the presence of an information protection system, as a complex of software, technical, cryptographic, organizational and other methods, means and measures that ensure the integrity, confidentiality, authenticity and availability of information in conditions of exposure to natural or artificial threats, is an integral feature of almost any modern information system and database. At the same time, in order to be able to verify the conclusions about the degree of security, it must be measured in some way. The paper considers a database security model based on a full overlap security model (a covered security system), which is traditionally considered the basis for a formal description of security systems. Thanks to expanding the Clements-Hoffman model by including a set of vulnerabilities (as a separately objectively existing category necessary to describe a weakness of an asset or control that can be exploited by one or more threats), which makes it possible to assess more adequately the likelihood of an unwanted incident (threat realization) in a two-factor model (in which one of the factors reflects the motivational component of the threat, and the second takes into account the existing vulnerabilities); a defined integral indicator of database security (as a value inverse to the total residual risk, the constituent components of which are represented in the form of the corresponding linguistic variables); the developed technique for assessing the main components of security barriers and the security of the database as a whole, based on the theory of fuzzy sets and risk, it becomes possible to use the developed model to conduct a quantitative assessment of the security of the analyzed database.

Export Citation Format

Share document.

  • Systematic review
  • Open access
  • Published: 19 February 2024

‘It depends’: what 86 systematic reviews tell us about what strategies to use to support the use of research in clinical practice

  • Annette Boaz   ORCID: orcid.org/0000-0003-0557-1294 1 ,
  • Juan Baeza 2 ,
  • Alec Fraser   ORCID: orcid.org/0000-0003-1121-1551 2 &
  • Erik Persson 3  

Implementation Science volume  19 , Article number:  15 ( 2024 ) Cite this article

990 Accesses

55 Altmetric

Metrics details

The gap between research findings and clinical practice is well documented and a range of strategies have been developed to support the implementation of research into clinical practice. The objective of this study was to update and extend two previous reviews of systematic reviews of strategies designed to implement research evidence into clinical practice.

We developed a comprehensive systematic literature search strategy based on the terms used in the previous reviews to identify studies that looked explicitly at interventions designed to turn research evidence into practice. The search was performed in June 2022 in four electronic databases: Medline, Embase, Cochrane and Epistemonikos. We searched from January 2010 up to June 2022 and applied no language restrictions. Two independent reviewers appraised the quality of included studies using a quality assessment checklist. To reduce the risk of bias, papers were excluded following discussion between all members of the team. Data were synthesised using descriptive and narrative techniques to identify themes and patterns linked to intervention strategies, targeted behaviours, study settings and study outcomes.

We identified 32 reviews conducted between 2010 and 2022. The reviews are mainly of multi-faceted interventions ( n  = 20) although there are reviews focusing on single strategies (ICT, educational, reminders, local opinion leaders, audit and feedback, social media and toolkits). The majority of reviews report strategies achieving small impacts (normally on processes of care). There is much less evidence that these strategies have shifted patient outcomes. Furthermore, a lot of nuance lies behind these headline findings, and this is increasingly commented upon in the reviews themselves.

Combined with the two previous reviews, 86 systematic reviews of strategies to increase the implementation of research into clinical practice have been identified. We need to shift the emphasis away from isolating individual and multi-faceted interventions to better understanding and building more situated, relational and organisational capability to support the use of research in clinical practice. This will involve drawing on a wider range of research perspectives (including social science) in primary studies and diversifying the types of synthesis undertaken to include approaches such as realist synthesis which facilitate exploration of the context in which strategies are employed.

Peer Review reports

Contribution to the literature

Considerable time and money is invested in implementing and evaluating strategies to increase the implementation of research into clinical practice.

The growing body of evidence is not providing the anticipated clear lessons to support improved implementation.

Instead what is needed is better understanding and building more situated, relational and organisational capability to support the use of research in clinical practice.

This would involve a more central role in implementation science for a wider range of perspectives, especially from the social, economic, political and behavioural sciences and for greater use of different types of synthesis, such as realist synthesis.

Introduction

The gap between research findings and clinical practice is well documented and a range of interventions has been developed to increase the implementation of research into clinical practice [ 1 , 2 ]. In recent years researchers have worked to improve the consistency in the ways in which these interventions (often called strategies) are described to support their evaluation. One notable development has been the emergence of Implementation Science as a field focusing explicitly on “the scientific study of methods to promote the systematic uptake of research findings and other evidence-based practices into routine practice” ([ 3 ] p. 1). The work of implementation science focuses on closing, or at least narrowing, the gap between research and practice. One contribution has been to map existing interventions, identifying 73 discreet strategies to support research implementation [ 4 ] which have been grouped into 9 clusters [ 5 ]. The authors note that they have not considered the evidence of effectiveness of the individual strategies and that a next step is to understand better which strategies perform best in which combinations and for what purposes [ 4 ]. Other authors have noted that there is also scope to learn more from other related fields of study such as policy implementation [ 6 ] and to draw on methods designed to support the evaluation of complex interventions [ 7 ].

The increase in activity designed to support the implementation of research into practice and improvements in reporting provided the impetus for an update of a review of systematic reviews of the effectiveness of interventions designed to support the use of research in clinical practice [ 8 ] which was itself an update of the review conducted by Grimshaw and colleagues in 2001. The 2001 review [ 9 ] identified 41 reviews considering a range of strategies including educational interventions, audit and feedback, computerised decision support to financial incentives and combined interventions. The authors concluded that all the interventions had the potential to promote the uptake of evidence in practice, although no one intervention seemed to be more effective than the others in all settings. They concluded that combined interventions were more likely to be effective than single interventions. The 2011 review identified a further 13 systematic reviews containing 313 discrete primary studies. Consistent with the previous review, four main strategy types were identified: audit and feedback; computerised decision support; opinion leaders; and multi-faceted interventions (MFIs). Nine of the reviews reported on MFIs. The review highlighted the small effects of single interventions such as audit and feedback, computerised decision support and opinion leaders. MFIs claimed an improvement in effectiveness over single interventions, although effect sizes remained small to moderate and this improvement in effectiveness relating to MFIs has been questioned in a subsequent review [ 10 ]. In updating the review, we anticipated a larger pool of reviews and an opportunity to consolidate learning from more recent systematic reviews of interventions.

This review updates and extends our previous review of systematic reviews of interventions designed to implement research evidence into clinical practice. To identify potentially relevant peer-reviewed research papers, we developed a comprehensive systematic literature search strategy based on the terms used in the Grimshaw et al. [ 9 ] and Boaz, Baeza and Fraser [ 8 ] overview articles. To ensure optimal retrieval, our search strategy was refined with support from an expert university librarian, considering the ongoing improvements in the development of search filters for systematic reviews since our first review [ 11 ]. We also wanted to include technology-related terms (e.g. apps, algorithms, machine learning, artificial intelligence) to find studies that explored interventions based on the use of technological innovations as mechanistic tools for increasing the use of evidence into practice (see Additional file 1 : Appendix A for full search strategy).

The search was performed in June 2022 in the following electronic databases: Medline, Embase, Cochrane and Epistemonikos. We searched for articles published since the 2011 review. We searched from January 2010 up to June 2022 and applied no language restrictions. Reference lists of relevant papers were also examined.

We uploaded the results using EPPI-Reviewer, a web-based tool that facilitated semi-automation of the screening process and removal of duplicate studies. We made particular use of a priority screening function to reduce screening workload and avoid ‘data deluge’ [ 12 ]. Through machine learning, one reviewer screened a smaller number of records ( n  = 1200) to train the software to predict whether a given record was more likely to be relevant or irrelevant, thus pulling the relevant studies towards the beginning of the screening process. This automation did not replace manual work but helped the reviewer to identify eligible studies more quickly. During the selection process, we included studies that looked explicitly at interventions designed to turn research evidence into practice. Studies were included if they met the following pre-determined inclusion criteria:

The study was a systematic review

Search terms were included

Focused on the implementation of research evidence into practice

The methodological quality of the included studies was assessed as part of the review

Study populations included healthcare providers and patients. The EPOC taxonomy [ 13 ] was used to categorise the strategies. The EPOC taxonomy has four domains: delivery arrangements, financial arrangements, governance arrangements and implementation strategies. The implementation strategies domain includes 20 strategies targeted at healthcare workers. Numerous EPOC strategies were assessed in the review including educational strategies, local opinion leaders, reminders, ICT-focused approaches and audit and feedback. Some strategies that did not fit easily within the EPOC categories were also included. These were social media strategies and toolkits, and multi-faceted interventions (MFIs) (see Table  2 ). Some systematic reviews included comparisons of different interventions while other reviews compared one type of intervention against a control group. Outcomes related to improvements in health care processes or patient well-being. Numerous individual study types (RCT, CCT, BA, ITS) were included within the systematic reviews.

We excluded papers that:

Focused on changing patient rather than provider behaviour

Had no demonstrable outcomes

Made unclear or no reference to research evidence

The last of these criteria was sometimes difficult to judge, and there was considerable discussion amongst the research team as to whether the link between research evidence and practice was sufficiently explicit in the interventions analysed. As we discussed in the previous review [ 8 ] in the field of healthcare, the principle of evidence-based practice is widely acknowledged and tools to change behaviour such as guidelines are often seen to be an implicit codification of evidence, despite the fact that this is not always the case.

Reviewers employed a two-stage process to select papers for inclusion. First, all titles and abstracts were screened by one reviewer to determine whether the study met the inclusion criteria. Two papers [ 14 , 15 ] were identified that fell just before the 2010 cut-off. As they were not identified in the searches for the first review [ 8 ] they were included and progressed to assessment. Each paper was rated as include, exclude or maybe. The full texts of 111 relevant papers were assessed independently by at least two authors. To reduce the risk of bias, papers were excluded following discussion between all members of the team. 32 papers met the inclusion criteria and proceeded to data extraction. The study selection procedure is documented in a PRISMA literature flow diagram (see Fig.  1 ). We were able to include French, Spanish and Portuguese papers in the selection reflecting the language skills in the study team, but none of the papers identified met the inclusion criteria. Other non- English language papers were excluded.

figure 1

PRISMA flow diagram. Source: authors

One reviewer extracted data on strategy type, number of included studies, local, target population, effectiveness and scope of impact from the included studies. Two reviewers then independently read each paper and noted key findings and broad themes of interest which were then discussed amongst the wider authorial team. Two independent reviewers appraised the quality of included studies using a Quality Assessment Checklist based on Oxman and Guyatt [ 16 ] and Francke et al. [ 17 ]. Each study was rated a quality score ranging from 1 (extensive flaws) to 7 (minimal flaws) (see Additional file 2 : Appendix B). All disagreements were resolved through discussion. Studies were not excluded in this updated overview based on methodological quality as we aimed to reflect the full extent of current research into this topic.

The extracted data were synthesised using descriptive and narrative techniques to identify themes and patterns in the data linked to intervention strategies, targeted behaviours, study settings and study outcomes.

Thirty-two studies were included in the systematic review. Table 1. provides a detailed overview of the included systematic reviews comprising reference, strategy type, quality score, number of included studies, local, target population, effectiveness and scope of impact (see Table  1. at the end of the manuscript). Overall, the quality of the studies was high. Twenty-three studies scored 7, six studies scored 6, one study scored 5, one study scored 4 and one study scored 3. The primary focus of the review was on reviews of effectiveness studies, but a small number of reviews did include data from a wider range of methods including qualitative studies which added to the analysis in the papers [ 18 , 19 , 20 , 21 ]. The majority of reviews report strategies achieving small impacts (normally on processes of care). There is much less evidence that these strategies have shifted patient outcomes. In this section, we discuss the different EPOC-defined implementation strategies in turn. Interestingly, we found only two ‘new’ approaches in this review that did not fit into the existing EPOC approaches. These are a review focused on the use of social media and a review considering toolkits. In addition to single interventions, we also discuss multi-faceted interventions. These were the most common intervention approach overall. A summary is provided in Table  2 .

Educational strategies

The overview identified three systematic reviews focusing on educational strategies. Grudniewicz et al. [ 22 ] explored the effectiveness of printed educational materials on primary care physician knowledge, behaviour and patient outcomes and concluded they were not effective in any of these aspects. Koota, Kääriäinen and Melender [ 23 ] focused on educational interventions promoting evidence-based practice among emergency room/accident and emergency nurses and found that interventions involving face-to-face contact led to significant or highly significant effects on patient benefits and emergency nurses’ knowledge, skills and behaviour. Interventions using written self-directed learning materials also led to significant improvements in nurses’ knowledge of evidence-based practice. Although the quality of the studies was high, the review primarily included small studies with low response rates, and many of them relied on self-assessed outcomes; consequently, the strength of the evidence for these outcomes is modest. Wu et al. [ 20 ] questioned if educational interventions aimed at nurses to support the implementation of evidence-based practice improve patient outcomes. Although based on evaluation projects and qualitative data, their results also suggest that positive changes on patient outcomes can be made following the implementation of specific evidence-based approaches (or projects). The differing positive outcomes for educational strategies aimed at nurses might indicate that the target audience is important.

Local opinion leaders

Flodgren et al. [ 24 ] was the only systemic review focusing solely on opinion leaders. The review found that local opinion leaders alone, or in combination with other interventions, can be effective in promoting evidence‐based practice, but this varies both within and between studies and the effect on patient outcomes is uncertain. The review found that, overall, any intervention involving opinion leaders probably improves healthcare professionals’ compliance with evidence-based practice but varies within and across studies. However, how opinion leaders had an impact could not be determined because of insufficient details were provided, illustrating that reporting specific details in published studies is important if diffusion of effective methods of increasing evidence-based practice is to be spread across a system. The usefulness of this review is questionable because it cannot provide evidence of what is an effective opinion leader, whether teams of opinion leaders or a single opinion leader are most effective, or the most effective methods used by opinion leaders.

Pantoja et al. [ 26 ] was the only systemic review focusing solely on manually generated reminders delivered on paper included in the overview. The review explored how these affected professional practice and patient outcomes. The review concluded that manually generated reminders delivered on paper as a single intervention probably led to small to moderate increases in adherence to clinical recommendations, and they could be used as a single quality improvement intervention. However, the authors indicated that this intervention would make little or no difference to patient outcomes. The authors state that such a low-tech intervention may be useful in low- and middle-income countries where paper records are more likely to be the norm.

ICT-focused approaches

The three ICT-focused reviews [ 14 , 27 , 28 ] showed mixed results. Jamal, McKenzie and Clark [ 14 ] explored the impact of health information technology on the quality of medical and health care. They examined the impact of electronic health record, computerised provider order-entry, or decision support system. This showed a positive improvement in adherence to evidence-based guidelines but not to patient outcomes. The number of studies included in the review was low and so a conclusive recommendation could not be reached based on this review. Similarly, Brown et al. [ 28 ] found that technology-enabled knowledge translation interventions may improve knowledge of health professionals, but all eight studies raised concerns of bias. The De Angelis et al. [ 27 ] review was more promising, reporting that ICT can be a good way of disseminating clinical practice guidelines but conclude that it is unclear which type of ICT method is the most effective.

Audit and feedback

Sykes, McAnuff and Kolehmainen [ 29 ] examined whether audit and feedback were effective in dementia care and concluded that it remains unclear which ingredients of audit and feedback are successful as the reviewed papers illustrated large variations in the effectiveness of interventions using audit and feedback.

Non-EPOC listed strategies: social media, toolkits

There were two new (non-EPOC listed) intervention types identified in this review compared to the 2011 review — fewer than anticipated. We categorised a third — ‘care bundles’ [ 36 ] as a multi-faceted intervention due to its description in practice and a fourth — ‘Technology Enhanced Knowledge Transfer’ [ 28 ] was classified as an ICT-focused approach. The first new strategy was identified in Bhatt et al.’s [ 30 ] systematic review of the use of social media for the dissemination of clinical practice guidelines. They reported that the use of social media resulted in a significant improvement in knowledge and compliance with evidence-based guidelines compared with more traditional methods. They noted that a wide selection of different healthcare professionals and patients engaged with this type of social media and its global reach may be significant for low- and middle-income countries. This review was also noteworthy for developing a simple stepwise method for using social media for the dissemination of clinical practice guidelines. However, it is debatable whether social media can be classified as an intervention or just a different way of delivering an intervention. For example, the review discussed involving opinion leaders and patient advocates through social media. However, this was a small review that included only five studies, so further research in this new area is needed. Yamada et al. [ 31 ] draw on 39 studies to explore the application of toolkits, 18 of which had toolkits embedded within larger KT interventions, and 21 of which evaluated toolkits as standalone interventions. The individual component strategies of the toolkits were highly variable though the authors suggest that they align most closely with educational strategies. The authors conclude that toolkits as either standalone strategies or as part of MFIs hold some promise for facilitating evidence use in practice but caution that the quality of many of the primary studies included is considered weak limiting these findings.

Multi-faceted interventions

The majority of the systematic reviews ( n  = 20) reported on more than one intervention type. Some of these systematic reviews focus exclusively on multi-faceted interventions, whilst others compare different single or combined interventions aimed at achieving similar outcomes in particular settings. While these two approaches are often described in a similar way, they are actually quite distinct from each other as the former report how multiple strategies may be strategically combined in pursuance of an agreed goal, whilst the latter report how different strategies may be incidentally used in sometimes contrasting settings in the pursuance of similar goals. Ariyo et al. [ 35 ] helpfully summarise five key elements often found in effective MFI strategies in LMICs — but which may also be transferrable to HICs. First, effective MFIs encourage a multi-disciplinary approach acknowledging the roles played by different professional groups to collectively incorporate evidence-informed practice. Second, they utilise leadership drawing on a wide set of clinical and non-clinical actors including managers and even government officials. Third, multiple types of educational practices are utilised — including input from patients as stakeholders in some cases. Fourth, protocols, checklists and bundles are used — most effectively when local ownership is encouraged. Finally, most MFIs included an emphasis on monitoring and evaluation [ 35 ]. In contrast, other studies offer little information about the nature of the different MFI components of included studies which makes it difficult to extrapolate much learning from them in relation to why or how MFIs might affect practice (e.g. [ 28 , 38 ]). Ultimately, context matters, which some review authors argue makes it difficult to say with real certainty whether single or MFI strategies are superior (e.g. [ 21 , 27 ]). Taking all the systematic reviews together we may conclude that MFIs appear to be more likely to generate positive results than single interventions (e.g. [ 34 , 45 ]) though other reviews should make us cautious (e.g. [ 32 , 43 ]).

While multi-faceted interventions still seem to be more effective than single-strategy interventions, there were important distinctions between how the results of reviews of MFIs are interpreted in this review as compared to the previous reviews [ 8 , 9 ], reflecting greater nuance and debate in the literature. This was particularly noticeable where the effectiveness of MFIs was compared to single strategies, reflecting developments widely discussed in previous studies [ 10 ]. We found that most systematic reviews are bounded by their clinical, professional, spatial, system, or setting criteria and often seek to draw out implications for the implementation of evidence in their areas of specific interest (such as nursing or acute care). Frequently this means combining all relevant studies to explore the respective foci of each systematic review. Therefore, most reviews we categorised as MFIs actually include highly variable numbers and combinations of intervention strategies and highly heterogeneous original study designs. This makes statistical analyses of the type used by Squires et al. [ 10 ] on the three reviews in their paper not possible. Further, it also makes extrapolating findings and commenting on broad themes complex and difficult. This may suggest that future research should shift its focus from merely examining ‘what works’ to ‘what works where and what works for whom’ — perhaps pointing to the value of realist approaches to these complex review topics [ 48 , 49 ] and other more theory-informed approaches [ 50 ].

Some reviews have a relatively small number of studies (i.e. fewer than 10) and the authors are often understandably reluctant to engage with wider debates about the implications of their findings. Other larger studies do engage in deeper discussions about internal comparisons of findings across included studies and also contextualise these in wider debates. Some of the most informative studies (e.g. [ 35 , 40 ]) move beyond EPOC categories and contextualise MFIs within wider systems thinking and implementation theory. This distinction between MFIs and single interventions can actually be very useful as it offers lessons about the contexts in which individual interventions might have bounded effectiveness (i.e. educational interventions for individual change). Taken as a whole, this may also then help in terms of how and when to conjoin single interventions into effective MFIs.

In the two previous reviews, a consistent finding was that MFIs were more effective than single interventions [ 8 , 9 ]. However, like Squires et al. [ 10 ] this overview is more equivocal on this important issue. There are four points which may help account for the differences in findings in this regard. Firstly, the diversity of the systematic reviews in terms of clinical topic or setting is an important factor. Secondly, there is heterogeneity of the studies within the included systematic reviews themselves. Thirdly, there is a lack of consistency with regards to the definition and strategies included within of MFIs. Finally, there are epistemological differences across the papers and the reviews. This means that the results that are presented depend on the methods used to measure, report, and synthesise them. For instance, some reviews highlight that education strategies can be useful to improve provider understanding — but without wider organisational or system-level change, they may struggle to deliver sustained transformation [ 19 , 44 ].

It is also worth highlighting the importance of the theory of change underlying the different interventions. Where authors of the systematic reviews draw on theory, there is space to discuss/explain findings. We note a distinction between theoretical and atheoretical systematic review discussion sections. Atheoretical reviews tend to present acontextual findings (for instance, one study found very positive results for one intervention, and this gets highlighted in the abstract) whilst theoretically informed reviews attempt to contextualise and explain patterns within the included studies. Theory-informed systematic reviews seem more likely to offer more profound and useful insights (see [ 19 , 35 , 40 , 43 , 45 ]). We find that the most insightful systematic reviews of MFIs engage in theoretical generalisation — they attempt to go beyond the data of individual studies and discuss the wider implications of the findings of the studies within their reviews drawing on implementation theory. At the same time, they highlight the active role of context and the wider relational and system-wide issues linked to implementation. It is these types of investigations that can help providers further develop evidence-based practice.

This overview has identified a small, but insightful set of papers that interrogate and help theorise why, how, for whom, and in which circumstances it might be the case that MFIs are superior (see [ 19 , 35 , 40 ] once more). At the level of this overview — and in most of the systematic reviews included — it appears to be the case that MFIs struggle with the question of attribution. In addition, there are other important elements that are often unmeasured, or unreported (e.g. costs of the intervention — see [ 40 ]). Finally, the stronger systematic reviews [ 19 , 35 , 40 , 43 , 45 ] engage with systems issues, human agency and context [ 18 ] in a way that was not evident in the systematic reviews identified in the previous reviews [ 8 , 9 ]. The earlier reviews lacked any theory of change that might explain why MFIs might be more effective than single ones — whereas now some systematic reviews do this, which enables them to conclude that sometimes single interventions can still be more effective.

As Nilsen et al. ([ 6 ] p. 7) note ‘Study findings concerning the effectiveness of various approaches are continuously synthesized and assembled in systematic reviews’. We may have gone as far as we can in understanding the implementation of evidence through systematic reviews of single and multi-faceted interventions and the next step would be to conduct more research exploring the complex and situated nature of evidence used in clinical practice and by particular professional groups. This would further build on the nuanced discussion and conclusion sections in a subset of the papers we reviewed. This might also support the field to move away from isolating individual implementation strategies [ 6 ] to explore the complex processes involving a range of actors with differing capacities [ 51 ] working in diverse organisational cultures. Taxonomies of implementation strategies do not fully account for the complex process of implementation, which involves a range of different actors with different capacities and skills across multiple system levels. There is plenty of work to build on, particularly in the social sciences, which currently sits at the margins of debates about evidence implementation (see for example, Normalisation Process Theory [ 52 ]).

There are several changes that we have identified in this overview of systematic reviews in comparison to the review we published in 2011 [ 8 ]. A consistent and welcome finding is that the overall quality of the systematic reviews themselves appears to have improved between the two reviews, although this is not reflected upon in the papers. This is exhibited through better, clearer reporting mechanisms in relation to the mechanics of the reviews, alongside a greater attention to, and deeper description of, how potential biases in included papers are discussed. Additionally, there is an increased, but still limited, inclusion of original studies conducted in low- and middle-income countries as opposed to just high-income countries. Importantly, we found that many of these systematic reviews are attuned to, and comment upon the contextual distinctions of pursuing evidence-informed interventions in health care settings in different economic settings. Furthermore, systematic reviews included in this updated article cover a wider set of clinical specialities (both within and beyond hospital settings) and have a focus on a wider set of healthcare professions — discussing both similarities, differences and inter-professional challenges faced therein, compared to the earlier reviews. These wider ranges of studies highlight that a particular intervention or group of interventions may work well for one professional group but be ineffective for another. This diversity of study settings allows us to consider the important role context (in its many forms) plays on implementing evidence into practice. Examining the complex and varied context of health care will help us address what Nilsen et al. ([ 6 ] p. 1) described as, ‘society’s health problems [that] require research-based knowledge acted on by healthcare practitioners together with implementation of political measures from governmental agencies’. This will help us shift implementation science to move, ‘beyond a success or failure perspective towards improved analysis of variables that could explain the impact of the implementation process’ ([ 6 ] p. 2).

This review brings together 32 papers considering individual and multi-faceted interventions designed to support the use of evidence in clinical practice. The majority of reviews report strategies achieving small impacts (normally on processes of care). There is much less evidence that these strategies have shifted patient outcomes. Combined with the two previous reviews, 86 systematic reviews of strategies to increase the implementation of research into clinical practice have been conducted. As a whole, this substantial body of knowledge struggles to tell us more about the use of individual and MFIs than: ‘it depends’. To really move forwards in addressing the gap between research evidence and practice, we may need to shift the emphasis away from isolating individual and multi-faceted interventions to better understanding and building more situated, relational and organisational capability to support the use of research in clinical practice. This will involve drawing on a wider range of perspectives, especially from the social, economic, political and behavioural sciences in primary studies and diversifying the types of synthesis undertaken to include approaches such as realist synthesis which facilitate exploration of the context in which strategies are employed. Harvey et al. [ 53 ] suggest that when context is likely to be critical to implementation success there are a range of primary research approaches (participatory research, realist evaluation, developmental evaluation, ethnography, quality/ rapid cycle improvement) that are likely to be appropriate and insightful. While these approaches often form part of implementation studies in the form of process evaluations, they are usually relatively small scale in relation to implementation research as a whole. As a result, the findings often do not make it into the subsequent systematic reviews. This review provides further evidence that we need to bring qualitative approaches in from the periphery to play a central role in many implementation studies and subsequent evidence syntheses. It would be helpful for systematic reviews, at the very least, to include more detail about the interventions and their implementation in terms of how and why they worked.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Before and after study

Controlled clinical trial

Effective Practice and Organisation of Care

High-income countries

Information and Communications Technology

Interrupted time series

Knowledge translation

Low- and middle-income countries

Randomised controlled trial

Grol R, Grimshaw J. From best evidence to best practice: effective implementation of change in patients’ care. Lancet. 2003;362:1225–30. https://doi.org/10.1016/S0140-6736(03)14546-1 .

Article   PubMed   Google Scholar  

Green LA, Seifert CM. Translation of research into practice: why we can’t “just do it.” J Am Board Fam Pract. 2005;18:541–5. https://doi.org/10.3122/jabfm.18.6.541 .

Eccles MP, Mittman BS. Welcome to Implementation Science. Implement Sci. 2006;1:1–3. https://doi.org/10.1186/1748-5908-1-1 .

Article   PubMed Central   Google Scholar  

Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10:2–14. https://doi.org/10.1186/s13012-015-0209-1 .

Article   Google Scholar  

Waltz TJ, Powell BJ, Matthieu MM, Damschroder LJ, et al. Use of concept mapping to characterize relationships among implementation strategies and assess their feasibility and importance: results from the Expert Recommendations for Implementing Change (ERIC) study. Implement Sci. 2015;10:1–8. https://doi.org/10.1186/s13012-015-0295-0 .

Nilsen P, Ståhl C, Roback K, et al. Never the twain shall meet? - a comparison of implementation science and policy implementation research. Implementation Sci. 2013;8:2–12. https://doi.org/10.1186/1748-5908-8-63 .

Rycroft-Malone J, Seers K, Eldh AC, et al. A realist process evaluation within the Facilitating Implementation of Research Evidence (FIRE) cluster randomised controlled international trial: an exemplar. Implementation Sci. 2018;13:1–15. https://doi.org/10.1186/s13012-018-0811-0 .

Boaz A, Baeza J, Fraser A, European Implementation Score Collaborative Group (EIS). Effective implementation of research into practice: an overview of systematic reviews of the health literature. BMC Res Notes. 2011;4:212. https://doi.org/10.1186/1756-0500-4-212 .

Article   PubMed   PubMed Central   Google Scholar  

Grimshaw JM, Shirran L, Thomas R, Mowatt G, Fraser C, Bero L, et al. Changing provider behavior – an overview of systematic reviews of interventions. Med Care. 2001;39 8Suppl 2:II2–45.

Google Scholar  

Squires JE, Sullivan K, Eccles MP, et al. Are multifaceted interventions more effective than single-component interventions in changing health-care professionals’ behaviours? An overview of systematic reviews. Implement Sci. 2014;9:1–22. https://doi.org/10.1186/s13012-014-0152-6 .

Salvador-Oliván JA, Marco-Cuenca G, Arquero-Avilés R. Development of an efficient search filter to retrieve systematic reviews from PubMed. J Med Libr Assoc. 2021;109:561–74. https://doi.org/10.5195/jmla.2021.1223 .

Thomas JM. Diffusion of innovation in systematic review methodology: why is study selection not yet assisted by automation? OA Evid Based Med. 2013;1:1–6.

Effective Practice and Organisation of Care (EPOC). The EPOC taxonomy of health systems interventions. EPOC Resources for review authors. Oslo: Norwegian Knowledge Centre for the Health Services; 2016. epoc.cochrane.org/epoc-taxonomy . Accessed 9 Oct 2023.

Jamal A, McKenzie K, Clark M. The impact of health information technology on the quality of medical and health care: a systematic review. Health Inf Manag. 2009;38:26–37. https://doi.org/10.1177/183335830903800305 .

Menon A, Korner-Bitensky N, Kastner M, et al. Strategies for rehabilitation professionals to move evidence-based knowledge into practice: a systematic review. J Rehabil Med. 2009;41:1024–32. https://doi.org/10.2340/16501977-0451 .

Oxman AD, Guyatt GH. Validation of an index of the quality of review articles. J Clin Epidemiol. 1991;44:1271–8. https://doi.org/10.1016/0895-4356(91)90160-b .

Article   CAS   PubMed   Google Scholar  

Francke AL, Smit MC, de Veer AJ, et al. Factors influencing the implementation of clinical guidelines for health care professionals: a systematic meta-review. BMC Med Inform Decis Mak. 2008;8:1–11. https://doi.org/10.1186/1472-6947-8-38 .

Jones CA, Roop SC, Pohar SL, et al. Translating knowledge in rehabilitation: systematic review. Phys Ther. 2015;95:663–77. https://doi.org/10.2522/ptj.20130512 .

Scott D, Albrecht L, O’Leary K, Ball GDC, et al. Systematic review of knowledge translation strategies in the allied health professions. Implement Sci. 2012;7:1–17. https://doi.org/10.1186/1748-5908-7-70 .

Wu Y, Brettle A, Zhou C, Ou J, et al. Do educational interventions aimed at nurses to support the implementation of evidence-based practice improve patient outcomes? A systematic review. Nurse Educ Today. 2018;70:109–14. https://doi.org/10.1016/j.nedt.2018.08.026 .

Yost J, Ganann R, Thompson D, Aloweni F, et al. The effectiveness of knowledge translation interventions for promoting evidence-informed decision-making among nurses in tertiary care: a systematic review and meta-analysis. Implement Sci. 2015;10:1–15. https://doi.org/10.1186/s13012-015-0286-1 .

Grudniewicz A, Kealy R, Rodseth RN, Hamid J, et al. What is the effectiveness of printed educational materials on primary care physician knowledge, behaviour, and patient outcomes: a systematic review and meta-analyses. Implement Sci. 2015;10:2–12. https://doi.org/10.1186/s13012-015-0347-5 .

Koota E, Kääriäinen M, Melender HL. Educational interventions promoting evidence-based practice among emergency nurses: a systematic review. Int Emerg Nurs. 2018;41:51–8. https://doi.org/10.1016/j.ienj.2018.06.004 .

Flodgren G, O’Brien MA, Parmelli E, et al. Local opinion leaders: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2019. https://doi.org/10.1002/14651858.CD000125.pub5 .

Arditi C, Rège-Walther M, Durieux P, et al. Computer-generated reminders delivered on paper to healthcare professionals: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2017. https://doi.org/10.1002/14651858.CD001175.pub4 .

Pantoja T, Grimshaw JM, Colomer N, et al. Manually-generated reminders delivered on paper: effects on professional practice and patient outcomes. Cochrane Database Syst Rev. 2019. https://doi.org/10.1002/14651858.CD001174.pub4 .

De Angelis G, Davies B, King J, McEwan J, et al. Information and communication technologies for the dissemination of clinical practice guidelines to health professionals: a systematic review. JMIR Med Educ. 2016;2:e16. https://doi.org/10.2196/mededu.6288 .

Brown A, Barnes C, Byaruhanga J, McLaughlin M, et al. Effectiveness of technology-enabled knowledge translation strategies in improving the use of research in public health: systematic review. J Med Internet Res. 2020;22:e17274. https://doi.org/10.2196/17274 .

Sykes MJ, McAnuff J, Kolehmainen N. When is audit and feedback effective in dementia care? A systematic review. Int J Nurs Stud. 2018;79:27–35. https://doi.org/10.1016/j.ijnurstu.2017.10.013 .

Bhatt NR, Czarniecki SW, Borgmann H, et al. A systematic review of the use of social media for dissemination of clinical practice guidelines. Eur Urol Focus. 2021;7:1195–204. https://doi.org/10.1016/j.euf.2020.10.008 .

Yamada J, Shorkey A, Barwick M, Widger K, et al. The effectiveness of toolkits as knowledge translation strategies for integrating evidence into clinical care: a systematic review. BMJ Open. 2015;5:e006808. https://doi.org/10.1136/bmjopen-2014-006808 .

Afari-Asiedu S, Abdulai MA, Tostmann A, et al. Interventions to improve dispensing of antibiotics at the community level in low and middle income countries: a systematic review. J Glob Antimicrob Resist. 2022;29:259–74. https://doi.org/10.1016/j.jgar.2022.03.009 .

Boonacker CW, Hoes AW, Dikhoff MJ, Schilder AG, et al. Interventions in health care professionals to improve treatment in children with upper respiratory tract infections. Int J Pediatr Otorhinolaryngol. 2010;74:1113–21. https://doi.org/10.1016/j.ijporl.2010.07.008 .

Al Zoubi FM, Menon A, Mayo NE, et al. The effectiveness of interventions designed to increase the uptake of clinical practice guidelines and best practices among musculoskeletal professionals: a systematic review. BMC Health Serv Res. 2018;18:2–11. https://doi.org/10.1186/s12913-018-3253-0 .

Ariyo P, Zayed B, Riese V, Anton B, et al. Implementation strategies to reduce surgical site infections: a systematic review. Infect Control Hosp Epidemiol. 2019;3:287–300. https://doi.org/10.1017/ice.2018.355 .

Borgert MJ, Goossens A, Dongelmans DA. What are effective strategies for the implementation of care bundles on ICUs: a systematic review. Implement Sci. 2015;10:1–11. https://doi.org/10.1186/s13012-015-0306-1 .

Cahill LS, Carey LM, Lannin NA, et al. Implementation interventions to promote the uptake of evidence-based practices in stroke rehabilitation. Cochrane Database Syst Rev. 2020. https://doi.org/10.1002/14651858.CD012575.pub2 .

Pedersen ER, Rubenstein L, Kandrack R, Danz M, et al. Elusive search for effective provider interventions: a systematic review of provider interventions to increase adherence to evidence-based treatment for depression. Implement Sci. 2018;13:1–30. https://doi.org/10.1186/s13012-018-0788-8 .

Jenkins HJ, Hancock MJ, French SD, Maher CG, et al. Effectiveness of interventions designed to reduce the use of imaging for low-back pain: a systematic review. CMAJ. 2015;187:401–8. https://doi.org/10.1503/cmaj.141183 .

Bennett S, Laver K, MacAndrew M, Beattie E, et al. Implementation of evidence-based, non-pharmacological interventions addressing behavior and psychological symptoms of dementia: a systematic review focused on implementation strategies. Int Psychogeriatr. 2021;33:947–75. https://doi.org/10.1017/S1041610220001702 .

Noonan VK, Wolfe DL, Thorogood NP, et al. Knowledge translation and implementation in spinal cord injury: a systematic review. Spinal Cord. 2014;52:578–87. https://doi.org/10.1038/sc.2014.62 .

Albrecht L, Archibald M, Snelgrove-Clarke E, et al. Systematic review of knowledge translation strategies to promote research uptake in child health settings. J Pediatr Nurs. 2016;31:235–54. https://doi.org/10.1016/j.pedn.2015.12.002 .

Campbell A, Louie-Poon S, Slater L, et al. Knowledge translation strategies used by healthcare professionals in child health settings: an updated systematic review. J Pediatr Nurs. 2019;47:114–20. https://doi.org/10.1016/j.pedn.2019.04.026 .

Bird ML, Miller T, Connell LA, et al. Moving stroke rehabilitation evidence into practice: a systematic review of randomized controlled trials. Clin Rehabil. 2019;33:1586–95. https://doi.org/10.1177/0269215519847253 .

Goorts K, Dizon J, Milanese S. The effectiveness of implementation strategies for promoting evidence informed interventions in allied healthcare: a systematic review. BMC Health Serv Res. 2021;21:1–11. https://doi.org/10.1186/s12913-021-06190-0 .

Zadro JR, O’Keeffe M, Allison JL, Lembke KA, et al. Effectiveness of implementation strategies to improve adherence of physical therapist treatment choices to clinical practice guidelines for musculoskeletal conditions: systematic review. Phys Ther. 2020;100:1516–41. https://doi.org/10.1093/ptj/pzaa101 .

Van der Veer SN, Jager KJ, Nache AM, et al. Translating knowledge on best practice into improving quality of RRT care: a systematic review of implementation strategies. Kidney Int. 2011;80:1021–34. https://doi.org/10.1038/ki.2011.222 .

Pawson R, Greenhalgh T, Harvey G, et al. Realist review–a new method of systematic review designed for complex policy interventions. J Health Serv Res Policy. 2005;10Suppl 1:21–34. https://doi.org/10.1258/1355819054308530 .

Rycroft-Malone J, McCormack B, Hutchinson AM, et al. Realist synthesis: illustrating the method for implementation research. Implementation Sci. 2012;7:1–10. https://doi.org/10.1186/1748-5908-7-33 .

Johnson MJ, May CR. Promoting professional behaviour change in healthcare: what interventions work, and why? A theory-led overview of systematic reviews. BMJ Open. 2015;5:e008592. https://doi.org/10.1136/bmjopen-2015-008592 .

Metz A, Jensen T, Farley A, Boaz A, et al. Is implementation research out of step with implementation practice? Pathways to effective implementation support over the last decade. Implement Res Pract. 2022;3:1–11. https://doi.org/10.1177/26334895221105585 .

May CR, Finch TL, Cornford J, Exley C, et al. Integrating telecare for chronic disease management in the community: What needs to be done? BMC Health Serv Res. 2011;11:1–11. https://doi.org/10.1186/1472-6963-11-131 .

Harvey G, Rycroft-Malone J, Seers K, Wilson P, et al. Connecting the science and practice of implementation – applying the lens of context to inform study design in implementation research. Front Health Serv. 2023;3:1–15. https://doi.org/10.3389/frhs.2023.1162762 .

Download references

Acknowledgements

The authors would like to thank Professor Kathryn Oliver for her support in the planning the review, Professor Steve Hanney for reading and commenting on the final manuscript and the staff at LSHTM library for their support in planning and conducting the literature search.

This study was supported by LSHTM’s Research England QR strategic priorities funding allocation and the National Institute for Health and Care Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust. Grant number NIHR200152. The views expressed are those of the author(s) and not necessarily those of the NIHR, the Department of Health and Social Care or Research England.

Author information

Authors and affiliations.

Health and Social Care Workforce Research Unit, The Policy Institute, King’s College London, Virginia Woolf Building, 22 Kingsway, London, WC2B 6LE, UK

Annette Boaz

King’s Business School, King’s College London, 30 Aldwych, London, WC2B 4BG, UK

Juan Baeza & Alec Fraser

Federal University of Santa Catarina (UFSC), Campus Universitário Reitor João Davi Ferreira Lima, Florianópolis, SC, 88.040-900, Brazil

Erik Persson

You can also search for this author in PubMed   Google Scholar

Contributions

AB led the conceptual development and structure of the manuscript. EP conducted the searches and data extraction. All authors contributed to screening and quality appraisal. EP and AF wrote the first draft of the methods section. AB, JB and AF performed result synthesis and contributed to the analyses. AB wrote the first draft of the manuscript and incorporated feedback and revisions from all other authors. All authors revised and approved the final manuscript.

Corresponding author

Correspondence to Annette Boaz .

Ethics declarations

Ethics approval and consent to participate.

Not applicable.

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: appendix a., additional file 2: appendix b., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Boaz, A., Baeza, J., Fraser, A. et al. ‘It depends’: what 86 systematic reviews tell us about what strategies to use to support the use of research in clinical practice. Implementation Sci 19 , 15 (2024). https://doi.org/10.1186/s13012-024-01337-z

Download citation

Received : 01 November 2023

Accepted : 05 January 2024

Published : 19 February 2024

DOI : https://doi.org/10.1186/s13012-024-01337-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Implementation
  • Interventions
  • Clinical practice
  • Research evidence
  • Multi-faceted

Implementation Science

ISSN: 1748-5908

  • Submission enquiries: Access here and click Contact Us
  • General enquiries: [email protected]

database topics for research paper

Data, Privacy Laws and Firm Production: Evidence from the GDPR

By regulating how firms collect, store, and use data, privacy laws may change the role of data in production and alter firm demand for information technology inputs. We study how firms respond to privacy laws in the context of the EU’s General Data Protection Regulation (GDPR) by using seven years of data from a large global cloud-computing provider. Our difference-in-difference estimates indicate that, in response to the GDPR, EU firms decreased data storage by 26% and data processing by 15% relative to comparable US firms, becoming less “data-intensive.” To estimate the costs of the GDPR for firms, we propose and estimate a production function where data and computation serve as inputs to the production of “information." We find that data and computation are strong complements in production and that firm responses are consistent with the GDPR, representing a 20% increase in the cost of data on average. Variation in the firm-level effects of the GDPR and industry-level exposure to data, however, drives significant heterogeneity in our estimates of the impact of the GDPR on production costs.

We thank Guy Aridor, James Brand, Alessandro Bonatti, Peter Cihon, Jean Pierre Dubé, Joe Doyle, Ben Edelman, Liran Einav, Sara Ellison, Maryam Farboodi, Samuel Goldberg, Yizhou Jin, Garrett Johnson, Gaston Illanes, Markus Mobius, Devesh Raval, Dominik Rehse, Tobias Salz, Bryan Stuart, Taheya Tarannum, Joel Waldfogel, and Mike Whinston for helpful comments, and Abbie Natkin, Taegan Mullane, Doris Pan, Ryan Perry, Bea Rivera for excellent research assistance. We are also grateful to Han Choi for copyediting assistance. We gratefully acknowledge the support of the National Institute on Aging, Grant Number T32- AG000186 (Li) and the National Science Foundation Graduate Research Fellowship under Grant No 214106 (Li). The views expressed herein are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of Chicago, the Federal Reserve System, or the National Bureau of Economic Research.

Mert Demirer is a former paid postdoctoral researcher at Microsoft (a firm active in the cloud market, which this paper studies).

Diego Jiménez Hernández is a former paid postdoctoral researcher at Microsoft.

Dean Li is a former intern at Microsoft.

Sida Peng is a paid employee and minority equity holder at Microsoft.

MARC RIS BibTeΧ

Download Citation Data

  • data appendix

Mentioned in the News

More from nber.

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .

15th Annual Feldstein Lecture, Mario Draghi, "The Next Flight of the Bumblebee: The Path to Common Fiscal Policy in the Eurozone cover slide

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

  • Machine learning
  • Social justice
  • Black holes
  • Classes and programs

Departments

  • Aeronautics and Astronautics
  • Brain and Cognitive Sciences
  • Architecture
  • Political Science
  • Mechanical Engineering

Centers, Labs, & Programs

  • Abdul Latif Jameel Poverty Action Lab (J-PAL)
  • Picower Institute for Learning and Memory
  • Lincoln Laboratory
  • School of Architecture + Planning
  • School of Engineering
  • School of Humanities, Arts, and Social Sciences
  • Sloan School of Management
  • School of Science
  • MIT Schwarzman College of Computing

MIT researchers remotely map crops, field by field

Press contact :, media download.

Four Google Street View photos show rice, cassava, sugarcane, and maize fields.

*Terms of Use:

Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commons Attribution Non-Commercial No Derivatives license . You may not alter the images provided, other than to crop them to size. A credit line must be used when reproducing images; if one is not provided below, credit the images to "MIT."

Four Google Street View photos show rice, cassava, sugarcane, and maize fields.

Previous image Next image

Crop maps help scientists and policymakers track global food supplies and estimate how they might shift with climate change and growing populations. But getting accurate maps of the types of crops that are grown from farm to farm often requires on-the-ground surveys that only a handful of countries have the resources to maintain.

Now, MIT engineers have developed a method to quickly and accurately label and map crop types without requiring in-person assessments of every single farm. The team’s method uses a combination of Google Street View images, machine learning, and satellite data to automatically determine the crops grown throughout a region, from one fraction of an acre to the next. 

The researchers used the technique to automatically generate the first nationwide crop map of Thailand — a smallholder country where small, independent farms make up the predominant form of agriculture. The team created a border-to-border map of Thailand’s four major crops — rice, cassava, sugarcane, and maize — and determined which of the four types was grown, at every 10 meters, and without gaps, across the entire country. The resulting map achieved an accuracy of 93 percent, which the researchers say is comparable to on-the-ground mapping efforts in high-income, big-farm countries.

The team is applying their mapping technique to other countries such as India, where small farms sustain most of the population but the type of crops grown from farm to farm has historically been poorly recorded.

“It’s a longstanding gap in knowledge about what is grown around the world,” says Sherrie Wang, the d’Arbeloff Career Development Assistant Professor in MIT’s Department of Mechanical Engineering, and the Institute for Data, Systems, and Society (IDSS). Wang, who is one of the new shared faculty hires between the MIT Schwarzman College of Computing and departments across MIT says, “The final goal is to understand agricultural outcomes like yield, and how to farm more sustainably. One of the key preliminary steps is to map what is even being grown — the more granularly you can map, the more questions you can answer.”

Wang, along with MIT graduate student Jordi Laguarta Soler and Thomas Friedel of the agtech company PEAT GmbH, will present a paper detailing their mapping method later this month at the AAAI Conference on Artificial Intelligence.

Ground truth

Smallholder farms are often run by a single family or farmer, who subsist on the crops and livestock that they raise. It’s estimated that smallholder farms support two-thirds of the world’s rural population and produce 80 percent of the world’s food. Keeping tabs on what is grown and where is essential to tracking and forecasting food supplies around the world. But the majority of these small farms are in low to middle-income countries, where few resources are devoted to keeping track of individual farms’ crop types and yields.

Crop mapping efforts are mainly carried out in high-income regions such as the United States and Europe, where government agricultural agencies oversee crop surveys and send assessors to farms to label crops from field to field. These “ground truth” labels are then fed into machine-learning models that make connections between the ground labels of actual crops and satellite signals of the same fields. They then label and map wider swaths of farmland that assessors don’t cover but that satellites automatically do.

“What’s lacking in low- and middle-income countries is this ground label that we can associate with satellite signals,” Laguarta Soler says. “Getting these ground truths to train a model in the first place has been limited in most of the world.”

The team realized that, while many developing countries do not have the resources to maintain crop surveys, they could potentially use another source of ground data: roadside imagery, captured by services such as Google Street View and Mapillary, which send cars throughout a region to take continuous 360-degree images with dashcams and rooftop cameras.

In recent years, such services have been able to access low- and middle-income countries. While the goal of these services is not specifically to capture images of crops, the MIT team saw that they could search the roadside images to identify crops.

Cropped image

In their new study, the researchers worked with Google Street View (GSV) images taken throughout Thailand — a country that the service has recently imaged fairly thoroughly, and which consists predominantly of smallholder farms.

Starting with over 200,000 GSV images randomly sampled across Thailand, the team filtered out images that depicted buildings, trees, and general vegetation. About 81,000 images were crop-related. They set aside 2,000 of these, which they sent to an agronomist, who determined and labeled each crop type by eye. They then trained a convolutional neural network to automatically generate crop labels for the other 79,000 images, using various training methods, including iNaturalist — a web-based crowdsourced  biodiversity database, and GPT-4V, a “multimodal large language model” that enables a user to input an image and ask the model to identify what the image is depicting. For each of the 81,000 images, the model generated a label of one of four crops that the image was likely depicting — rice, maize, sugarcane, or cassava.

The researchers then paired each labeled image with the corresponding satellite data taken of the same location throughout a single growing season. These satellite data include measurements across multiple wavelengths, such as a location’s greenness and its reflectivity (which can be a sign of water). 

“Each type of crop has a certain signature across these different bands, which changes throughout a growing season,” Laguarta Soler notes.

The team trained a second model to make associations between a location’s satellite data and its corresponding crop label. They then used this model to process satellite data taken of the rest of the country, where crop labels were not generated or available. From the associations that the model learned, it then assigned crop labels across Thailand, generating a country-wide map of crop types, at a resolution of 10 square meters.

This first-of-its-kind crop map included locations corresponding to the 2,000 GSV images that the researchers originally set aside, that were labeled by arborists. These human-labeled images were used to validate the map’s labels, and when the team looked to see whether the map’s labels matched the expert, “gold standard” labels, it did so 93 percent of the time.

“In the U.S., we’re also looking at over 90 percent accuracy, whereas with previous work in India, we’ve only seen 75 percent because ground labels are limited,” Wang says. “Now we can create these labels in a cheap and automated way.”

The researchers are moving to map crops across India, where roadside images via Google Street View and other services have recently become available.

“There are over 150 million smallholder farmers in India,” Wang says. “India is covered in agriculture, almost wall-to-wall farms, but very small farms, and historically it’s been very difficult to create maps of India because there are very sparse ground labels.”

The team is working to generate crop maps in India, which could be used to inform policies having to do with assessing and bolstering yields, as global temperatures and populations rise.

“What would be interesting would be to create these maps over time,” Wang says. “Then you could start to see trends, and we can try to relate those things to anything like changes in climate and policies.”

Share this news article on:

Related links.

  • Sherrie Wang
  • Institute for Data, Systems, and Society
  • Department of Mechanical Engineering

Related Topics

  • Agriculture
  • Computer modeling
  • Computer vision
  • Developing countries
  • Environment
  • Mechanical engineering

Related Articles

Collage of eleven new faculty member's headshots, arranged in two rows

School of Engineering welcomes new faculty

Landscape of a peat bog under a blue sky. In the foreground, several islands of peat are surrounded by water.

Satellite-based method measures carbon in peat bogs

Three women, researchers from the GEAR Lab, stand on a dirt road in a field in Jordan holding laptops.

Smart irrigation technology covers “more crop per drop”

The village has about 20 huts that form a large a ring around an empty, brown, circular area. Lots of trees are around the village.

Ancient Amazonians intentionally created fertile “dark earth”

Aerial view of an abandoned agricultural terrace in France

3 Questions: Can disused croplands help mitigate climate change?

Previous item Next item

More MIT News

Rendering shows several layers, including a metallic block on bottom. Above this block are lattices of layered atoms. Above these lattices, a twist of energy has a two-sided arrow, with the top part emphasized.

Researchers harness 2D magnetic materials for energy-efficient computing

Read full story →

Photo of the facade of MIT’s Building 10, which features columns and the MIT Dome

Thirty-five outstanding MIT students selected as Burchard Scholars for 2024

Photo of Albert Almada smiling

What can super-healing species teach us about regeneration?

Three small purple spheres are on left, and one large purple sphere is on right. A bending stream of energy is between them. Graphene layers are in the background.

Electrons become fractions of themselves in graphene, study finds

Mi-Eun Kim, seated, plays a piano while Holden Mui, standing behind her, watches. An open laptop with a visual representation of data rests atop the piano.

Play it again, Spirio

Stylized collage of bar graphs, wavy lines and a sphere with coordinates.

Automated method helps researchers quantify uncertainty in their predictions

  • More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

  • Map (opens in new window)
  • Events (opens in new window)
  • People (opens in new window)
  • Careers (opens in new window)
  • Accessibility
  • Social Media Hub
  • MIT on Facebook
  • MIT on YouTube
  • MIT on Instagram

IMAGES

  1. 250+ Best Research Paper Topics Ideas that Inspire

    database topics for research paper

  2. Reasearch Ideas for High School Students

    database topics for research paper

  3. 🏷️ The best research paper topics. 200 Easy Research Paper Topics for

    database topics for research paper

  4. Writing a Databases Research Paper

    database topics for research paper

  5. 😍 Database for research papers. Research paper database. 2019-01-28

    database topics for research paper

  6. Writing a Databases Research Paper

    database topics for research paper

VIDEO

  1. Free database to search articles for your thesis

  2. Learning the basics of research. Session 1:Selecting a Topic

  3. Online Workshop on Research Paper Writing & Publishing Day 2

  4. Research Methodology

  5. Write a paper on A database management system (DBMS)

  6. "How write a Research Paper Introduction?

COMMENTS

  1. 10 Current Database Research Topic Ideas in 2024

    Analyzing information on prevalence, risk factors, and interventions is a popular research topic in DBMS these days. Effective data management is essential for ensuring that this information is collected, stored, and analyzed in a way that is useful and actionable.

  2. 19024 PDFs

    Jan 2024 Yerik Afrianto Singgalen Jan 2024 Anita Fira Waluyo Jan 2024 Explore the latest full-text research PDFs, articles, conference papers, preprints and more on DATABASE MANAGEMENT...

  3. 67 Data Management Essay Topics & Database Research Topics

    🏆 Best Database Research Topics Database Management Systems' Major Capabilities Relational Database Management Systems in Business Data Assets Management of LuLu Hypermarkets System Big Data Opportunities in Green Supply Chain Management Information Technology-Based Data Management in Retail Object-Oriented and Database Management Systems Tradeoffs

  4. Database Search

    What is Database Search? Harvard Library licenses hundreds of online databases, giving you access to academic and news articles, books, journals, primary sources, streaming media, and much more. The contents of these databases are only partially included in HOLLIS. To make sure you're really seeing everything, you need to search in multiple places.

  5. Research Area: DBMS

    Topics Declarative languages and runtime systems Design and implementation of declarative programming languages with applications to distributed systems, networking, machine learning, metadata management, and interactive visualization; design of query interface for applications. Scalable data analysis and query processing

  6. PDF Database management system performance comparisons: A systematic

    A database is a collection of interrelated data, typically stored according to a data model. Typically, the database is used by one or several software applications via a DBMS. Collectively, the database, the DBMS, and the software application are referred to as a database system [31, p.7][17, p.65]. The separation

  7. How to Find Sources

    Research databases. You can search for scholarly sources online using databases and search engines like Google Scholar. These provide a range of search functions that can help you to find the most relevant sources. If you are searching for a specific article or book, include the title or the author's name. Alternatively, if you're just ...

  8. GitHub Pages

    If you were excited by the topics in 4111, this graduate level course in database systems research will be a deep dive into classic and modern database systems research. Topics will range from classic database system design, modern optimizations in single-machine and multi-machine settings, data cleaning and quality, and application-oriented ...

  9. Databases

    Databases can be used to store research data, for example in protein databases and genetic databases, and they organise data into standard formats so that information can readily be...

  10. 11407 PDFs

    Explore the latest full-text research PDFs, articles, conference papers, preprints and more on DATABASE TECHNOLOGIES. Find methods information, sources, references or conduct a literature review ...

  11. Advances in database systems education: Methods, tools, curricula, and

    Whereas, the graduate course is more theoretical and includes topics related to DB architecture, transactions, concurrency, reliability, distribution, parallelism, replication, query optimization, along with some specialized classes.

  12. (PDF) Database System: Concepts and Design

    Such related data are called a database. A database system is an integrated collection of related files, along with details of the interpretation of the data contained therein. Basically, the ...

  13. 214 Big Data Research Topics: Interesting Ideas To Try

    214 Big Data Research Topics: Interesting Ideas To Try » 214 Best Big Data Research Topics for Your Thesis Paper 214 Best Big Data Research Topics for Your Thesis Paper Finding an ideal big data research topic can take you a long time. Big data, IoT, and robotics have evolved.

  14. 40 List of DBMS Project Topics and Ideas

    40 List of DBMS Project Topics and Ideas June 5, 2022 inettutor.com 40 List of DBMS Project Topics and Ideas Introduction A Capstone project is the last project of an IT degree program. It is made up of one or more research projects in which students create prototypes, services, and/or products.

  15. 9.3 Basic Guidelines for Research in Academic Databases

    4.3 Topic Sentences; 4.4 Supporting Evidence; 4.5 Explaining Evidence; 4.6 Breaking, Combining, or Beginning New Paragraphs ... Many of your professors will expect you to use academic research databases for research papers in college. Getting used to doing research in an academic database can be challenging, especially if you have only used ...

  16. 113 Great Research Paper Topics

    #1: It's Something You're Interested In A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject.

  17. List of academic databases and search engines

    This article contains a representative list of notable databases and search engines useful in an academic setting for finding and accessing articles in academic journals, institutional repositories, archives, or other collections of scientific and other articles.

  18. The best academic research databases [Update 2024]

    1. Scopus 2. Web of Science 3. PubMed 4. ERIC 5. IEEE Xplore 6. ScienceDirect 7. Directory of Open Access Journals (DOAJ) 8. JSTOR Frequently Asked Questions about academic research databases Related Articles Whether you are writing a thesis, dissertation, or research paper it is a key task to survey prior literature and research findings.

  19. Using Databases to Find a Research Paper Topic

    This database can also be accessed from the A-Z Databases list under "O." In summary, finding a topic for your research paper or project can be made easier by reading background material. The four resources mentioned above can help you find those background articles that point you to an interesting and compelling topic. But don't ...

  20. 500 Good Research Paper Topics

    500 Good Research Paper Topics September 7, 2022 | In Preparing | By Emily Bonus Material: Essential essay checklist Writing a research paper for a class and not sure how to start? One of the most important steps to creating a great paper is finding a good topic!

  21. 300+ Good Research Paper Topics

    1. What are Good Topics for a Research Paper? 2. Research Paper Topics for Your Academic Level 3. Research Paper Topics for Science & Technology 4. Research Paper Topics For Social Sciences 5. Research Paper Topics for Humanities 6. Research Paper Topics on Economics 7. Research Paper Topics Related to Marketing 8. Best Research Paper Topics 2023

  22. Genomic data in the All of Us Research Program

    A study describes the release of clinical-grade whole-genome sequence data for 245,388 diverse participants by the All of Us Research Program and characterizes the properties of the dataset.

  23. database security Latest Research Papers

    One way to maintain the security of the database is to use encryption techniques. The method used to secure the database is encryption using the ROTI3 and Caesar Cipher methods. Both of these methods have advantages in processing speed. For thisreason, the author will compare the use of the two algorithms above in terms of the encryption and ...

  24. 23 Research Databases for Professional and Academic Use

    1. Scopus Scopus is a database that features literature for a large variety of disciplines. It offers some services for free, but full access to the database requires a subscription. A unique feature of Scopus is that it also ranks journals and authors by their h-index, which tracks how many users cite the specific resource.

  25. 'It depends': what 86 systematic reviews tell us about what strategies

    The gap between research findings and clinical practice is well documented and a range of interventions has been developed to increase the implementation of research into clinical practice [1, 2].In recent years researchers have worked to improve the consistency in the ways in which these interventions (often called strategies) are described to support their evaluation.

  26. Data, Privacy Laws and Firm Production: Evidence from the GDPR

    We study how firms respond to privacy laws in the context of the EU's General Data Protection Regulation (GDPR) by using seven years of data from a large global cloud-computing provider. Our difference-in-difference estimates indicate that, in response to the GDPR, EU firms decreased data storage by 26% and data processing by 15% relative to ...

  27. Leveraging Big Data to Understand Women's Mobility in Buenos Aires

    This paper explores this topic in the context of the Buenos Aires Metropolitan Area, aiming to identify policy relevant differences between the mobility of women and men. It does so by leveraging mobile phone—based data, combined with existing household travel survey data and an original large-scale interception survey implemented in late ...

  28. MIT researchers remotely map crops, field by field

    They then trained a convolutional neural network to automatically generate crop labels for the other 79,000 images, using various training methods, including iNaturalist — a web-based crowdsourced biodiversity database, and GPT-4V, a "multimodal large language model" that enables a user to input an image and ask the model to identify what ...