how to do related studies in research

• Translation

How to refer to other studies or literature in the different sections of a research paper

By charlesworth author services.

• Charlesworth Author Services
• 07 October, 2021

There are many articles which discuss how you can include and discuss existing studies and research in the literature review section of a paper. However, in addition to the literature review , there are many other opportunities to discuss or engage with prior studies in your research. This article offers guidance on how to include other studies or literature in different sections in a research paper.

Engaging with literature in the Introduction

Prior studies are often mentioned in the Introduction , generally as high-level summaries without much detail. Although some people may choose not to use existing literature or research to motivate a study, this is not an uncommon practice. Researchers sometimes rely on prior studies to emphasise the importance of the current study – for example, in challenging a standing argument or addressing an outstanding gap . Prior studies are also often discussed to build the foundation of the arguments of the research paper in question. 

Working with previous studies in the Methodology

It is also common practice to refer to prior literature in the Methodology. You may refer to prior studies as you design the study, collect and/or select data and perform the analysis. If this is the case, it is important to explain clearly why you are using and drawing from previous studies and how these are relevant to your own research paper. 

It is also possible to refer to prior studies to highlight the different methodological choices you have taken in your research. For example, there may be a comparison of the data sources, the sample or subject selections. Or, you might offer a comparison in the decisions made for different parameters, constructs, factors, model selection preferences and so on. Highlighting these differences can help you to clearly present new perspectives and why your study provides value to the field.

If you are offering a comparison between your current and previous studies, try to avoid solely comparing and contrasting, or simply stating what you have performed. What is more important is to explain why you have made these different decisions so that readers can understand the rationale behind your methodological decisions and your project design .

Referring to the literature in the Discussion and Conclusion

It is always a good idea to refer to prior studies and existing literature in the Discussion or Conclusion sections. This is a good time to reiterate the arguments, research questions/hypotheses and objectives that you introduced in the earlier sections of the paper and to discuss your results and findings .

Integrating other relevant literature into your Discussion serves two key purposes . First, it outlines what has already been achieved in prior studies. Second, you can explain how your study builds on this existing work to advance the knowledge in the field . 

Sometimes, through this discussion, you can also demonstrate why or how your findings are the same as or different from prior studies. 

Three common mistakes to avoid

When forging connections between prior studies and your own research paper, it is important to be aware of three common mistakes that authors make.

• Some researchers sometimes focus too much on the existing literature , so that their research paper does not, ultimately, seem to provide many new insights. 
• Because of the way authors might present and discuss prior studies in the Introduction, readers may become distracted or be led to raise more questions that are not relevant to the present research paper. [ Tip : In this and the above instances, it is advisable that you ensure your discussion of the literature is relevant at all times to the specific issues that you are discussing in each section and does not overshadow the main idea(s) in the research paper.]
• Although you can critique prior studies to highlight the unique approach or key message of your study, it is a good practice to avoid subjective assessments, so as not to introduce any personal biases into your discussion of either the literature or your own research. 

In conclusion

Remember that engagement with the literature serves primarily to set the scene and contextualise your own research . It should provide enough information for your reader to understand the relevance and significance of your study, but not take over the main focus of the paper.

Read next (fifth/final) in series: Difference between a literature review and a critical review

Read previous (third) in series: Deciding what to include and exclude as you begin to write your literature review

Charlesworth Author Services , a trusted brand supporting the world’s leading academic publishers, institutions and authors since 1928. 

To know more about our services, visit:  Our Services

Visit our new Researcher Education Portal  that offers articles and webinars covering all aspects of your research to publication journey! And sign up for our newsletter on the Portal to stay updated on all essential researcher knowledge and information!

Register now:  Researcher Education Portal

Maximise your publication success with Charlesworth Author Services .

Share with your colleagues

Scientific Editing Services

Sign up – stay updated.

We use cookies to offer you a personalized experience. By continuing to use this website, you consent to the use of cookies in accordance with our Cookie Policy.

Educational resources and simple solutions for your research journey

How to Write Review of Related Literature (RRL) in Research

A review of related literature (a.k.a RRL in research) is a comprehensive review of the existing literature pertaining to a specific topic or research question. An effective review provides the reader with an organized analysis and synthesis of the existing knowledge about a subject. With the increasing amount of new information being disseminated every day, conducting a review of related literature is becoming more difficult and the purpose of review of related literature is clearer than ever.  

All new knowledge is necessarily based on previously known information, and every new scientific study must be conducted and reported in the context of previous studies. This makes a review of related literature essential for research, and although it may be tedious work at times , most researchers will complete many such reviews of varying depths during their career. So, why exactly is a review of related literature important?    

Table of Contents

Why a review of related literature in research is important  

Before thinking how to do reviews of related literature , it is necessary to understand its importance. Although the purpose of a review of related literature varies depending on the discipline and how it will be used, its importance is never in question. Here are some ways in which a review can be crucial.  

• Identify gaps in the knowledge – This is the primary purpose of a review of related literature (often called RRL in research ). To create new knowledge, you must first determine what knowledge may be missing. This also helps to identify the scope of your study.  
• Avoid duplication of research efforts – Not only will a review of related literature indicate gaps in the existing research, but it will also lead you away from duplicating research that has already been done and thus save precious resources.  
• Provide an overview of disparate and interdisciplinary research areas – Researchers cannot possibly know everything related to their disciplines. Therefore, it is very helpful to have access to a review of related literature already written and published.  
• Highlight researcher’s familiarity with their topic 1  – A strong review of related literature in a study strengthens readers’ confidence in that study and that researcher.

Tips on how to write a review of related literature in research

Given that you will probably need to produce a number of these at some point, here are a few general tips on how to write an effective review of related literature 2 .

• Define your topic, audience, and purpose: You will be spending a lot of time with this review, so choose a topic that is interesting to you. While deciding what to write in a review of related literature , think about who you expect to read the review – researchers in your discipline, other scientists, the general public – and tailor the language to the audience. Also, think about the purpose of your review of related literature .  
• Conduct a comprehensive literature search: While writing your review of related literature , emphasize more recent works but don’t forget to include some older publications as well. Cast a wide net, as you may find some interesting and relevant literature in unexpected databases or library corners. Don’t forget to search for recent conference papers.
• Review the identified articles and take notes: It is a good idea to take notes in a way such that individual items in your notes can be moved around when you organize them. For example, index cards are great tools for this. Write each individual idea on a separate card along with the source. The cards can then be easily grouped and organized.  
• Determine how to organize your review: A review of related literature should not be merely a listing of descriptions. It should be organized by some criterion, such as chronologically or thematically.  
• Be critical and objective: Don’t just report the findings of other studies in your review of related literature . Challenge the methodology, find errors in the analysis, question the conclusions. Use what you find to improve your research. However, do not insert your opinions into the review of related literature. Remain objective and open-minded.  
• Structure your review logically: Guide the reader through the information. The structure will depend on the function of the review of related literature. Creating an outline prior to writing the RRL in research is a good way to ensure the presented information flows well.  

As you read more extensively in your discipline, you will notice that the review of related literature appears in various forms in different places. For example, when you read an article about an experimental study, you will typically see a literature review or a RRL in research , in the introduction that includes brief descriptions of similar studies. In longer research studies and dissertations, especially in the social sciences, the review of related literature will typically be a separate chapter and include more information on methodologies and theory building. In addition, stand-alone review articles will be published that are extremely useful to researchers.  

The review of relevant literature or often abbreviated as, RRL in research , is an important communication tool that can be used in many forms for many purposes. It is a tool that all researchers should befriend.  

• University of North Carolina at Chapel Hill Writing Center. Literature Reviews.  https://writingcenter.unc.edu/tips-and-tools/literature-reviews/  [Accessed September 8, 2022]
• Pautasso M. Ten simple rules for writing a literature review. PLoS Comput Biol. 2013, 9. doi: 10.1371/journal.pcbi.1003149.

Q:  Is research complete without a review of related literature?

A research project is usually considered incomplete without a proper review of related literature. The review of related literature is a crucial component of any research project as it provides context for the research question, identifies gaps in existing literature, and ensures novelty by avoiding duplication. It also helps inform research design and supports arguments, highlights the significance of a study, and demonstrates your knowledge an expertise.

Q: What is difference between RRL and RRS?

The key difference between an RRL and an RRS lies in their focus and scope. An RRL or review of related literature examines a broad range of literature, including theoretical frameworks, concepts, and empirical studies, to establish the context and significance of the research topic. On the other hand, an RRS or review of research studies specifically focuses on analyzing and summarizing previous research studies within a specific research domain to gain insights into methodologies, findings, and gaps in the existing body of knowledge. While there may be some overlap between the two, they serve distinct purposes and cover different aspects of the research process.

Q: Does review of related literature improve accuracy and validity of research?

Yes, a comprehensive review of related literature (RRL) plays a vital role in improving the accuracy and validity of research. It helps authors gain a deeper understanding and offers different perspectives on the research topic. RRL can help you identify research gaps, dictate the selection of appropriate research methodologies, enhance theoretical frameworks, avoid biases and errors, and even provide support for research design and interpretation. By building upon and critically engaging with existing related literature, researchers can ensure their work is rigorous, reliable, and contributes meaningfully to their field of study.

R Discovery is a literature search and research reading platform that accelerates your research discovery journey by keeping you updated on the latest, most relevant scholarly content. With 250M+ research articles sourced from trusted aggregators like CrossRef, Unpaywall, PubMed, PubMed Central, Open Alex and top publishing houses like Springer Nature, JAMA, IOP, Taylor & Francis, NEJM, BMJ, Karger, SAGE, Emerald Publishing and more, R Discovery puts a world of research at your fingertips.  

Try R Discovery Prime FREE for 1 week or upgrade at just US$72 a year to access premium features that let you listen to research on the go, read in your language, collaborate with peers, auto sync with reference managers, and much more. Choose a simpler, smarter way to find and read research – Download the app and start your free 7-day trial today !  

Related Posts

What is Research Impact: Types and Tips for Academics

Research in Shorts: R Discovery’s New Feature Helps Academics Assess Relevant Papers in 2mins 

Review of Related Literature: Format, Example, & How to Make RRL

A review of related literature is a separate paper or a part of an article that collects and synthesizes discussion on a topic. Its purpose is to show the current state of research on the issue and highlight gaps in existing knowledge. A literature review can be included in a research paper or scholarly article, typically following the introduction and before the research methods section.

This article will clarify the definition, significance, and structure of a review of related literature. You’ll also learn how to organize your literature review and discover ideas for an RRL in different subjects.

🔤 What Is RRL?

• ❗ Significance of Literature Review
• 🔎 How to Search for Literature
• 🧩 Literature Review Structure
• 📋 Format of RRL — APA, MLA, & Others
• ✍️ How to Write an RRL
• 📚 Examples of RRL

🔗 References

A review of related literature (RRL) is a part of the research report that examines significant studies, theories, and concepts published in scholarly sources on a particular topic. An RRL includes 3 main components:

• A short overview and critique of the previous research.
• Similarities and differences between past studies and the current one.
• An explanation of the theoretical frameworks underpinning the research.

❗ Significance of Review of Related Literature

Although the goal of a review of related literature differs depending on the discipline and its intended use, its significance cannot be overstated. Here are some examples of how a review might be beneficial:

• It helps determine knowledge gaps .
• It saves from duplicating research that has already been conducted.
• It provides an overview of various research areas within the discipline.
• It demonstrates the researcher’s familiarity with the topic.

🔎 How to Perform a Literature Search

Including a description of your search strategy in the literature review section can significantly increase your grade. You can search sources with the following steps:

🧩 Literature Review Structure Example

The majority of literature reviews follow a standard introduction-body-conclusion structure. Let’s look at the RRL structure in detail.

Introduction of Review of Related Literature: Sample

An introduction should clarify the study topic and the depth of the information to be delivered. It should also explain the types of sources used. If your lit. review is part of a larger research proposal or project, you can combine its introductory paragraph with the introduction of your paper.

Here is a sample introduction to an RRL about cyberbullying:

Bullying has troubled people since the beginning of time. However, with modern technological advancements, especially social media, bullying has evolved into cyberbullying. As a result, nowadays, teenagers and adults cannot flee their bullies, which makes them feel lonely and helpless. This literature review will examine recent studies on cyberbullying.

Sample Review of Related Literature Thesis

A thesis statement should include the central idea of your literature review and the primary supporting elements you discovered in the literature. Thesis statements are typically put at the end of the introductory paragraph.

Look at a sample thesis of a review of related literature:

This literature review shows that scholars have recently covered the issues of bullies’ motivation, the impact of bullying on victims and aggressors, common cyberbullying techniques, and victims’ coping strategies. However, there is still no agreement on the best practices to address cyberbullying.

Literature Review Body Paragraph Example

The main body of a literature review should provide an overview of the existing research on the issue. Body paragraphs should not just summarize each source but analyze them. You can organize your paragraphs with these 3 elements:

• Claim . Start with a topic sentence linked to your literature review purpose.
• Evidence . Cite relevant information from your chosen sources.
• Discussion . Explain how the cited data supports your claim.

Here’s a literature review body paragraph example:

Scholars have examined the link between the aggressor and the victim. Beran et al. (2007) state that students bullied online often become cyberbullies themselves. Faucher et al. (2014) confirm this with their findings: they discovered that male and female students began engaging in cyberbullying after being subject to bullying. Hence, one can conclude that being a victim of bullying increases one’s likelihood of becoming a cyberbully.

Review of Related Literature: Conclusion

A conclusion presents a general consensus on the topic. Depending on your literature review purpose, it might include the following:

• Introduction to further research . If you write a literature review as part of a larger research project, you can present your research question in your conclusion .
• Overview of theories . You can summarize critical theories and concepts to help your reader understand the topic better.
• Discussion of the gap . If you identified a research gap in the reviewed literature, your conclusion could explain why that gap is significant.

Check out a conclusion example that discusses a research gap:

There is extensive research into bullies’ motivation, the consequences of bullying for victims and aggressors, strategies for bullying, and coping with it. Yet, scholars still have not reached a consensus on what to consider the best practices to combat cyberbullying. This question is of great importance because of the significant adverse effects of cyberbullying on victims and bullies.

📋 Format of RRL — APA, MLA, & Others

In this section, we will discuss how to format an RRL according to the most common citation styles: APA, Chicago, MLA, and Harvard.

Writing a literature review using the APA7 style requires the following text formatting:

• When using APA in-text citations , include the author’s last name and the year of publication in parentheses.
• For direct quotations , you must also add the page number. If you use sources without page numbers, such as websites or e-books, include a paragraph number instead.
• When referring to the author’s name in a sentence , you do not need to repeat it at the end of the sentence. Instead, include the year of publication inside the parentheses after their name.
• The reference list should be included at the end of your literature review. It is always alphabetized by the last name of the author (from A to Z), and the lines are indented one-half inch from the left margin of your paper. Do not forget to invert authors’ names (the last name should come first) and include the full titles of journals instead of their abbreviations. If you use an online source, add its URL.

The RRL format in the Chicago style is as follows:

• Author-date . You place your citations in brackets within the text, indicating the name of the author and the year of publication.
• Notes and bibliography . You place your citations in numbered footnotes or endnotes to connect the citation back to the source in the bibliography.
• The reference list, or bibliography , in Chicago style, is at the end of a literature review. The sources are arranged alphabetically and single-spaced. Each bibliography entry begins with the author’s name and the source’s title, followed by publication information, such as the city of publication, the publisher, and the year of publication.

Writing a literature review using the MLA style requires the following text formatting:

• In the MLA format, you can cite a source in the text by indicating the author’s last name and the page number in parentheses at the end of the citation. If the cited information takes several pages, you need to include all the page numbers.
• The reference list in MLA style is titled “ Works Cited .” In this section, all sources used in the paper should be listed in alphabetical order. Each entry should contain the author, title of the source, title of the journal or a larger volume, other contributors, version, number, publisher, and publication date.

The Harvard style requires you to use the following text formatting for your RRL:

• In-text citations in the Harvard style include the author’s last name and the year of publication. If you are using a direct quote in your literature review, you need to add the page number as well.
• Arrange your list of references alphabetically. Each entry should contain the author’s last name, their initials, the year of publication, the title of the source, and other publication information, like the journal title and issue number or the publisher.

✍️ How to Write Review of Related Literature – Sample

Literature reviews can be organized in many ways depending on what you want to achieve with them. In this section, we will look at 3 examples of how you can write your RRL.

Thematic Literature Review

A thematic literature review is arranged around central themes or issues discussed in the sources. If you have identified some recurring themes in the literature, you can divide your RRL into sections that address various aspects of the topic. For example, if you examine studies on e-learning, you can distinguish such themes as the cost-effectiveness of online learning, the technologies used, and its effectiveness compared to traditional education.

Chronological Literature Review

A chronological literature review is a way to track the development of the topic over time. If you use this method, avoid merely listing and summarizing sources in chronological order. Instead, try to analyze the trends, turning moments, and critical debates that have shaped the field’s path. Also, you can give your interpretation of how and why specific advances occurred.

Methodological Literature Review

A methodological literature review differs from the preceding ones in that it usually doesn’t focus on the sources’ content. Instead, it is concerned with the research methods . So, if your references come from several disciplines or fields employing various research techniques, you can compare the findings and conclusions of different methodologies, for instance:

• empirical vs. theoretical studies;
• qualitative vs. quantitative research.

📚 Examples of Review of Related Literature and Studies

We have prepared a short example of RRL on climate change for you to see how everything works in practice!

Climate change is one of the most important issues nowadays. Based on a variety of facts, it is now clearer than ever that humans are altering the Earth's climate. The atmosphere and oceans have warmed, causing sea level rise, a significant loss of Arctic ice, and other climate-related changes. This literature review provides a thorough summary of research on climate change, focusing on climate change fingerprints and evidence of human influence on the Earth's climate system.

Physical Mechanisms and Evidence of Human Influence

Scientists are convinced that climate change is directly influenced by the emission of greenhouse gases. They have carefully analyzed various climate data and evidence, concluding that the majority of the observed global warming over the past 50 years cannot be explained by natural factors alone. Instead, there is compelling evidence pointing to a significant contribution of human activities, primarily the emission of greenhouse gases (Walker, 2014). For example, based on simple physics calculations, doubled carbon dioxide concentration in the atmosphere can lead to a global temperature increase of approximately 1 degree Celsius. (Elderfield, 2022). In order to determine the human influence on climate, scientists still have to analyze a lot of natural changes that affect temperature, precipitation, and other components of climate on timeframes ranging from days to decades and beyond.

Fingerprinting Climate Change

Fingerprinting climate change is a useful tool to identify the causes of global warming because different factors leave unique marks on climate records. This is evident when scientists look beyond overall temperature changes and examine how warming is distributed geographically and over time (Watson, 2022). By investigating these climate patterns, scientists can obtain a more complex understanding of the connections between natural climate variability and climate variability caused by human activity.

Modeling Climate Change and Feedback

To accurately predict the consequences of feedback mechanisms, the rate of warming, and regional climate change, scientists can employ sophisticated mathematical models of the atmosphere, ocean, land, and ice (the cryosphere). These models are grounded in well-established physical laws and incorporate the latest scientific understanding of climate-related processes (Shuckburgh, 2013). Although different climate models produce slightly varying projections for future warming, they all will agree that feedback mechanisms play a significant role in amplifying the initial warming caused by greenhouse gas emissions. (Meehl, 2019).

In conclusion, the literature on global warming indicates that there are well-understood physical processes that link variations in greenhouse gas concentrations to climate change. In addition, it covers the scientific proof that the rates of these gases in the atmosphere have increased and continue to rise fast. According to the sources, the majority of this recent change is almost definitely caused by greenhouse gas emissions produced by human activities. Citizens and governments can alter their energy production methods and consumption patterns to reduce greenhouse gas emissions and, thus, the magnitude of climate change. By acting now, society can prevent the worst consequences of climate change and build a more resilient and sustainable future for generations to come.

Have you ever struggled with finding the topic for an RRL in different subjects? Read the following paragraphs to get some ideas!

Nursing Literature Review Example

Many topics in the nursing field require research. For example, you can write a review of literature related to dengue fever . Give a general overview of dengue virus infections, including its clinical symptoms, diagnosis, prevention, and therapy.

Another good idea is to review related literature and studies about teenage pregnancy . This review can describe the effectiveness of specific programs for adolescent mothers and their children and summarize recommendations for preventing early pregnancy.

📝 Check out some more valuable examples below:

• Hospital Readmissions: Literature Review .
• Literature Review: Lower Sepsis Mortality Rates .
• Breast Cancer: Literature Review .
• Sexually Transmitted Diseases: Literature Review .
• PICO for Pressure Ulcers: Literature Review .
• COVID-19 Spread Prevention: Literature Review .
• Chronic Obstructive Pulmonary Disease: Literature Review .
• Hypertension Treatment Adherence: Literature Review .
• Neonatal Sepsis Prevention: Literature Review .
• Healthcare-Associated Infections: Literature Review .
• Understaffing in Nursing: Literature Review .

Psychology Literature Review Example

If you look for an RRL topic in psychology , you can write a review of related literature about stress . Summarize scientific evidence about stress stages, side effects, types, or reduction strategies. Or you can write a review of related literature about computer game addiction . In this case, you may concentrate on the neural mechanisms underlying the internet gaming disorder, compare it to other addictions, or evaluate treatment strategies.

A review of related literature about cyberbullying is another interesting option. You can highlight the impact of cyberbullying on undergraduate students’ academic, social, and emotional development.

📝 Look at the examples that we have prepared for you to come up with some more ideas:

• Mindfulness in Counseling: A Literature Review .
• Team-Building Across Cultures: Literature Review .
• Anxiety and Decision Making: Literature Review .
• Literature Review on Depression .
• Literature Review on Narcissism .
• Effects of Depression Among Adolescents .
• Causes and Effects of Anxiety in Children .

Literature Review — Sociology Example

Sociological research poses critical questions about social structures and phenomena. For example, you can write a review of related literature about child labor , exploring cultural beliefs and social norms that normalize the exploitation of children. Or you can create a review of related literature about social media . It can investigate the impact of social media on relationships between adolescents or the role of social networks on immigrants’ acculturation .

📝 You can find some more ideas below!

• Single Mothers’ Experiences of Relationships with Their Adolescent Sons .
• Teachers and Students’ Gender-Based Interactions .
• Gender Identity: Biological Perspective and Social Cognitive Theory .
• Gender: Culturally-Prescribed Role or Biological Sex .
• The Influence of Opioid Misuse on Academic Achievement of Veteran Students .
• The Importance of Ethics in Research .
• The Role of Family and Social Network Support in Mental Health .

Education Literature Review Example

For your education studies , you can write a review of related literature about academic performance to determine factors that affect student achievement and highlight research gaps. One more idea is to create a review of related literature on study habits , considering their role in the student’s life and academic outcomes.

You can also evaluate a computerized grading system in a review of related literature to single out its advantages and barriers to implementation. Or you can complete a review of related literature on instructional materials to identify their most common types and effects on student achievement.

📝 Find some inspiration in the examples below:

• Literature Review on Online Learning Challenges From COVID-19 .
• Education, Leadership, and Management: Literature Review .
• Literature Review: Standardized Testing Bias .
• Bullying of Disabled Children in School .
• Interventions and Letter & Sound Recognition: A Literature Review .
• Social-Emotional Skills Program for Preschoolers .
• Effectiveness of Educational Leadership Management Skills .

Business Research Literature Review

If you’re a business student, you can focus on customer satisfaction in your review of related literature. Discuss specific customer satisfaction features and how it is affected by service quality and prices. You can also create a theoretical literature review about consumer buying behavior to evaluate theories that have significantly contributed to understanding how consumers make purchasing decisions.

📝 Look at the examples to get more exciting ideas:

• Leadership and Communication: Literature Review .
• Human Resource Development: Literature Review .
• Project Management. Literature Review .
• Strategic HRM: A Literature Review .
• Customer Relationship Management: Literature Review .
• Literature Review on International Financial Reporting Standards .
• Cultures of Management: Literature Review .

To conclude, a review of related literature is a significant genre of scholarly works that can be applied in various disciplines and for multiple goals. The sources examined in an RRL provide theoretical frameworks for future studies and help create original research questions and hypotheses.

When you finish your outstanding literature review, don’t forget to check whether it sounds logical and coherent. Our text-to-speech tool can help you with that!

• Literature Reviews | University of North Carolina at Chapel Hill
• Writing a Literature Review | Purdue Online Writing Lab
• Learn How to Write a Review of Literature | University of Wisconsin-Madison
• The Literature Review: A Few Tips on Conducting It | University of Toronto
• Writing a Literature Review | UC San Diego
• Conduct a Literature Review | The University of Arizona
• Methods for Literature Reviews | National Library of Medicine
• Literature Reviews: 5. Write the Review | Georgia State University

How to Write an Animal Testing Essay: Tips for Argumentative & Persuasive Papers

Descriptive essay topics: examples, outline, & more.

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• 5. The Literature Review
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

A literature review surveys prior research published in books, scholarly articles, and any other sources relevant to a particular issue, area of research, or theory, and by so doing, provides a description, summary, and critical evaluation of these works in relation to the research problem being investigated. Literature reviews are designed to provide an overview of sources you have used in researching a particular topic and to demonstrate to your readers how your research fits within existing scholarship about the topic.

Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . Fourth edition. Thousand Oaks, CA: SAGE, 2014.

Importance of a Good Literature Review

A literature review may consist of simply a summary of key sources, but in the social sciences, a literature review usually has an organizational pattern and combines both summary and synthesis, often within specific conceptual categories . A summary is a recap of the important information of the source, but a synthesis is a re-organization, or a reshuffling, of that information in a way that informs how you are planning to investigate a research problem. The analytical features of a literature review might:

• Give a new interpretation of old material or combine new with old interpretations,
• Trace the intellectual progression of the field, including major debates,
• Depending on the situation, evaluate the sources and advise the reader on the most pertinent or relevant research, or
• Usually in the conclusion of a literature review, identify where gaps exist in how a problem has been researched to date.

Given this, the purpose of a literature review is to:

• Place each work in the context of its contribution to understanding the research problem being studied.
• Describe the relationship of each work to the others under consideration.
• Identify new ways to interpret prior research.
• Reveal any gaps that exist in the literature.
• Resolve conflicts amongst seemingly contradictory previous studies.
• Identify areas of prior scholarship to prevent duplication of effort.
• Point the way in fulfilling a need for additional research.
• Locate your own research within the context of existing literature [very important].

Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper. 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Jesson, Jill. Doing Your Literature Review: Traditional and Systematic Techniques . Los Angeles, CA: SAGE, 2011; Knopf, Jeffrey W. "Doing a Literature Review." PS: Political Science and Politics 39 (January 2006): 127-132; Ridley, Diana. The Literature Review: A Step-by-Step Guide for Students . 2nd ed. Los Angeles, CA: SAGE, 2012.

Types of Literature Reviews

It is important to think of knowledge in a given field as consisting of three layers. First, there are the primary studies that researchers conduct and publish. Second are the reviews of those studies that summarize and offer new interpretations built from and often extending beyond the primary studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally among scholars that become part of the body of epistemological traditions within the field.

In composing a literature review, it is important to note that it is often this third layer of knowledge that is cited as "true" even though it often has only a loose relationship to the primary studies and secondary literature reviews. Given this, while literature reviews are designed to provide an overview and synthesis of pertinent sources you have explored, there are a number of approaches you could adopt depending upon the type of analysis underpinning your study.

Argumentative Review This form examines literature selectively in order to support or refute an argument, deeply embedded assumption, or philosophical problem already established in the literature. The purpose is to develop a body of literature that establishes a contrarian viewpoint. Given the value-laden nature of some social science research [e.g., educational reform; immigration control], argumentative approaches to analyzing the literature can be a legitimate and important form of discourse. However, note that they can also introduce problems of bias when they are used to make summary claims of the sort found in systematic reviews [see below].

Integrative Review Considered a form of research that reviews, critiques, and synthesizes representative literature on a topic in an integrated way such that new frameworks and perspectives on the topic are generated. The body of literature includes all studies that address related or identical hypotheses or research problems. A well-done integrative review meets the same standards as primary research in regard to clarity, rigor, and replication. This is the most common form of review in the social sciences.

Historical Review Few things rest in isolation from historical precedent. Historical literature reviews focus on examining research throughout a period of time, often starting with the first time an issue, concept, theory, phenomena emerged in the literature, then tracing its evolution within the scholarship of a discipline. The purpose is to place research in a historical context to show familiarity with state-of-the-art developments and to identify the likely directions for future research.

Methodological Review A review does not always focus on what someone said [findings], but how they came about saying what they say [method of analysis]. Reviewing methods of analysis provides a framework of understanding at different levels [i.e. those of theory, substantive fields, research approaches, and data collection and analysis techniques], how researchers draw upon a wide variety of knowledge ranging from the conceptual level to practical documents for use in fieldwork in the areas of ontological and epistemological consideration, quantitative and qualitative integration, sampling, interviewing, data collection, and data analysis. This approach helps highlight ethical issues which you should be aware of and consider as you go through your own study.

Systematic Review This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research, and to collect, report, and analyze data from the studies that are included in the review. The goal is to deliberately document, critically evaluate, and summarize scientifically all of the research about a clearly defined research problem . Typically it focuses on a very specific empirical question, often posed in a cause-and-effect form, such as "To what extent does A contribute to B?" This type of literature review is primarily applied to examining prior research studies in clinical medicine and allied health fields, but it is increasingly being used in the social sciences.

Theoretical Review The purpose of this form is to examine the corpus of theory that has accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature review helps to establish what theories already exist, the relationships between them, to what degree the existing theories have been investigated, and to develop new hypotheses to be tested. Often this form is used to help establish a lack of appropriate theories or reveal that current theories are inadequate for explaining new or emerging research problems. The unit of analysis can focus on a theoretical concept or a whole theory or framework.

NOTE: Most often the literature review will incorporate some combination of types. For example, a review that examines literature supporting or refuting an argument, assumption, or philosophical problem related to the research problem will also need to include writing supported by sources that establish the history of these arguments in the literature.

Baumeister, Roy F. and Mark R. Leary. "Writing Narrative Literature Reviews."  Review of General Psychology 1 (September 1997): 311-320; Mark R. Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Kennedy, Mary M. "Defining a Literature." Educational Researcher 36 (April 2007): 139-147; Petticrew, Mark and Helen Roberts. Systematic Reviews in the Social Sciences: A Practical Guide . Malden, MA: Blackwell Publishers, 2006; Torracro, Richard. "Writing Integrative Literature Reviews: Guidelines and Examples." Human Resource Development Review 4 (September 2005): 356-367; Rocco, Tonette S. and Maria S. Plakhotnik. "Literature Reviews, Conceptual Frameworks, and Theoretical Frameworks: Terms, Functions, and Distinctions." Human Ressource Development Review 8 (March 2008): 120-130; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016.

Structure and Writing Style

I.  Thinking About Your Literature Review

The structure of a literature review should include the following in support of understanding the research problem :

• An overview of the subject, issue, or theory under consideration, along with the objectives of the literature review,
• Division of works under review into themes or categories [e.g. works that support a particular position, those against, and those offering alternative approaches entirely],
• An explanation of how each work is similar to and how it varies from the others,
• Conclusions as to which pieces are best considered in their argument, are most convincing of their opinions, and make the greatest contribution to the understanding and development of their area of research.

The critical evaluation of each work should consider :

• Provenance -- what are the author's credentials? Are the author's arguments supported by evidence [e.g. primary historical material, case studies, narratives, statistics, recent scientific findings]?
• Methodology -- were the techniques used to identify, gather, and analyze the data appropriate to addressing the research problem? Was the sample size appropriate? Were the results effectively interpreted and reported?
• Objectivity -- is the author's perspective even-handed or prejudicial? Is contrary data considered or is certain pertinent information ignored to prove the author's point?
• Persuasiveness -- which of the author's theses are most convincing or least convincing?
• Validity -- are the author's arguments and conclusions convincing? Does the work ultimately contribute in any significant way to an understanding of the subject?

II.  Development of the Literature Review

Four Basic Stages of Writing 1.  Problem formulation -- which topic or field is being examined and what are its component issues? 2.  Literature search -- finding materials relevant to the subject being explored. 3.  Data evaluation -- determining which literature makes a significant contribution to the understanding of the topic. 4.  Analysis and interpretation -- discussing the findings and conclusions of pertinent literature.

Consider the following issues before writing the literature review: Clarify If your assignment is not specific about what form your literature review should take, seek clarification from your professor by asking these questions: 1.  Roughly how many sources would be appropriate to include? 2.  What types of sources should I review (books, journal articles, websites; scholarly versus popular sources)? 3.  Should I summarize, synthesize, or critique sources by discussing a common theme or issue? 4.  Should I evaluate the sources in any way beyond evaluating how they relate to understanding the research problem? 5.  Should I provide subheadings and other background information, such as definitions and/or a history? Find Models Use the exercise of reviewing the literature to examine how authors in your discipline or area of interest have composed their literature review sections. Read them to get a sense of the types of themes you might want to look for in your own research or to identify ways to organize your final review. The bibliography or reference section of sources you've already read, such as required readings in the course syllabus, are also excellent entry points into your own research. Narrow the Topic The narrower your topic, the easier it will be to limit the number of sources you need to read in order to obtain a good survey of relevant resources. Your professor will probably not expect you to read everything that's available about the topic, but you'll make the act of reviewing easier if you first limit scope of the research problem. A good strategy is to begin by searching the USC Libraries Catalog for recent books about the topic and review the table of contents for chapters that focuses on specific issues. You can also review the indexes of books to find references to specific issues that can serve as the focus of your research. For example, a book surveying the history of the Israeli-Palestinian conflict may include a chapter on the role Egypt has played in mediating the conflict, or look in the index for the pages where Egypt is mentioned in the text. Consider Whether Your Sources are Current Some disciplines require that you use information that is as current as possible. This is particularly true in disciplines in medicine and the sciences where research conducted becomes obsolete very quickly as new discoveries are made. However, when writing a review in the social sciences, a survey of the history of the literature may be required. In other words, a complete understanding the research problem requires you to deliberately examine how knowledge and perspectives have changed over time. Sort through other current bibliographies or literature reviews in the field to get a sense of what your discipline expects. You can also use this method to explore what is considered by scholars to be a "hot topic" and what is not.

III.  Ways to Organize Your Literature Review

Chronology of Events If your review follows the chronological method, you could write about the materials according to when they were published. This approach should only be followed if a clear path of research building on previous research can be identified and that these trends follow a clear chronological order of development. For example, a literature review that focuses on continuing research about the emergence of German economic power after the fall of the Soviet Union. By Publication Order your sources by publication chronology, then, only if the order demonstrates a more important trend. For instance, you could order a review of literature on environmental studies of brown fields if the progression revealed, for example, a change in the soil collection practices of the researchers who wrote and/or conducted the studies. Thematic [“conceptual categories”] A thematic literature review is the most common approach to summarizing prior research in the social and behavioral sciences. Thematic reviews are organized around a topic or issue, rather than the progression of time, although the progression of time may still be incorporated into a thematic review. For example, a review of the Internet’s impact on American presidential politics could focus on the development of online political satire. While the study focuses on one topic, the Internet’s impact on American presidential politics, it would still be organized chronologically reflecting technological developments in media. The difference in this example between a "chronological" and a "thematic" approach is what is emphasized the most: themes related to the role of the Internet in presidential politics. Note that more authentic thematic reviews tend to break away from chronological order. A review organized in this manner would shift between time periods within each section according to the point being made. Methodological A methodological approach focuses on the methods utilized by the researcher. For the Internet in American presidential politics project, one methodological approach would be to look at cultural differences between the portrayal of American presidents on American, British, and French websites. Or the review might focus on the fundraising impact of the Internet on a particular political party. A methodological scope will influence either the types of documents in the review or the way in which these documents are discussed.

Other Sections of Your Literature Review Once you've decided on the organizational method for your literature review, the sections you need to include in the paper should be easy to figure out because they arise from your organizational strategy. In other words, a chronological review would have subsections for each vital time period; a thematic review would have subtopics based upon factors that relate to the theme or issue. However, sometimes you may need to add additional sections that are necessary for your study, but do not fit in the organizational strategy of the body. What other sections you include in the body is up to you. However, only include what is necessary for the reader to locate your study within the larger scholarship about the research problem.

Here are examples of other sections, usually in the form of a single paragraph, you may need to include depending on the type of review you write:

• Current Situation : Information necessary to understand the current topic or focus of the literature review.
• Sources Used : Describes the methods and resources [e.g., databases] you used to identify the literature you reviewed.
• History : The chronological progression of the field, the research literature, or an idea that is necessary to understand the literature review, if the body of the literature review is not already a chronology.
• Selection Methods : Criteria you used to select (and perhaps exclude) sources in your literature review. For instance, you might explain that your review includes only peer-reviewed [i.e., scholarly] sources.
• Standards : Description of the way in which you present your information.
• Questions for Further Research : What questions about the field has the review sparked? How will you further your research as a result of the review?

IV.  Writing Your Literature Review

Once you've settled on how to organize your literature review, you're ready to write each section. When writing your review, keep in mind these issues.

Use Evidence A literature review section is, in this sense, just like any other academic research paper. Your interpretation of the available sources must be backed up with evidence [citations] that demonstrates that what you are saying is valid. Be Selective Select only the most important points in each source to highlight in the review. The type of information you choose to mention should relate directly to the research problem, whether it is thematic, methodological, or chronological. Related items that provide additional information, but that are not key to understanding the research problem, can be included in a list of further readings . Use Quotes Sparingly Some short quotes are appropriate if you want to emphasize a point, or if what an author stated cannot be easily paraphrased. Sometimes you may need to quote certain terminology that was coined by the author, is not common knowledge, or taken directly from the study. Do not use extensive quotes as a substitute for using your own words in reviewing the literature. Summarize and Synthesize Remember to summarize and synthesize your sources within each thematic paragraph as well as throughout the review. Recapitulate important features of a research study, but then synthesize it by rephrasing the study's significance and relating it to your own work and the work of others. Keep Your Own Voice While the literature review presents others' ideas, your voice [the writer's] should remain front and center. For example, weave references to other sources into what you are writing but maintain your own voice by starting and ending the paragraph with your own ideas and wording. Use Caution When Paraphrasing When paraphrasing a source that is not your own, be sure to represent the author's information or opinions accurately and in your own words. Even when paraphrasing an author’s work, you still must provide a citation to that work.

V.  Common Mistakes to Avoid

These are the most common mistakes made in reviewing social science research literature.

• Sources in your literature review do not clearly relate to the research problem;
• You do not take sufficient time to define and identify the most relevant sources to use in the literature review related to the research problem;
• Relies exclusively on secondary analytical sources rather than including relevant primary research studies or data;
• Uncritically accepts another researcher's findings and interpretations as valid, rather than examining critically all aspects of the research design and analysis;
• Does not describe the search procedures that were used in identifying the literature to review;
• Reports isolated statistical results rather than synthesizing them in chi-squared or meta-analytic methods; and,
• Only includes research that validates assumptions and does not consider contrary findings and alternative interpretations found in the literature.

Cook, Kathleen E. and Elise Murowchick. “Do Literature Review Skills Transfer from One Course to Another?” Psychology Learning and Teaching 13 (March 2014): 3-11; Fink, Arlene. Conducting Research Literature Reviews: From the Internet to Paper . 2nd ed. Thousand Oaks, CA: Sage, 2005; Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1998; Jesson, Jill. Doing Your Literature Review: Traditional and Systematic Techniques . London: SAGE, 2011; Literature Review Handout. Online Writing Center. Liberty University; Literature Reviews. The Writing Center. University of North Carolina; Onwuegbuzie, Anthony J. and Rebecca Frels. Seven Steps to a Comprehensive Literature Review: A Multimodal and Cultural Approach . Los Angeles, CA: SAGE, 2016; Ridley, Diana. The Literature Review: A Step-by-Step Guide for Students . 2nd ed. Los Angeles, CA: SAGE, 2012; Randolph, Justus J. “A Guide to Writing the Dissertation Literature Review." Practical Assessment, Research, and Evaluation. vol. 14, June 2009; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016; Taylor, Dena. The Literature Review: A Few Tips On Conducting It. University College Writing Centre. University of Toronto; Writing a Literature Review. Academic Skills Centre. University of Canberra.

Writing Tip

Break Out of Your Disciplinary Box!

Thinking interdisciplinarily about a research problem can be a rewarding exercise in applying new ideas, theories, or concepts to an old problem. For example, what might cultural anthropologists say about the continuing conflict in the Middle East? In what ways might geographers view the need for better distribution of social service agencies in large cities than how social workers might study the issue? You don’t want to substitute a thorough review of core research literature in your discipline for studies conducted in other fields of study. However, particularly in the social sciences, thinking about research problems from multiple vectors is a key strategy for finding new solutions to a problem or gaining a new perspective. Consult with a librarian about identifying research databases in other disciplines; almost every field of study has at least one comprehensive database devoted to indexing its research literature.

Frodeman, Robert. The Oxford Handbook of Interdisciplinarity . New York: Oxford University Press, 2010.

Another Writing Tip

Don't Just Review for Content!

While conducting a review of the literature, maximize the time you devote to writing this part of your paper by thinking broadly about what you should be looking for and evaluating. Review not just what scholars are saying, but how are they saying it. Some questions to ask:

• How are they organizing their ideas?
• What methods have they used to study the problem?
• What theories have been used to explain, predict, or understand their research problem?
• What sources have they cited to support their conclusions?
• How have they used non-textual elements [e.g., charts, graphs, figures, etc.] to illustrate key points?

When you begin to write your literature review section, you'll be glad you dug deeper into how the research was designed and constructed because it establishes a means for developing more substantial analysis and interpretation of the research problem.

Hart, Chris. Doing a Literature Review: Releasing the Social Science Research Imagination . Thousand Oaks, CA: Sage Publications, 1 998.

Yet Another Writing Tip

When Do I Know I Can Stop Looking and Move On?

Here are several strategies you can utilize to assess whether you've thoroughly reviewed the literature:

• Look for repeating patterns in the research findings . If the same thing is being said, just by different people, then this likely demonstrates that the research problem has hit a conceptual dead end. At this point consider: Does your study extend current research?  Does it forge a new path? Or, does is merely add more of the same thing being said?
• Look at sources the authors cite to in their work . If you begin to see the same researchers cited again and again, then this is often an indication that no new ideas have been generated to address the research problem.
• Search Google Scholar to identify who has subsequently cited leading scholars already identified in your literature review [see next sub-tab]. This is called citation tracking and there are a number of sources that can help you identify who has cited whom, particularly scholars from outside of your discipline. Here again, if the same authors are being cited again and again, this may indicate no new literature has been written on the topic.

Onwuegbuzie, Anthony J. and Rebecca Frels. Seven Steps to a Comprehensive Literature Review: A Multimodal and Cultural Approach . Los Angeles, CA: Sage, 2016; Sutton, Anthea. Systematic Approaches to a Successful Literature Review . Los Angeles, CA: Sage Publications, 2016.

• << Previous: Theoretical Framework
• Next: Citation Tracking >>
• Last Updated: Sep 4, 2024 9:40 AM
• URL: https://libguides.usc.edu/writingguide

Research Methods

• Getting Started
• Literature Review Research
• Research Design
• Research Design By Discipline
• SAGE Research Methods
• Teaching with SAGE Research Methods

Literature Review

• What is a Literature Review?
• What is NOT a Literature Review?
• Purposes of a Literature Review
• Types of Literature Reviews
• Literature Reviews vs. Systematic Reviews
• Systematic vs. Meta-Analysis

Literature Review  is a comprehensive survey of the works published in a particular field of study or line of research, usually over a specific period of time, in the form of an in-depth, critical bibliographic essay or annotated list in which attention is drawn to the most significant works.

Also, we can define a literature review as the collected body of scholarly works related to a topic:

• Summarizes and analyzes previous research relevant to a topic
• Includes scholarly books and articles published in academic journals
• Can be an specific scholarly paper or a section in a research paper

The objective of a Literature Review is to find previous published scholarly works relevant to an specific topic

• Help gather ideas or information
• Keep up to date in current trends and findings
• Help develop new questions

A literature review is important because it:

• Explains the background of research on a topic.
• Demonstrates why a topic is significant to a subject area.
• Helps focus your own research questions or problems
• Discovers relationships between research studies/ideas.
• Suggests unexplored ideas or populations
• Identifies major themes, concepts, and researchers on a topic.
• Tests assumptions; may help counter preconceived ideas and remove unconscious bias.
• Identifies critical gaps, points of disagreement, or potentially flawed methodology or theoretical approaches.
• Indicates potential directions for future research.

All content in this section is from Literature Review Research from Old Dominion University 

Keep in mind the following, a literature review is NOT:

Not an essay 

Not an annotated bibliography  in which you summarize each article that you have reviewed.  A literature review goes beyond basic summarizing to focus on the critical analysis of the reviewed works and their relationship to your research question.

Not a research paper   where you select resources to support one side of an issue versus another.  A lit review should explain and consider all sides of an argument in order to avoid bias, and areas of agreement and disagreement should be highlighted.

A literature review serves several purposes. For example, it

• provides thorough knowledge of previous studies; introduces seminal works.
• helps focus one’s own research topic.
• identifies a conceptual framework for one’s own research questions or problems; indicates potential directions for future research.
• suggests previously unused or underused methodologies, designs, quantitative and qualitative strategies.
• identifies gaps in previous studies; identifies flawed methodologies and/or theoretical approaches; avoids replication of mistakes.
• helps the researcher avoid repetition of earlier research.
• suggests unexplored populations.
• determines whether past studies agree or disagree; identifies controversy in the literature.
• tests assumptions; may help counter preconceived ideas and remove unconscious bias.

As Kennedy (2007) notes*, it is important to think of knowledge in a given field as consisting of three layers. First, there are the primary studies that researchers conduct and publish. Second are the reviews of those studies that summarize and offer new interpretations built from and often extending beyond the original studies. Third, there are the perceptions, conclusions, opinion, and interpretations that are shared informally that become part of the lore of field. In composing a literature review, it is important to note that it is often this third layer of knowledge that is cited as "true" even though it often has only a loose relationship to the primary studies and secondary literature reviews.

Given this, while literature reviews are designed to provide an overview and synthesis of pertinent sources you have explored, there are several approaches to how they can be done, depending upon the type of analysis underpinning your study. Listed below are definitions of types of literature reviews:

Argumentative Review      This form examines literature selectively in order to support or refute an argument, deeply imbedded assumption, or philosophical problem already established in the literature. The purpose is to develop a body of literature that establishes a contrarian viewpoint. Given the value-laden nature of some social science research [e.g., educational reform; immigration control], argumentative approaches to analyzing the literature can be a legitimate and important form of discourse. However, note that they can also introduce problems of bias when they are used to to make summary claims of the sort found in systematic reviews.

Integrative Review      Considered a form of research that reviews, critiques, and synthesizes representative literature on a topic in an integrated way such that new frameworks and perspectives on the topic are generated. The body of literature includes all studies that address related or identical hypotheses. A well-done integrative review meets the same standards as primary research in regard to clarity, rigor, and replication.

Historical Review      Few things rest in isolation from historical precedent. Historical reviews are focused on examining research throughout a period of time, often starting with the first time an issue, concept, theory, phenomena emerged in the literature, then tracing its evolution within the scholarship of a discipline. The purpose is to place research in a historical context to show familiarity with state-of-the-art developments and to identify the likely directions for future research.

Methodological Review      A review does not always focus on what someone said [content], but how they said it [method of analysis]. This approach provides a framework of understanding at different levels (i.e. those of theory, substantive fields, research approaches and data collection and analysis techniques), enables researchers to draw on a wide variety of knowledge ranging from the conceptual level to practical documents for use in fieldwork in the areas of ontological and epistemological consideration, quantitative and qualitative integration, sampling, interviewing, data collection and data analysis, and helps highlight many ethical issues which we should be aware of and consider as we go through our study.

Systematic Review      This form consists of an overview of existing evidence pertinent to a clearly formulated research question, which uses pre-specified and standardized methods to identify and critically appraise relevant research, and to collect, report, and analyse data from the studies that are included in the review. Typically it focuses on a very specific empirical question, often posed in a cause-and-effect form, such as "To what extent does A contribute to B?"

Theoretical Review      The purpose of this form is to concretely examine the corpus of theory that has accumulated in regard to an issue, concept, theory, phenomena. The theoretical literature review help establish what theories already exist, the relationships between them, to what degree the existing theories have been investigated, and to develop new hypotheses to be tested. Often this form is used to help establish a lack of appropriate theories or reveal that current theories are inadequate for explaining new or emerging research problems. The unit of analysis can focus on a theoretical concept or a whole theory or framework.

* Kennedy, Mary M. "Defining a Literature."  Educational Researcher  36 (April 2007): 139-147.

All content in this section is from The Literature Review created by Dr. Robert Larabee USC

Robinson, P. and Lowe, J. (2015),  Literature reviews vs systematic reviews.  Australian and New Zealand Journal of Public Health, 39: 103-103. doi: 10.1111/1753-6405.12393

What's in the name? The difference between a Systematic Review and a Literature Review, and why it matters . By Lynn Kysh from University of Southern California

Systematic review or meta-analysis?

A  systematic review  answers a defined research question by collecting and summarizing all empirical evidence that fits pre-specified eligibility criteria.

A  meta-analysis  is the use of statistical methods to summarize the results of these studies.

Systematic reviews, just like other research articles, can be of varying quality. They are a significant piece of work (the Centre for Reviews and Dissemination at York estimates that a team will take 9-24 months), and to be useful to other researchers and practitioners they should have:

• clearly stated objectives with pre-defined eligibility criteria for studies
• explicit, reproducible methodology
• a systematic search that attempts to identify all studies
• assessment of the validity of the findings of the included studies (e.g. risk of bias)
• systematic presentation, and synthesis, of the characteristics and findings of the included studies

Not all systematic reviews contain meta-analysis. 

Meta-analysis is the use of statistical methods to summarize the results of independent studies. By combining information from all relevant studies, meta-analysis can provide more precise estimates of the effects of health care than those derived from the individual studies included within a review.  More information on meta-analyses can be found in  Cochrane Handbook, Chapter 9 .

A meta-analysis goes beyond critique and integration and conducts secondary statistical analysis on the outcomes of similar studies.  It is a systematic review that uses quantitative methods to synthesize and summarize the results.

An advantage of a meta-analysis is the ability to be completely objective in evaluating research findings.  Not all topics, however, have sufficient research evidence to allow a meta-analysis to be conducted.  In that case, an integrative review is an appropriate strategy. 

Some of the content in this section is from Systematic reviews and meta-analyses: step by step guide created by Kate McAllister.

• << Previous: Getting Started
• Next: Research Design >>
• Last Updated: Jul 15, 2024 10:34 AM
• URL: https://guides.lib.udel.edu/researchmethods

[email protected]  

+91 80562 90962.

• Jul 9, 2017

What are Related studies in research? How it is helpful for all Ph.D and master level students?

Updated: Jun 11, 2020

Once you all set with research field/domain/area in next step you need to know about recent trends and research going on particular domain. Before starting with your research or project work to understand feasibility of research/project related study or review of literature need to be done.

Here we will see what are related studies/ literature review for completing your project/research work.

Usually, related studies is about reviewing or studying existing works carried out in your project/research field. Especially, for Ph.D candidate’s related works is important constraint since pave path to entire research process. Related studies can be taken from journals, magazines, website links, government reports and other source.

Here your related studies need to provide

What’s problem in existing in selected domain?

What are the methods developed or adopted?

Which technique exhibit excellent outcome and effective?

Once you find answer for all this question rest will be easy! To calculate the feasibility and methodology need to be adopted for completion of your project.

In final stage of both Ph.D and Master level you need to submit dissertation/thesis which is documentation of research work. In that related studies offers need to be included to justify your novelty of your research work. Even you can point out research gap of selected research field why you selected this domain. If you clearly mention in your documentation and presentation you complete research/project.

Related: Thesis writing help in India

#definitionforresearch #Inresearch #relatedstudies #researchfield #literaturereview #thesis #academic #dissertation #PhDcandidate

Recent Posts

HOW MANY CHAPTERS SHOULD A DISSERTATION HAVE?

Top 10 University to pursue a Ph.D. in India (2019)

What is Correlation analysis

Student Academic Success Center

Related work / literature review / research review, download pdf handout:   literature reviews, watch video:   literature reviews.

A  literature review, research review,  or  related work   section compares, contrasts, synthesizes, and provides introspection about the available knowledge for a given topic or field. The two terms are sometimes used interchangeably (as they are here), but while both can refer to a section of a longer work, “literature review” can also describe a stand-alone paper.

When you start writing a literature review, the most straightforward course may be to compile all relevant sources and compare them, perhaps evaluating their strengths and weaknesses. While this is a good place to start, your literature review is incomplete unless it creates something new through these comparisons. Luckily, our resources can help you do this!

With these resources, you’ll learn:

• How to write a literature review that  contributes  rather than  summarizes
• Common mistakes to avoid
• Useful phrases to show agreement and disagreement between sources

Need one-on-one help with your literature review or research article? Schedule an appointment with one of our consultants now!

Schedule an Appointment

Quick Links

• Academic Calendar
• Academic Integrity
• Bias Reporting and Response
• Statement of Assurance
• Documents, Forms, and News [Internal Staff Only]

Other Helpful Departments

• Disability Resources
• Center for Student Diversity & Inclusion
• Graduate Education
• Office of International Education
• University Health Services

• Affiliate Program

• UNITED STATES
• 台灣 (TAIWAN)
• TÜRKIYE (TURKEY)
• Academic Editing Services
• - Research Paper
• - Journal Manuscript
• - Dissertation
• - College & University Assignments
• Admissions Editing Services
• - Application Essay
• - Personal Statement
• - Recommendation Letter
• - Cover Letter
• - CV/Resume
• Business Editing Services
• - Business Documents
• - Report & Brochure
• - Website & Blog
• Writer Editing Services
• - Script & Screenplay
• Our Editors
• Client Reviews
• Editing & Proofreading Prices
• Wordvice Points
• Partner Discount
• Plagiarism Checker
• APA Citation Generator
• MLA Citation Generator
• Chicago Citation Generator
• Vancouver Citation Generator
• - APA Style
• - MLA Style
• - Chicago Style
• - Vancouver Style
• Writing & Editing Guide
• Academic Resources
• Admissions Resources

How to Make a Literature Review in Research (RRL Example)

What is an RRL in a research paper?

A relevant review of the literature (RRL) is an objective, concise, critical summary of published research literature relevant to a topic being researched in an article. In an RRL, you discuss knowledge and findings from existing literature relevant to your study topic. If there are conflicts or gaps in existing literature, you can also discuss these in your review, as well as how you will confront these missing elements or resolve these issues in your study.

To complete an RRL, you first need to collect relevant literature; this can include online and offline sources. Save all of your applicable resources as you will need to include them in your paper. When looking through these sources, take notes and identify concepts of each source to describe in the review of the literature.

A good RRL does NOT:

A literature review does not simply reference and list all of the material you have cited in your paper.

• Presenting material that is not directly relevant to your study will distract and frustrate the reader and make them lose sight of the purpose of your study.
• Starting a literature review with “A number of scholars have studied the relationship between X and Y” and simply listing who has studied the topic and what each scholar concluded is not going to strengthen your paper.

A good RRL DOES:

• Present a brief typology that orders articles and books into groups to help readers focus on unresolved debates, inconsistencies, tensions, and new questions about a research topic.
• Summarize the most relevant and important aspects of the scientific literature related to your area of research
• Synthesize what has been done in this area of research and by whom, highlight what previous research indicates about a topic, and identify potential gaps and areas of disagreement in the field
• Give the reader an understanding of the background of the field and show which studies are important—and highlight errors in previous studies

How long is a review of the literature for a research paper?

The length of a review of the literature depends on its purpose and target readership and can vary significantly in scope and depth. In a dissertation, thesis, or standalone review of literature, it is usually a full chapter of the text (at least 20 pages). Whereas, a standard research article or school assignment literature review section could only be a few paragraphs in the Introduction section .

Building Your Literature Review Bookshelf

One way to conceive of a literature review is to think about writing it as you would build a bookshelf. You don’t need to cut each piece by yourself from scratch. Rather, you can take the pieces that other researchers have cut out and put them together to build a framework on which to hang your own “books”—that is, your own study methods, results, and conclusions.

What Makes a Good Literature Review?

The contents of a literature review (RRL) are determined by many factors, including its precise purpose in the article, the degree of consensus with a given theory or tension between competing theories, the length of the article, the number of previous studies existing in the given field, etc. The following are some of the most important elements that a literature review provides.

Historical background for your research

Analyze what has been written about your field of research to highlight what is new and significant in your study—or how the analysis itself contributes to the understanding of this field, even in a small way. Providing a historical background also demonstrates to other researchers and journal editors your competency in discussing theoretical concepts. You should also make sure to understand how to paraphrase scientific literature to avoid plagiarism in your work.

The current context of your research

Discuss central (or peripheral) questions, issues, and debates in the field. Because a field is constantly being updated by new work, you can show where your research fits into this context and explain developments and trends in research.

A discussion of relevant theories and concepts

Theories and concepts should provide the foundation for your research. For example, if you are researching the relationship between ecological environments and human populations, provide models and theories that focus on specific aspects of this connection to contextualize your study. If your study asks a question concerning sustainability, mention a theory or model that underpins this concept. If it concerns invasive species, choose material that is focused in this direction.

Definitions of relevant terminology

In the natural sciences, the meaning of terms is relatively straightforward and consistent. But if you present a term that is obscure or context-specific, you should define the meaning of the term in the Introduction section (if you are introducing a study) or in the summary of the literature being reviewed.

Description of related relevant research

Include a description of related research that shows how your work expands or challenges earlier studies or fills in gaps in previous work. You can use your literature review as evidence of what works, what doesn’t, and what is missing in the field.

Supporting evidence for a practical problem or issue your research is addressing that demonstrates its importance: Referencing related research establishes your area of research as reputable and shows you are building upon previous work that other researchers have deemed significant.

Types of Literature Reviews

Literature reviews can differ in structure, length, amount, and breadth of content included. They can range from selective (a very narrow area of research or only a single work) to comprehensive (a larger amount or range of works). They can also be part of a larger work or stand on their own.

• A course assignment is an example of a selective, stand-alone work. It focuses on a small segment of the literature on a topic and makes up an entire work on its own.
• The literature review in a dissertation or thesis is both comprehensive and helps make up a larger work.
• A majority of journal articles start with a selective literature review to provide context for the research reported in the study; such a literature review is usually included in the Introduction section (but it can also follow the presentation of the results in the Discussion section ).
• Some literature reviews are both comprehensive and stand as a separate work—in this case, the entire article analyzes the literature on a given topic.

Literature Reviews Found in Academic Journals

The two types of literature reviews commonly found in journals are those introducing research articles (studies and surveys) and stand-alone literature analyses. They can differ in their scope, length, and specific purpose.

Literature reviews introducing research articles

The literature review found at the beginning of a journal article is used to introduce research related to the specific study and is found in the Introduction section, usually near the end. It is shorter than a stand-alone review because it must be limited to very specific studies and theories that are directly relevant to the current study. Its purpose is to set research precedence and provide support for the study’s theory, methods, results, and/or conclusions. Not all research articles contain an explicit review of the literature, but most do, whether it is a discrete section or indistinguishable from the rest of the Introduction.

How to structure a literature review for an article

When writing a literature review as part of an introduction to a study, simply follow the structure of the Introduction and move from the general to the specific—presenting the broadest background information about a topic first and then moving to specific studies that support your rationale , finally leading to your hypothesis statement. Such a literature review is often indistinguishable from the Introduction itself—the literature is INTRODUCING the background and defining the gaps your study aims to fill.

The stand-alone literature review

The literature review published as a stand-alone article presents and analyzes as many of the important publications in an area of study as possible to provide background information and context for a current area of research or a study. Stand-alone reviews are an excellent resource for researchers when they are first searching for the most relevant information on an area of study.

Such literature reviews are generally a bit broader in scope and can extend further back in time. This means that sometimes a scientific literature review can be highly theoretical, in addition to focusing on specific methods and outcomes of previous studies. In addition, all sections of such a “review article” refer to existing literature rather than describing the results of the authors’ own study.

In addition, this type of literature review is usually much longer than the literature review introducing a study. At the end of the review follows a conclusion that once again explicitly ties all of the cited works together to show how this analysis is itself a contribution to the literature. While not absolutely necessary, such articles often include the terms “Literature Review” or “Review of the Literature” in the title. Whether or not that is necessary or appropriate can also depend on the specific author instructions of the target journal. Have a look at this article for more input on how to compile a stand-alone review article that is insightful and helpful for other researchers in your field.

How to Write a Literature Review in 6 Steps

So how do authors turn a network of articles into a coherent review of relevant literature?

Writing a literature review is not usually a linear process—authors often go back and check the literature while reformulating their ideas or making adjustments to their study. Sometimes new findings are published before a study is completed and need to be incorporated into the current work. This also means you will not be writing the literature review at any one time, but constantly working on it before, during, and after your study is complete.

Here are some steps that will help you begin and follow through on your literature review.

Step 1: Choose a topic to write about—focus on and explore this topic.

Choose a topic that you are familiar with and highly interested in analyzing; a topic your intended readers and researchers will find interesting and useful; and a topic that is current, well-established in the field, and about which there has been sufficient research conducted for a review. This will help you find the “sweet spot” for what to focus on.

Step 2: Research and collect all the scholarly information on the topic that might be pertinent to your study.

This includes scholarly articles, books, conventions, conferences, dissertations, and theses—these and any other academic work related to your area of study is called “the literature.”

Step 3: Analyze the network of information that extends or responds to the major works in your area; select the material that is most useful.

Use thought maps and charts to identify intersections in the research and to outline important categories; select the material that will be most useful to your review.

Step 4: Describe and summarize each article—provide the essential information of the article that pertains to your study.

Determine 2-3 important concepts (depending on the length of your article) that are discussed in the literature; take notes about all of the important aspects of this study relevant to the topic being reviewed.

For example, in a given study, perhaps some of the main concepts are X, Y, and Z. Note these concepts and then write a brief summary about how the article incorporates them. In reviews that introduce a study, these can be relatively short. In stand-alone reviews, there may be significantly more texts and more concepts.

Step 5: Demonstrate how these concepts in the literature relate to what you discovered in your study or how the literature connects the concepts or topics being discussed.

In a literature review intro for an article, this information might include a summary of the results or methods of previous studies that correspond to and/or confirm those sections in your own study. For a stand-alone literature review, this may mean highlighting the concepts in each article and showing how they strengthen a hypothesis or show a pattern.

Discuss unaddressed issues in previous studies. These studies that are missing something you address are important to include in your literature review. In addition, those works whose theories and conclusions directly support your findings will be valuable to review here.

Step 6: Identify relationships in the literature and develop and connect your own ideas to them.

This is essentially the same as step 5 but focused on the connections between the literature and the current study or guiding concepts or arguments of the paper, not only on the connections between the works themselves.

Your hypothesis, argument, or guiding concept is the “golden thread” that will ultimately tie the works together and provide readers with specific insights they didn’t have before reading your literature review. Make sure you know where to put the research question , hypothesis, or statement of the problem in your research paper so that you guide your readers logically and naturally from your introduction of earlier work and evidence to the conclusions you want them to draw from the bigger picture.

Your literature review will not only cover publications on your topics but will include your own ideas and contributions. By following these steps you will be telling the specific story that sets the background and shows the significance of your research and you can turn a network of related works into a focused review of the literature.

Literature Review (RRL) Examples

Because creating sample literature reviews would take too long and not properly capture the nuances and detailed information needed for a good review, we have included some links to different types of literature reviews below. You can find links to more literature reviews in these categories by visiting the TUS Library’s website . Sample literature reviews as part of an article, dissertation, or thesis:

• Critical Thinking and Transferability: A Review of the Literature (Gwendolyn Reece)
• Building Customer Loyalty: A Customer Experience Based Approach in a Tourism Context (Martina Donnelly)

Sample stand-alone literature reviews

• Literature Review on Attitudes towards Disability (National Disability Authority)
• The Effects of Communication Styles on Marital Satisfaction (Hannah Yager)

Additional Literature Review Format Guidelines

In addition to the content guidelines above, authors also need to check which style guidelines to use ( APA , Chicago, MLA, etc.) and what specific rules the target journal might have for how to structure such articles or how many studies to include—such information can usually be found on the journals’ “Guide for Authors” pages. Additionally, use one of the four Wordvice citation generators below, choosing the citation style needed for your paper:

Wordvice Writing and Academic Editing Resources

Finally, after you have finished drafting your literature review, be sure to receive professional proofreading services , including paper editing for your academic work. A competent proofreader who understands academic writing conventions and the specific style guides used by academic journals will ensure that your paper is ready for publication in your target journal.

See our academic resources for further advice on references in your paper , how to write an abstract , how to write a research paper title, how to impress the editor of your target journal with a perfect cover letter , and dozens of other research writing and publication topics.

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

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• HHS Author Manuscripts

How to Conduct Responsible Research: A Guide for Graduate Students

Alison l. antes.

1 Department of Medicine, Division of General Medical Sciences, Washington University School of Medicine, St. Louis, Missouri, 314-362-6006

Leonard B. Maggi, Jr.

2 Department of Medicine, Division of Molecular Oncology, Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, 314-362-4102

Researchers must conduct research responsibly for it to have an impact and to safeguard trust in science. Essential responsibilities of researchers include using rigorous, reproducible research methods, reporting findings in a trustworthy manner, and giving the researchers who contributed appropriate authorship credit. This “how-to” guide covers strategies and practices for doing reproducible research and being a responsible author. The article also covers how to utilize decision-making strategies when uncertain about the best way to proceed in a challenging situation. The advice focuses especially on graduate students but is appropriate for undergraduates and experienced researchers. The article begins with an overview of the responsible conduct of research, research misconduct, and ethical behavior in the scientific workplace. The takeaway message is that responsible conduct of research requires a thoughtful approach to doing research to ensure trustworthy results and conclusions and that researchers receive fair credit.

INTRODUCTION

Doing research is stimulating and fulfilling work. Scientists make discoveries to build knowledge and solve problems, and they work with other dedicated researchers. Research is a highly complex activity, so it takes years for beginning researchers to learn everything they need to know to do science well. Part of this large body of knowledge is learning how to do research responsibly. Our purpose in this article is to provide graduate students a guide for how to perform responsible research. Our advice is also relevant to undergraduate researchers and for principal investigators (PIs), postdocs, or other researchers who mentor beginning researchers and wish to share our advice.

We begin by introducing some fundamentals about the responsible conduct of research (RCR), research misconduct, and ethical behavior. We focus on how to do reproducible science and be a responsible author. We provide practical advice for these topics and present scenarios to practice thinking through challenges in research. Our article concludes with decision-making strategies for addressing complex problems.

What is the responsible conduct of research?

To be committed to RCR means upholding the highest standards of honesty, accuracy, efficiency, and objectivity ( Steneck, 2007 ). Each day, RCR requires engaging in research in a conscientious, intentional fashion that yields the best science possible ( “Research Integrity is Much More Than Misconduct,” 2019 ). We adopt a practical, “how-to” approach, discussing the behaviors and habits that yield responsible research. However, some background knowledge about RCR is helpful to frame our discussion.

The scientific community uses many terms to refer to ethical and responsible behavior in research: responsible conduct of research, research integrity, scientific integrity, and research ethics ( National Academies of Science, 2009 ; National Academies of Sciences Engineering and Medicine, 2017 ; Steneck, 2007 ). A helpful way to think about these concepts is “doing good science in a good manner” ( DuBois & Antes, 2018 ). This means that the way researchers do their work, from experimental procedures to data analysis and interpretation, research reporting, and so on, leads to trustworthy research findings and conclusions. It also includes respectful interactions among researchers both within research teams (e.g., between peers, mentors and trainees, and collaborators) and with researchers external to the team (e.g., peer reviewers). We expand on trainee-mentor relationships and interpersonal dynamics with labmates in a companion article ( Antes & Maggi, 2021 ). When research involves human or animal research subjects, RCR includes protecting the well-being of research subjects.

We do not cover all potential RCR topics but focus on what we consider fundamentals for graduate students. Common topics covered in texts and courses on RCR include the following: authorship and publication; collaboration; conflicts of interest; data management, sharing, and ownership; intellectual property; mentor and trainee responsibilities; peer review; protecting human subjects; protecting animal subjects; research misconduct; the role of researchers in society; and laboratory safety. A number of topics prominently discussed among the scientific community in recent years are also relevant to RCR. These include the reproducibility of research ( Baker, 2016 ; Barba, 2016 ; Winchester, 2018 ), diversity and inclusion in science ( Asplund & Welle, 2018 ; Hofstra et al., 2020 ; Meyers, Brown, Moneta-Koehler, & Chalkley, 2018 ; National Academies of Sciences Engineering and Medicine, 2018a ; Roper, 2019 ), harassment and bullying ( Else, 2018 ; National Academies of Sciences Engineering and Medicine, 2018b ; “ No Place for Bullies in Science,” 2018 ), healthy research work environments ( Norris, Dirnagl, Zigmond, Thompson-Peer, & Chow, 2018 ; “ Research Institutions Must Put the Health of Labs First,” 2018 ), and the mental health of graduate students ( Evans, Bira, Gastelum, Weiss, & Vanderford, 2018 ).

The National Institutes of Health (NIH) ( National Institutes of Health, 2009 ) and the National Science Foundation ( National Science Foundation, 2017 ) have formal policies indicating research trainees must receive education in RCR. Researchers are accountable to these funding agencies and the public which supports research through billions in tax dollars annually. The public stands to benefit from, or be harmed by, research. For example, the public may be harmed if medical treatments or social policies are based on untrustworthy research findings. Funding for research, participation in research, and utilization of the fruits of research all rely on public trust ( Resnik, 2011 ). Trustworthy findings are also essential for good stewardship of scarce resources ( Emanuel, Wendler, & Grady, 2000 ). Researchers are further accountable to their peers, colleagues, and scientists more broadly. Trust in the work of other researchers is essential for science to advance. Finally, researchers are accountable for complying with the rules and policies of their universities or research institutions, such as rules about laboratory safety, bullying and harassment, and the treatment of animal research subjects.

What is research misconduct?

When researchers intentionally misrepresent or manipulate their results, these cases of scientific fraud often make the news headlines ( Chappell, 2019 ; O’Connor, 2018 ; Park, 2012 ), and they can seriously undermine public trust in research. These cases also harm trust within the scientific community.

The U.S. defines research misconduct as fabrication, falsification, and plagiarism (FFP) ( Department of Health and Human Services, 2005 ). FFP violate the fundamental ethical principle of honesty. Fabrication is making up data, and falsification is manipulating or changing data or results so they are no longer truthful. Plagiarism is a form of dishonesty because it includes using someone’s words or ideas and portraying them as your own. When brought to light, misconduct involves lengthy investigations and serious consequences, such as ineligibility to receive federal research funding, loss of employment, paper retractions, and, for students, withdrawal of graduate degrees.

One aspect of responsible behavior includes addressing misconduct if you observe it. We suggest a guide titled “Responding to Research Wrongdoing: A User-Friendly Guide” that provides advice for thinking about your options if you think you have observed misconduct ( Keith-Spiegel, Sieber, & Koocher, 2010 ). Your university will have written policies and procedures for investigating allegations of misconduct. Making an allegation is very serious. As Keith-Spiegel et al.’s guide indicates, it is important to know the evidence that supports your claim, and what to expect in the process. We encourage, if possible, talking to the persons involved first. For example, one of us knew of a graduate student who reported to a journal editor their suspicion of falsified data in a manuscript. It turned out that the student was incorrect. Going above the PI directly to the editor ultimately led to the PI leaving the university, and the student had a difficult time finding a new lab to complete their degree. If the student had first spoken to the PI and lab members, they could have learned that their assumptions about the data in the paper were wrong. In turn, they could have avoided accusing the PI of a serious form of scientific misconduct—making up data—and harming everyone’s scientific career.

What shapes ethical behavior in the scientific workplace?

Responsible conduct of research and research misconduct are two sides of a continuum of behavior—RCR upholds the ideals of research and research misconduct violates them. Problematic practices that fall in the middle but are not defined formally as research misconduct have been labeled as detrimental research practices ( National Academies of Sciences Engineering and Medicine, 2017 ). Researchers conducting misleading statistical analyses or PIs providing inadequate supervision are examples of the latter. Research suggests that characteristics of individual researchers and research environments explain (un)ethical behavior in the scientific workplace ( Antes et al., 2007 ; Antes, English, Baldwin, & DuBois, 2018 ; Davis, Riske-Morris, & Diaz, 2007 ; DuBois et al., 2013 ).

These two influences on ethical behavior are helpful to keep in mind when thinking about your behavior. When people think about their ethical behavior, they think about their personal values and integrity and tend to overlook the influence of their environment. While “being a good person” and having the right intentions are essential to ethical behavior, the environment also has an influence. In addition, knowledge of standards for ethical research is important for ethical behavior, and graduate students new to research do not yet know everything they need to. They also have not fully refined their ethical decision-making skills for solving professional problems. We discuss strategies for ethical decision-making in the final section of this article ( McIntosh, Antes, & DuBois, 2020 ).

The research environment influences ethical behavior in a number of ways. For example, if a research group explicitly discusses high standards for research, people will be more likely to prioritize these ideals in their behavior ( Plemmons et al., 2020 ). A mentor who sets a good example is another important factor ( Anderson et al., 2007 ). Research labs must also provide individuals with adequate training, supervision and feedback, opportunities to discuss data, and the psychological safety to feel comfortable communicating about problems, including mistakes ( Antes, Kuykendall, & DuBois, 2019a , 2019b ). On the other hand, unfair research environments, inadequate supervision, poor communication, and severe stress and anxiety may undermine ethical decision-making and behavior; particularly when many of these factors exist together. Thus, (un)ethical behavior is a complex interplay of individual factors (e.g., personality, stress, decision-making skills) and the environment.

For graduate students, it is important to attend to what you are learning and how the environment around you might influence your behavior. You do not know what you do not know, and you necessarily rely on others to teach you responsible practices. So, it is important to be aware. Ultimately, you are accountable for your behavior. You cannot just say “I didn’t know.” Rather, just like you are curious about your scientific questions, maintain a curiosity about responsible behavior as a researcher. If you feel uncomfortable with something, pay attention to that feeling, speak to someone you trust, and seek out information about how to handle the situation. In what follows, we cover key tips for responsible behavior in the areas of reproducibility and authorship that we hope will help you as you begin.

HOW TO DO REPRODUCIBLE SCIENCE

The foremost responsibility of scientists is to ensure they conduct research in such a manner that the findings are trustworthy. Reproducibility is the ability to duplicate results ( Goodman, Fanelli, & Ioannidis, 2016 ). The scientific community has called for greater openness, transparency, and rigor as key remedies for lack of reproducibility ( Munafò et al., 2017 ). As a graduate student, essential to fostering reproducibility is the rigor of your approach to doing experiments and handling data. We discuss how to utilize research protocols, document experiments in a lab notebook, and handle data responsibly.

Utilize research protocols

1. learn and utilize the lab’s protocols.

Research protocols describe the step-by-step procedures for doing an experiment. They are critical for the quality and reproducibility of experiments. Lab members must learn and follow the lab’s protocols with the understanding that they may need to make adjustments based on the requirements of a specific experiment.

Also, it is important to distinguish between the experiment you are performing and analyzing the data from that experiment. For example, the experiment you want to perform might be to determine if loss of a gene blocks cell growth. Several protocols, each with pros and cons, will allow you to examine “cell growth.” Using the wrong experimental protocol can produce data that leads to muddled conclusions. In this example, the gene does block cell growth, but the experiment used to produce the data that you analyze to understand cell growth is wrong, thus giving a result that is a false negative.

When first joining a lab, it is essential to commit to learning the protocols necessary for your assigned research project. Researchers must ensure they are proficient in executing a protocol and can perform their experiments reliably. If you do not feel confident with a protocol, you should do practice runs if possible. Repetition is the best way to work through difficulties with protocols. Often it takes several attempts to work through the steps of a protocol before you will be comfortable performing it. Asking to watch another lab member perform the protocol is also helpful. Be sure to watch closely how steps are performed, as often there are minor steps taken that are not written down. Also, experienced lab members may do things as second nature and not think to explicitly mention them when working through the protocol. Ask questions of other lab members so that you can improve your knowledge and gain confidence with a protocol. It is better to ask a question than potentially ruin a valuable or hard-to-get sample.

Be cautious of differences in the standing protocols in the lab and how you actually perform the experiment. Even the most minor deviations can seriously impact the results and reproducibility of an experiment. As mentioned above, often there are minor things that are done that might not be listed in the protocol. Paying attention and asking questions are the best ways to learn, in addition to adding notes to the protocol if you find minor details are missing.

2. Develop your own protocols

Often you will find that a project requires a protocol that has not been performed in the lab. If performing a new experiment in the lab and no protocol exists, find a protocol and try it. Protocols can be obtained from many different sources. A great source is other labs on campus, as you can speak directly to the person who performs the experiment. There are many journal sources as well, such as Current Protocols, Nature Protocols, Nature Methods, and Cell STAR Methods . These methods journals provide the most detailed protocols for experiments often with troubleshooting tips. Scientific papers are the most common source of protocols. However, keep in mind that due to the common brevity of methods sections, they often omit crucial details or reference other papers that may not contain a complete description of the protocol.

3. Handle mistakes or problems promptly

At some point, everyone encounters problems with a protocol, or realizes they made a mistake. You should be prepared to handle this situation by being able to detail exactly how you performed the experiment. Did you skip a step? Shorten or lengthen a time point? Did you have to make a new buffer or borrow a labmate’s buffer? There are too many ways an experiment can go wrong to list here but being able to recount all the steps you performed in detail will help you work through the problem. Keep in mind that often the best way to understand how to perform an experiment is learning from when something goes wrong. This situation requires you to critically think through what was done and understand the steps taken. When everything works perfectly, it is easy to pay less attention to the details, which can lead to problems down the line.

It is up to you to be attentive and meticulous in the lab. Paying attention to the details may feel like a pain at first, or even seem overwhelming. Practice and repetition will help this focus on details become a natural part of your lab work. Ultimately, this skill will be essential to being a responsible scientist.

Document experiments in a lab notebook

1. recognize the importance of a lab notebook.

Maintaining detailed documentation in a lab notebook allows researchers to keep track of their experiments and generation of data. This detailed documentation helps you communicate about your research with others in the lab, and serves as a basis for preparing publications. It also provides a lasting record for the lab that exists beyond your time in the lab. After graduate students leave the lab, sometimes it is necessary to go back to the results of older experiments. A complete and detailed notebook is essential, or all of the time, effort, and resources are lost.

2. Learn the note-keeping practices in your lab

When you enter a new lab, it is important to understand how the lab keeps notebooks and the expectations for documentation. Being conscientious about documentation will make you a better scientist. In some labs, the PI might routinely examine your notebook, while in other labs you may be expected to maintain a notebook, but it may not be regularly viewed by others. It is tempting to become relaxed in documentation if you think your notebook may not be reviewed. Avoid this temptation; documentation of your ideas and process will improve your ability to think critically about research. Further, even if the PI or lab members do not physically view your notebook, you will need to communicate with them about your experiments. This documentation is necessary to communicate effectively about your work.

3. Organize your lab notebook

Different labs use different formats; some use electronic notebooks while others handwritten notebooks. The contents of a good notebook include the purpose of the experiment, the details of the experimental procedure, the data, and thoughts about the results. To effectively document your experiment, there are 5 critical questions that the information you record should be able to answer.

• Why I am doing this experiment? (purpose)
• What did I do to perform the experiment? (protocol)
• What are the results of what I did? (data, graphs)
• What do I think about the results?
• What do I think are the next steps?

We also recommend a table of contents. It will make the information more useful to you and the lab in the future. The table of contents should list the title of the experiment, the date(s) it was performed, and the page numbers on which it is recorded. Also, make sure that you write clearly and provide a legend or explanation of any shorthand or non-standard abbreviation you use. Often labs will have a combination of written lab notebooks and electronic data. It is important to reference where electronic data are located that go with each experiment. The idea is to make it as easy as possible to understand what you did and where to find all the data (electronic and hard copy) that accompanies your experiment.

Keeping a lab notebook becomes easier with practice. It can be thought of almost like journaling about your experiment. Sometimes people think of it as just a place to paste their protocol and a graph or data. We strongly encourage you to include your thoughts about why you made the decisions you made when conducting the experiment and to document your thoughts about next steps.

4. Commit to doing it the right way

A common reason to become lax in documentation is feeling rushed for time. Although documentation takes time, it saves time in the long-run and fosters good science. Without good notes, you will waste time trying to recall precisely what you did, reproduce your findings, and remember what you thought would be important next steps. The lab notebook helps you think about your research critically and keep your thoughts together. It can also save you time later when writing up results for publication. Further, well-documented data will help you draft a cogent and rigorous dissertation.

Handle data responsibly

1. keep all data.

Data are the product of research. Data include raw data, processed data, analyzed data, figures, and tables. Many data today are electronic, but not all. Generating data requires a lot of time and resources and researchers must treat data with care. The first essential tip is to keep all data. Do not discard data just because the experiment did not turn out as expected. A lot of experiments do not turn out to yield publishable data, but the results are still important for informing next steps.

Always keep the original, raw data. That is, as you process and analyze data, always maintain an unprocessed version of the original data.

Universities and funding agencies have data retention policies. These policies specify the number of years beyond a grant that data must be kept. Some policies also indicate researchers need to retain original data that served as the basis for a publication for a certain number of years. Therefore, your data will be important well beyond your time in graduate school. Most labs require you to keep samples for reanalysis until a paper is published, then the analyzed data are enough. If you leave a lab before a paper is accepted for publication, you are responsible for ensuring your data and original samples are well documented for others to find and use.

2. Document all data

In addition to keeping all data, data must be well-organized and documented. This means that no matter the way you keep your data (e.g., electronic or in written lab notebooks), there is a clear guide—in your lab notebook, a binder, or on a lab hard drive—to finding the data for a particular experiment. For example, it must be clear which data produced a particular graph. Version control of data is also critical. Your documentation should include “metadata” (data about your data) that tracks versions of the data. For example, as you edit data for a table, you should save separate versions of the tables, name the files sequentially, and note the changes that were made to each version.

3. Backup your data

You should backup electronic data regularly. Ideally, your lab has a shared server or cloud storage to backup data. If you are supposed to put your data there, make sure you do it! When you leave the lab, it must be possible to find your data.

4. Perform data analysis honestly and competently

Inappropriate use of statistics is a major concern in the scientific community, as the results and conclusions will be misleading if done incorrectly ( DeMets, 1999 ). Some practices are clearly an abuse of statistics, while other inappropriate practices stem from lack of knowledge. For example, a practice called “p-hacking” describes when researchers “collect or select data or statistical analyses until nonsignificant results become significant” ( Head, Holman, Lanfear, Kahn, & Jennions, 2015 ). In addition to avoiding such misbehavior, it is essential to be proficient with statistics to ensure you do statistical procedures appropriately. Learning statistical procedures and analyzing data takes many years of practice, and your statistics courses may only cover the basics. You will need to know when to consult others for help. In addition to consulting members in your lab or your PI, your university may have statistical experts who can provide consultations.

5. Master pressure to obtain favored results

When you conduct an experiment, the results are the results. As a beginning researcher, it is important to be prepared to manage the frustration of experiments not turning out as expected. It is also important to manage the real or perceived pressure to produce favored results. Investigators can become wedded to a hypothesis, and they can have a difficult time accepting the results. Sometimes you may feel this pressure coming from yourself; for example, if you want to please your PI, or if you want to get results for a certain publication. It is important to always follow the data no matter where it leads.

If you do feel pressure, this situation can be uncomfortable and stressful. If you have been meticulous and followed the above recommendations, this can be one great safeguard. You will be better able to confidently communicate your results to the PI because of your detailed documentation, and you will be more confident in your procedures if the possibility of error is suggested. Typically, with enough evidence that the unexpected results are real, the PI will concede. We recommend seeking the support of friends or colleagues to vent and cope with stress. In the rare case that the PI does not relent, you could turn to an advisor outside the lab if you need advice about how to proceed. They can help you look at the data objectively and also help you think about the interpersonal aspects of navigating this situation.

6. Communicate about your data in the lab

A critical element of reproducible research is communication in the lab. Ideally, there are weekly or bi-weekly meetings to discuss data. You need to develop your communication skills for writing and speaking about data. Often you and your labmates will discuss experimental issues and results informally during the course of daily work. This is an excellent way to hone critical thinking and communication skills about data.

Scenario 1 – The Protocol is Not Working

At the beginning of a rotation during their first year, a graduate student is handed a lab notebook and a pen and is told to keep track of their work. There does not appear to be a specific format to follow. There are standard lab protocols that everyone follows, but minor tweaks to the protocols do not seem to be tracked from experiment to experiment in the standard lab protocol nor in other lab notebooks. After two weeks of trying to follow one of the standard lab protocols, the student still cannot get the experiment to work. The student has included the appropriate positive and negative controls which are failing, making the experiment uninterpretable. After asking others in the lab for help, the graduate student learns that no one currently in the lab has performed this particular experiment. The former lab member who had performed the experiment only lists the standard protocol in their lab notebook.

How should the graduate student start to solve the problem?

Speaking to the PI would be the next logical step. As a first-year student in a lab rotation, the PI should expect this type of situation and provide additional troubleshooting guidance. It is possible that the PI may want to see how the new graduate student thinks critically and handles adversity in the lab. Rather than giving an answer, the PI might ask the student to work through the problem. The PI should give guidance, but it may not be an immediate fix for the problem. If the PI’s suggestions fail to correct the problem, asking a labmate or the PI for the contact information of the former lab member who most recently performed the experiment would be a reasonable next step. The graduate student’s conversations with the PI and labmates in this situation will help them learn a lot about how the people in the lab interact.

Most of the answers for these types of problems will require you as a graduate student to take the initiative to answer. They will require your effort and ingenuity to talk to other lab members, other labs at the university, and even scour the literature for alternatives. While labs have standard protocols, there are multiple ways to do many experiments, and working out an alternative will teach you more than when everything works. Having to troubleshoot problems will result in better standard protocols in the lab and better science.

HOW TO BE A RESPONSIBLE AUTHOR

Researchers communicate their findings via peer-reviewed publications, and publications are important for advancing in a research career. Many graduate students will first author or co-author publications in graduate school. For good advice on how to write a research manuscript, consult the Current Protocols article “How to write a research manuscript” ( Frank, 2018 ). We focus on the issues of assigning authors and reporting your findings responsibly. First, we describe some important basics: journal impact factors, predatory journals, and peer review.

What are journal impact factors?

It is helpful to understand journal impact factors. There is criticism about an overemphasis on impact factors for evaluating the quality or importance of researchers’ work ( DePellegrin & Johnston, 2015 ), but they remain common for this purpose. Journal impact factors reflect the average number of times articles in a journal were cited in the last two years. Higher impact factors place journals at a higher rank. Approximately 2% of journals have an impact factor of 10 or higher. For example, Cell, Science, and Nature have impact factors of approximately 39, 42, and 43, respectively. Journals can be great journals but have lower impact factors; often this is because they focus on a smaller specialty field. For example, Journal of Immunology and Oncogene are respected journals, but their impact factors are about 4 and 7, respectively.

Research trainees often want to publish in journals with the highest possible impact factor because they expect this to be viewed favorably when applying to future positions. We encourage you to bear in mind that many different journals publish excellent science and focus on publishing where your work will reach the desired audience. Also, keep in mind that while a high impact factor can direct you to respectable, high-impact science, it does not guarantee that the science in the paper is good or even correct. You must critically evaluate all papers you read no matter the impact factor.

What are predatory journals?

Predatory journals have flourished over the past few years as publishing science has moved online. An international panel defined predatory journals as follows ( Grudniewicz et al., 2019 ):

Predatory journals and publishers are entities that prioritize self-interest at the expense of scholarship and are characterized by false or misleading information, deviation from best editorial and publication practices, a lack of transparency, and/or the use of aggressive and indiscriminate solicitation practices. (p. 211)

Often young researchers receive emails soliciting them to submit their work to a journal. There are typically small fees (around $99 US) requested but these fees will be much lower than open access fees of reputable journals (often around $2000 US). A warning sign of a predatory journal is outlandish promises, such as 24-hour peer review or immediate publication. You can find a list of predatory journals created by a postdoc in Europe at BeallsList.net ( “Beall’s List of Potential Predatory Journals and Publishers,” 2020 ).

What is peer review?

Peer reviewers are other scientists who have the expertise to evaluate a manuscript. Typically 2 or 3 reviewers evaluate a manuscript. First, an editor performs an initial screen of the manuscript to ensure its appropriateness for the journal and that it meets basic quality standards. At this stage, an editor can decide to reject the manuscript and not send it to review. Not sending a paper for peer review is common in the highest impact journals that receive more submissions per year than can be reviewed and published. For average-impact journals and specialty journals, typically your paper will be sent for peer review.

In general, peer review focuses on three aspects of a manuscript: research design and methods, validity of the data and conclusions, and significance. Peer reviewers assess the merit and rigor of the research design and methodology, and they evaluate the overall validity of the results, interpretations, and conclusions. Essentially, reviewers want to ensure that the data support the claims. Additionally, reviewers evaluate the overall significance, or contribution, of the findings, which involves the novelty of the research and the likelihood that the findings will advance the field. Significance standards vary between journals. Some journals are open to publishing findings that are incremental advancements in a field, while others want to publish only what they deem as major advancements. This feature can distinguish the highest impact journals which seek the most significant advancements and other journals that tend to consider a broader range of work as long as it is scientifically sound. It is important to keep in mind that determining at the stage of review and publication whether a paper is “high impact” is quite subjective. In reality, this can only really be determined in retrospect.

The key ethical issues in peer review are fairness, objectivity, and confidentiality ( Shamoo & Resnik, 2015 ). Peer reviewers are to evaluate the manuscript on its merits and not based on biases related to the authors or the science itself. If reviewers have a conflict of interest, this should be disclosed to the editor. Confidentiality of peer review means that the reviewers should keep private the information; they should not share the information with others or use it to their benefit. Reviewers can ultimately recommend that the manuscript is rejected, revised, and resubmitted (major or minor revisions), or accepted. The editor evaluates the reviewers’ feedback and makes a judgment about rejecting, accepting, or requesting a revision. Sometimes PIs will ask experienced graduate students to assist with peer reviewing a manuscript. This is a good learning opportunity. The PI should disclose to the editor that they included a trainee in preparing the review.

Assign authorship fairly

Authorship gives credit to the people who contributed to the research. This includes thinking of the ideas, designing and performing experiments, interpreting the results, and writing the paper. Two key questions regarding authorship include: 1 - Who will be an author? 2 - What will be the order in which authors are listed? These seem simple on the surface but can get quite complex.

1. Know authorship guidelines

Authorship guidelines published by journals, professional societies, and universities communicate key principles of authorship and standards for earning authorship. The core ethical principle of assigning authorship is fairness in who receives credit for the work. The people who contributed to the work should get credit for it. This seems simply enough, but determining authorship can (and often does) create conflict.

Many universities have authorship guidelines, and you should know the policies at your university. The International Committee of Medical Journal Editors (ICMJE) provides four criteria for determining who should be an author ( International Committee of Medical Journal Editors, 2020 ). These criteria indicate that an author should do all of the following: 1) make “substantial contributions” to the development of the idea or research design, or to acquiring, analyzing, or interpreting the data, 2) write the manuscript or revise it a substantive way, 3) give approval of the final manuscript (i.e., before it is submitted for review, and after it is revised, if necessary), and 4) agree to be responsible for any questions about the accuracy or integrity of the research.

Several types of authorship violate these guidelines and should be avoided. Guest authorship is when respected researchers are added out of appreciation, or to have the manuscript be perceived more favorably to get it published or increase its impact. Gift authorship is giving authorship to reward an individual, or as a favor. Ghost authorship is when someone made significant contributions to the paper but is not listed as an author. To increase transparency, some journals require authors to indicate how each individual contributed to the research and manuscript.

2. Apply the guidelines

Conflicts often arise from disagreements about how much people contributed to the research and whether those contributions merit authorship. The best approach is an open, honest, and ongoing discussion about authorship, which we discuss in #3 below. To have effective, informed conversations about authorship, you must understand how to apply the guidelines to your specific situation. The following is a simple rule of thumb that indicates there are three components of authorship. We do not list giving final approval of the manuscript and agreeing to be accountable, but we do consider these essentials of authorship.

• Thinking – this means contributing to the ideas leading to the hypothesis of the work, designing experiments to address the hypothesis, and/or analyzing the results in the larger context of the literature in the field.
• Doing – this means performing and analyzing the experiments.
• Writing – this means editing a draft, or writing the entire paper. The first author often writes the entire first draft.

In our experience, a first author would typically do all three. They also usually coordinate the writing and editing process. Co-authors are typically very involved in at least two of the three, and are somewhat involved in the other. The PI, who oversees and contributes to all three, is often the last, or “senior author.” The “senior author” is typically the “corresponding author”—the person listed as the individual to contact about the paper. The other co-authors are listed between the first and senior author either alphabetically, or more commonly, in order from the largest to smallest contribution.

Problems in assigning authorship typically arise due to people’s interpretations of #1 (thinking) and #2 (doing)—what and how much each individual contributed to a project’s design, execution, and analysis. Different fields or PIs may have their own slight variations on these guidelines. The potential conflicts associated with assigning authorship lead to the most common recommendation for responsibly assigning authorship: discuss authorship expectations early and revisit them during the project.

3. Discuss authorship with your collaborators

Publications are important for career advancement, so you can see why people might be worried about fairness in assigning authorship. If the problem arises from a lack of a shared understanding about contributions to the research, the only way to clarify this is an open discussion. This discussion should ideally take place very early at the beginning of a project, and should be ongoing. Hopefully you work in a laboratory that makes these discussions a natural part of the research process; this makes it much easier to understand the expectations upfront.

We encourage you to speak up about your interest in making a contribution that would merit authorship, especially if you want to earn first authorship. Sometimes norms about authoring papers in a lab make it clear you are expected to first and co-author publications, but it is best to communicate your interest in earning authorship. If the project is not yours, but you wish to collaborate, you can inquire what you may be able to contribute that would merit authorship.

If it is not a norm in your lab to discuss authorship throughout the life of projects, then as a graduate student you may feel reluctant to speak up. You could initiate a conversation with a more senior graduate student, a postdoc, or your PI, depending on the dynamics in the group. You could ask generally about how the lab approaches assignment of authorship, but discussing a specific project and paper may be best. It may feel awkward to ask, but asking early is less uncomfortable than waiting until the end of the project. If the group is already drafting a manuscript and you are told that your contribution is insufficient for authorship, this situation is much more discouraging than if you had asked earlier about what is expected to earn authorship.

How to report findings responsibly

The most significant responsibility of authors is to present their research accurately and honestly. Deliberately presenting misleading information is clearly unethical, but there are significant judgment calls about how to present your research findings. For example, an author can mislead by overstating the conclusions given what the data support.

1. Commit to presenting your findings honestly

Any good scientific manuscript writer will tell you that you need to “tell a good story.” This means that your paper is organized and framed to draw the reader into the research and convince them of the importance of the findings. But, this story must be sound and justified by the data. Other authors are presenting their findings in the best, most “publishable” light, so it is a balancing act to be persuasive but also responsible in presenting your findings in a trustworthy manner. To present your findings honestly, you must be conscious of how you interpret your data and present your conclusions so that they are accurate and not overstated.

One misbehavior known as “HARKing,” Hypothesis After the Results are Known, occurs when hypotheses are created after seeing the results of an experiment, but they are presented as if they were defined prior to collecting the data ( Munafò et al., 2017 ). This practice should be avoided. HARKing may be driven, in part, by a concern in scientific publishing known as publication bias. This bias is a preference that reviewers, editors, and researchers have for papers describing positive findings instead of negative findings ( Carroll, Toumpakari, Johnson, & Betts, 2017 ). This preference can lead to manipulating one’s practices, such as by HARKing, so that positive findings can be reported.

It is important to note that in addition to avoiding misbehaviors such as HARKing, all researchers are susceptible to a number of more subtle traps in judgment. Even the most well-intentioned researcher may jump to conclusions, discount alternative explanations, or accept results that seem correct without further scrutiny ( Nuzzo, 2015 ). Therefore, researchers must not only commit to presenting their findings honestly but consider how they can counteract such traps by slowing down and increasing their skepticism towards their findings.

2. Provide an appropriate amount of detail

Providing enough detail in a manuscript can be a challenge with the word limits imposed by most journals. Therefore, you will need to determine what details to include and which to exclude, or potentially include in the supplemental materials. Methods sections can be long and are often the first to be shortened, but complete methods are important for others to evaluate the research and to repeat the methods in other studies. Even more significant is making decisions about what experimental data to include and potentially exclude from the manuscript. Researchers must determine what data is required to create a complete scientific story that supports the central hypothesis of the paper. On the other hand, it is not necessary or helpful to include so much data in the manuscript, or in supplemental material, that the central point of the paper is difficult to discern. It is a tricky balance.

3. Follow proper citation practices

Of course, responsible authorship requires avoiding plagiarism. Many researchers think that plagiarism is not a concern for them because they assume it is always done intentionally by “copying and pasting” someone else’s words and claiming them as your own. Sometimes poor writing practices, such as taking notes from references without distinguishing between direct quotes and paraphrased material, can lead to including material that is not quoted properly. More broadly, proper citation practices include accurately and completely referencing prior studies to provide appropriate context for your manuscript.

4. Attend to the other important details

The journal will require several pieces of additional information, such as disclosure of sources of funding and potential conflicts of interest. Typically, graduate students do not have relationships that constitute conflicts of interest, but a PI who is a co-author may. In submitting a manuscript, also make sure to acknowledge individuals not listed as authors but who contributed to the work.

5. Share data and promote transparency

Data sharing is a key facet of promoting transparency in science ( Nosek et al., 2015 ). It will be important to know the expectations of the journals in which you wish to publish. Many top journals now require data sharing; for example, sharing your data files in an online repository so others have access to the data for secondary use. Funding agencies like NIH also increasingly require data sharing. To further foster transparency and public trust in research, researchers must deposit their final peer-reviewed manuscripts that report on research funded by NIH to PubMed Central. PubMed makes biomedical and life science research publicly accessible in a free, online database.

Scenario 2 – Authors In Conflict

To prepare a manuscript for publication, a postdoc’s data is added to a graduate student’s thesis project. After working together to combine the data and write the paper, the postdoc requests co-first authorship on the paper. The graduate student balks at this request on the basis that it is their thesis project. In a weekly meeting with the lab’s PI to discuss the status of the paper, the graduate student states that they should divide the data between the authors as a way to prove that the graduate student should be the sole first author. The PI agrees to this attempt to quantify how much data each person contributed to the manuscript. All parties agree the writing and thinking were equally shared between them. After this assessment, the graduate student sees that the postdoc actually contributed more than half of the data presented in the paper. The graduate student and a second graduate student contributed the remaining data; this means the graduate student contributed much less than half of the data in the paper. However, the graduate student is still adamant that they must be the sole first author of the paper because it is their thesis project.

Is the graduate student correct in insisting that it is their project, so they are entitled to be the sole first author?

Co-first authorship became popular about 10 years ago as a way to acknowledge shared contributions to a paper in which authors worked together and contributed equally. If the postdoc contributed half of the data and worked with the graduate student to combine their interpretations and write the first draft of the paper, then the postdoc did make a substantial contribution. If the graduate student wrote much of the first draft of the paper, contributed significantly to the second half of data, and played a major role in the thesis concept and design, this is also a major contribution. We summarized authorship requirements as contributing to thinking, doing, and writing, and we noted that a first author usually contributes to all of these. The graduate student has met all 3 elements to claim first authorship. However, it appears that the postdoc has also met these 3 requirements. Thus, it is at least reasonable for the postdoc to ask about co-first authorship.

The best way to move forward is to discuss their perspectives openly. Both the graduate student and postdoc want first authorship on papers to advance their careers. The postdoc feels they contributed more to the overall concept and design than the graduate student is recognizing, and the postdoc did contribute half of the data. This is likely frustrating and upsetting for the postdoc. On the other hand, perhaps the postdoc is forgetting how much a thesis becomes like “your baby,” so to speak. The work is the graduate student’s thesis, so it is easy to see why the graduate student would feel a sense of ownership of it. Given this fact, it may be hard for the graduate student to accept the idea that they would share first-author recognition for the work. Yet, the graduate student should consider that the manuscript would not be possible without the postdoc’s contribution. Further, if the postdoc was truly being unreasonable, then the postdoc could make the case for sole first authorship based on contributing the most data to the paper, in addition to contributing ideas and writing the paper. The graduate student should consider that the postdoc may be suggesting co-first authorship in good faith.

As with any interpersonal conflict, clear communication is key. While it might be temporarily uncomfortable to voice their views and address this disagreement, it is critical to avoiding permanent damage to their working relationship. The pair should consider each other’s perspectives and potential alternatives. For example, if the graduate student is first author and the postdoc second, at a minimum they could include an author note in the manuscript that describes the contribution of each author. This would make it clear the scope of the postdoc’s contribution, if they decided not to go with co-first authorship. Also, the graduate student should consider their assumptions about co-first authorship. Maybe they assume it makes it appear they contributed less, but instead, perhaps co-first authorship highlights their collaborative approach to science. Collaboration is a desirable quality many (although arguably not all) research organizations look for when they are hiring.

They will also need to speak with others for advice. The pair should definitely speak with the PI who could provide input about how these cases have been handled in the past. Ultimately, if they cannot reach an agreement, the PI, who is likely to be the last or “senior” author, may make the final decision. They should also speak to the other graduate student who is an author.

If either individual is upset with the situation, they will want to discuss it when they have had time to cool down. This might mean taking a day before discussing, or speaking with someone outside of the lab for support. Ideally, all authors on this paper would have initiated this conversation earlier, and the standards in the lab for first authorship would be discussed routinely. Clear communication may have avoided the conflict.

HOW TO USE DECISION-MAKING STRATEGIES TO NAVIGATE CHALLENGES

We have provided advice on some specific challenges you might encounter in research. This final section covers our overarching recommendation that you adopt a set of ethical decision-making strategies. These strategies help researchers address challenges by helping them think through a problem and possible alternatives ( McIntosh et al., 2020 ). The strategies encourage you to gather information, examine possible outcomes, consider your assumptions, and address emotional reactions before acting. They are especially helpful when you are uncertain how to proceed, face a new problem, or when the consequences of a decision could negatively impact you or others. The strategies also help people be honest with themselves, such as when they are discounting important factors or have competing goals, by encouraging them to identify outside perspectives and test their motivations. You can remember the strategies using the acronym SMART .

1. S eek Help

Obtain input from others who can be objective and that you trust. They can assist you with assessing the situation, predicting possible outcomes, and identifying potential options. They can also provide you with support. Individuals to consult may be peers, other faculty, or people in your personal life. It is important that you trust the people you talk with, but it is also good when they challenge your perspective, or encourage you to think in a new way about a problem. Keep in mind that people such as program directors and university ombudsmen are often available for confidential, objective advice.

2. M anage Emotions

Consider your emotional reaction to the situation and how it might influence your assessment of the situation, and your potential decisions and actions. In particular, identify negative emotions, like frustration, anxiety, fear, and anger, as they particularly tend to diminish decision-making and the quality of interactions with others. Take time to address these emotions before acting, for example, by exercising, listening to music, or simply taking a day before responding.

3. A nticipate Consequences

Think about how the situation could turn out. This includes for you, for the research team, and anyone else involved. Consider the short, middle-term, and longer-term impacts of the problem and your potential approach to addressing the situation. Ideally, it is possible to identify win-win outcomes. Often, however, in tough professional situations, you may need to select the best option from among several that are not ideal.

4. R ecognize Rules and Context

Determine if any ethical principles, professional policies, or rules apply that might help guide your choices. For instance, if the problem involves an authorship dispute, consider the authorship guidelines that apply. Recognizing the context means considering the situational factors that could impact your options and how you proceed. For example, factors such as the reality that ultimately the PI may have the final decision about authorship.

5. T est Assumptions and Motives

Examine your beliefs about the situation and whether any of your thoughts may not be justified. This includes critically examining the personal motivations and goals that are driving your interpretation of the problem and thoughts about how to resolve it.

These strategies do not have to be engaged in order, and they are interrelated. For example, seeking help can help you manage emotions, test assumptions, and anticipate consequences. Go back to the scenarios and our advice throughout this article, and you will see many of our suggestions align with these strategies. Practice applying SMART strategies when you encounter a problem and they will become more natural.

Learning practices for responsible research will be the foundation for your success in graduate school and your career. We encourage you to be reflective and intentional as you learn and hope that our advice helps you along the way.

ACKNOWLEDGEMENTS

This work was supported by the National Human Genome Research Institute (Antes, K01HG008990) and the National Center for Advancing Translational Sciences (UL1 TR002345).

LITERATURE CITED

• Anderson MS, Horn AS, Risbey KR, Ronning EA, De Vries R, & Martinson BC (2007). What Do Mentoring and Training in the Responsible Conduct of Research Have To Do with Scientists’ Misbehavior? Findings from a National Survey of NIH-Funded Scientists . Academic Medicine , 82 ( 9 ), 853–860. doi: 10.1097/ACM.0b013e31812f764c [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Antes AL, Brown RP, Murphy ST, Waples EP, Mumford MD, Connelly S, & Devenport LD (2007). Personality and Ethical Decision-Making in Research: The Role of Perceptions of Self and Others . Journal of Empirical Research on Human Research Ethics , 2 ( 4 ), 15–34. doi: 10.1525/jer.2007.2.4.15 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Antes AL, English T, Baldwin KA, & DuBois JM (2018). The Role of Culture and Acculturation in Researchers’ Perceptions of Rules in Science . Science and Engineering Ethics , 24 ( 2 ), 361–391. doi: 10.1007/s11948-017-9876-4 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Antes AL, Kuykendall A, & DuBois JM (2019a). The Lab Management Practices of “Research Exemplars” that Foster Research Rigor and Regulatory Compliance: A Qualitative Study of Successful Principal Investigators . PloS One , 14 ( 4 ), e0214595. doi: 10.1371/journal.pone.0214595 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Antes AL, Kuykendall A, & DuBois JM (2019b). Leading for Research Excellence and Integrity: A Qualitative Investigation of the Relationship-Building Practices of Exemplary Principal Investigators . Accountability in Research , 26 ( 3 ), 198–226. doi: 10.1080/08989621.2019.1611429 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Antes AL, & Maggi LB Jr. (2021). How to Navigate Trainee-Mentor Relationships and Interpersonal Dynamics in the Lab . Current Protocols Essential Laboratory Techniques. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Asplund M, & Welle CG (2018). Advancing Science: How Bias Holds Us Back . Neuron , 99 ( 4 ), 635–639. doi: 10.1016/j.neuron.2018.07.045 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Baker M (2016). Is There a Reproducibility Crisis? Nature , 533 , 452–454. doi: 10.1038/533452a [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Barba LA (2016). The Hard Road to Reproducibility . Science , 354 ( 6308 ), 142. doi: 10.1126/science.354.6308.142 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Beall’s List of Potential Predatory Journals and Publishers . (2020). Retrieved from https://beallslist.net/#update [ Google Scholar ]
• Carroll HA, Toumpakari Z, Johnson L, & Betts JA (2017). The Perceived Feasibility of Methods to Reduce Publication Bias . PloS One , 12 ( 10 ), e0186472–e0186472. doi: 10.1371/journal.pone.0186472 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chappell B (2019). Duke Whistleblower Gets More Than $33 Million in Research Fraud Settlement . NPR. Retrieved from https://www.npr.org/2019/03/25/706604033/duke-whistleblower-gets-more-than-33-million-in-research-fraud-settlement [ Google Scholar ]
• Davis MS, Riske-Morris M, & Diaz SR (2007). Causal Factors Implicated in Research Misconduct: Evidence from ORI Case Files . Science and Engineering Ethics , 13 ( 4 ), 395–414. doi: 10.1007/s11948-007-9045-2 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• DeMets DL (1999). Statistics and Ethics in Medical Research . Science and Engineering Ethics , 5 ( 1 ), 97–117. doi: 10.1007/s11948-999-0059-9 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Department of Health and Human Services. (2005). 42 CFR Parts 50 and 93 Public Health Service Policies on Research Misconduct; Final Rule. Retrieved from https://ori.hhs.gov/sites/default/files/42_cfr_parts_50_and_93_2005.pdf [ Google Scholar ]
• DePellegrin TA, & Johnston M (2015). An Arbitrary Line in the Sand: Rising Scientists Confront the Impact Factor . Genetics , 201 ( 3 ), 811–813. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• DuBois JM, Anderson EE, Chibnall J, Carroll K, Gibb T, Ogbuka C, & Rubbelke T (2013). Understanding Research Misconduct: A Comparative Analysis of 120 Cases of Professional Wrongdoing . Account Res , 20 ( 5–6 ), 320–338. doi: 10.1080/08989621.2013.822248 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• DuBois JM, & Antes AL (2018). Five Dimensions of Research Ethics: A Stakeholder Framework for Creating a Climate of Research Integrity . Academic Medicine , 93 ( 4 ), 550–555. doi: 10.1097/ACM.0000000000001966 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Else H (2018). Does Science have a Bullying Problem? Nature , 563 , 616–618. doi: 10.1038/d41586-018-07532-5 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Emanuel EJ, Wendler D, & Grady C (2000). What Makes Clinical Research Ethical ? Journal of the American Medical Association , 283 ( 20 ), 2701–2711. doi:jsc90374 [pii] [ PubMed ] [ Google Scholar ]
• Evans TM, Bira L, Gastelum JB, Weiss LT, & Vanderford NL (2018). Evidence for a Mental Health Crisis in Graduate Education . Nature Biotechnology , 36 ( 3 ), 282–284. doi: 10.1038/nbt.4089 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Frank DJ (2018). How to Write a Research Manuscript . Current Protocols Essential Laboratory Techniques , 16 ( 1 ), e20. doi: 10.1002/cpet.20 [ CrossRef ] [ Google Scholar ]
• Goodman SN, Fanelli D, & Ioannidis JPA (2016). What Does Research Reproducibility Mean? Science Translational Medicine , 8 ( 341 ), 341ps312. doi: 10.1126/scitranslmed.aaf5027 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Grudniewicz A, Moher D, Cobey KD, Bryson GL, Cukier S, Allen K, … Lalu MM (2019). Predatory journals: no definition, no defence . Nature , 576 ( 7786 ), 210–212. doi: 10.1038/d41586-019-03759-y [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Head ML, Holman L, Lanfear R, Kahn AT, & Jennions MD (2015). The Extent and Consequences of P-Hacking in Science . PLoS Biology , 13 ( 3 ), e1002106. doi: 10.1371/journal.pbio.1002106 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hofstra B, Kulkarni VV, Munoz-Najar Galvez S, He B, Jurafsky D, & McFarland DA (2020). The Diversity–Innovation Paradox in Science . Proceedings of the National Academy of Sciences , 117 ( 17 ), 9284. doi: 10.1073/pnas.1915378117 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• International Committee of Medical Journal Editors. (2020). Defining the Role of Authors and Contributors . Retrieved from http://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html
• Keith-Spiegel P, Sieber J, & Koocher GP (2010). Responding to Research Wrongdoing: A User-Friendly Guide . Retrieved from http://users.neo.registeredsite.com/1/4/0/20883041/assets/RRW_11-10.pdf
• McIntosh T, Antes AL, & DuBois JM (2020). Navigating Complex, Ethical Problems in Professional Life: A Guide to Teaching SMART Strategies for Decision-Making . Journal of Academic Ethics . doi: 10.1007/s10805-020-09369-y [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Meyers LC, Brown AM, Moneta-Koehler L, & Chalkley R (2018). Survey of Checkpoints along the Pathway to Diverse Biomedical Research Faculty . PloS One , 13 ( 1 ), e0190606–e0190606. doi: 10.1371/journal.pone.0190606 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Munafò MR, Nosek BA, Bishop DVM, Button KS, Chambers CD, Percie du Sert N, … Ioannidis JPA (2017). A manifesto for reproducible science . Nature Human Behaviour , 1 ( 1 ), 0021. doi: 10.1038/s41562-016-0021 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• National Academies of Science. (2009). On Being a Scientist: A Guide to Responsible Conduct in Research . Washington DC: National Academics Press. [ PubMed ] [ Google Scholar ]
• National Academies of Sciences Engineering and Medicine. (2017). Fostering Integrity in Research . Washington, DC: The National Academies Press [ PubMed ] [ Google Scholar ]
• National Academies of Sciences Engineering and Medicine. (2018a). An American Crisis: The Growing Absence of Black Men in Medicine and Science: Proceedings of a Joint Workshop . Washington, DC: The National Academies Press. [ PubMed ] [ Google Scholar ]
• National Academies of Sciences Engineering and Medicine. (2018b). Sexual harassment of women: climate, culture, and consequences in academic sciences, engineering, and medicine : National Academies Press. [ PubMed ] [ Google Scholar ]
• National Institutes of Health. (2009). Update on the Requirement for Instruction in the Responsible Conduct of Research . NOT-OD-10-019 . Retrieved from https://grants.nih.gov/grants/guide/notice-files/NOT-OD-10-019.html
• National Science Foundation. (2017). Important Notice No. 140 Training in Responsible Conduct of Research – A Reminder of the NSF Requirement . Retrieved from https://www.nsf.gov/pubs/issuances/in140.jsp
• No Place for Bullies in Science. (2018). Nature , 559 ( 7713 ), 151. doi: 10.1038/d41586-018-05683-z [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Norris D, Dirnagl U, Zigmond MJ, Thompson-Peer K, & Chow TT (2018). Health Tips for Research Groups . Nature , 557 , 302–304. doi: 10.1038/d41586-018-05146-5 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nosek BA, Alter G, Banks GC, Borsboom D, Bowman SD, Breckler SJ, … Yarkoni T (2015). Scientific Standards . Promoting an Open Research Culture. Science , 348 ( 6242 ), 1422–1425. doi: 10.1126/science.aab2374 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Nuzzo R (2015). How Scientists Fool Themselves - and How They Can Stop . Nature , 526 , 182–185. [ PubMed ] [ Google Scholar ]
• O’Connor A (2018). More Evidence that Nutrition Studies Don’t Always Add Up . The New York Times. Retrieved from https://www.nytimes.com/2018/09/29/sunday-review/cornell-food-scientist-wansink-misconduct.html [ Google Scholar ]
• Park A (2012). Great Science Frauds . Time. Retrieved from https://healthland.time.com/2012/01/13/great-science-frauds/slide/the-baltimore-case/ [ Google Scholar ]
• Plemmons DK, Baranski EN, Harp K, Lo DD, Soderberg CK, Errington TM, … Esterling KM (2020). A Randomized Trial of a Lab-embedded Discourse Intervention to Improve Research Ethics . Proceedings of the National Academy of Sciences , 117 ( 3 ), 1389. doi: 10.1073/pnas.1917848117 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Research Institutions Must Put the Health of Labs First. (2018). Nature , 557 ( 7705 ), 279–280. doi: 10.1038/d41586-018-05159-0 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Research Integrity is Much More Than Misconduct . (2019). ( 570 ). doi: 10.1038/d41586-019-01727-0 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Resnik DB (2011). Scientific Research and the Public Trust . Science and Engineering Ethics , 17 ( 3 ), 399–409. doi: 10.1007/s11948-010-9210-x [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Roper RL (2019). Does Gender Bias Still Affect Women in Science? Microbiology and Molecular Biology Reviews , 83 ( 3 ), e00018–00019. doi: 10.1128/MMBR.00018-19 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Shamoo AE, & Resnik DB (2015). Responsible Conduct of Research (3rd ed.). New York: Oxford University Press. [ Google Scholar ]
• Steneck NH (2007). ORI Introduction to the Responsible Conduct of Research (Updated ed.). Washington, D.C.: U.S. Government Printing Office. [ Google Scholar ]
• Winchester C (2018). Give Every Paper a Read for Reproducibility . Nature , 557 , 281. doi: 10.1038/d41586-018-05140-x [ PubMed ] [ CrossRef ] [ Google Scholar ]

What is a related work? A typology of relationships in research literature

• Original Research
• Open access
• Published: 09 January 2023
• Volume 201 , article number  24 , ( 2023 )

Cite this article

You have full access to this open access article

• Shayan Doroudi   ORCID: orcid.org/0000-0002-0602-1406 1  

2282 Accesses

2 Altmetric

Explore all metrics

An important part of research is situating one’s work in a body of existing literature, thereby connecting to existing ideas. Despite this, the various kinds of relationships that might exist among academic literature do not appear to have been formally studied. Here I present a graphical representation of academic work in terms of entities and relations, drawing on structure-mapping theory (used in the study of analogies). I then use this representation to present a typology of operations that could relate two pieces of academic work. I illustrate the various types of relationships with examples from medicine, physics, psychology, history and philosophy of science, machine learning, education, and neuroscience. The resulting typology not only gives insights into the relationships that might exist between static publications, but also the rich process whereby an ongoing research project evolves through interactions with the research literature.

Similar content being viewed by others

Understanding Research Dynamics

The evolution of knowledge within and across fields in modern physics

Introduction

Explore related subjects.

• Artificial Intelligence

Avoid common mistakes on your manuscript.

1 Introduction

An important part of the research process is literature search: identifying prior work that is of relevance to the present idea being investigated. In many cases, this is an activity that a researcher may defer until writing up the results of the project, in which case, it is primarily an activity one does because one “has to” rather than an activity that can substantially change the course of the research. In some cases, whether due to negligence or the difficulty of finding related works, a researcher may never come across the fact that someone had previously tackled the same problem or made a similar discovery, and perhaps only years later (if ever) it may be realized (Merton, 1963 ; Ke et al., 2015 ; Sacks, 2002 ). But at its best, this is an activity that leads to new insights into the research problem, generates new ideas, and alters the course of the research. In fact, in some cases, searching for related work can become the research process itself; through connecting various pieces of research literature alone, one can discover previously undiscovered public knowledge (Swanson, 1986 ).

Despite the importance of prior literature in the research process, there has been little effort, if any, dedicated to developing a typology of related works, that is, a typology of relationships that might exist among different pieces of research literature. (Of course, it is entirely possible that such a typology has been constructed, but I have missed it due to an inadequate search of the literature!) In this paper, I propose such a typology to help us better understand the kinds of prior work that might have bearing on a research project. I first present a form of knowledge representation that can theoretically be used to represent any piece of research literature or research project. I then present a typology of relationships that can connect two pieces of research in terms of operations that can apply to the two representations, thereby resulting in a representation of the relationship. I will demonstrate the various operations and how they might be employed with a variety of examples from different fields, including medicine, physics, psychology, history and philosophy of science, machine learning, education, and neuroscience. The same form of representation applies to both published research literature and research projects or topics, whether nascent or fully-fledged. In fact, some of the relationships discussed below make more sense in the context of research projects (or broader research agendas) that can dynamically evolve as relevant literature is encountered, rather than research papers whose underlying representations are static. As such, I will use the terms publication, literature, project, and topic somewhat interchangeably.

The specific representation I use is borrowed from structure-mapping theory (Gentner, 1983 ; Falkenhainer et al., 1989 ), which was originally developed as a way to structurally represent analogies. Structure-mapping theory is particularly useful here, both because we can use it when discussing abstractions and analogies, and because the underlying representation can also handle other types of relationships among literature. I could have instead used other forms of knowledge representation, such as conceptual graphs (Sowa, 1976 ), entailment meshes (Pask et al., 1975 ; Pask, 1988 ), or category theoretic representations like ologs (Spivak & Kent, 2012 ). There may be relative advantages to each of these, but the representation used here is both simple and powerful enough to clearly demonstrate the typology. The exact choice of representation may need further consideration if one wants to perform inference on the representations or utilize them in information retrieval tools. For now, we are not concerned with how one might construct these representations or even the fidelity with which it is possible (though we revisit these questions in Sect. 6 ). The possibility that research projects could in theory be represented in the way described below is sufficient to formulate the typology.

While the form of representation and typology presented below may not be directly used in information retrieval tools, I contend that they may be useful in guiding the overall direction that research on such tools might take (e.g., what kinds of papers should a tool search for?). Moreover, the typology may provide some clarity to researchers going through the literature search process for a project. Constructing a graphical representation of one’s paper may be a useful exercise, and can possibly illuminate different searches that are needed to find related work. Seeing how the representation of one’s paper changes over time can also be a useful documentation of the research and literature search process. Beyond such potential practical uses of the typology, I believe it can simply be beneficial to understand the various ways in which one product of research may relate to another. If alongside the physical and social worlds, the world of research literature “also qualifies as an endless frontier” (Swanson, 1986 , p. 115), then our efforts to make sense of the former should be accompanied by efforts to make sense of the latter.

2 Related work on related work

Related work on related work exists in a number of different disciplines. Literature search is central to all research after all! Fittingly, the typology we develop combines research that exists in different, largely isolated, strands.

In the information sciences and medicine, work on “literature-based discovery” (LBD), dating back to Swanson ( 1986 ), is concerned with making new scientific discoveries by establishing novel connections between different pieces of literature. Swanson ( 1986 ) describes literature-based discovery as a form of scientific discovery that takes place in Karl Popper’s world 3—the “world of the products of the human mind” (Popper, 1978 , p. 144)—whereby search functions are likened to scientific theories and the “logic of undiscovered public knowledge” (p. 116) is analogous to the logic of scientific discovery. In doing so, Swanson ( 1986 ) made a contribution to the philosophy of science, though it seems to have not been recognized in the philosophy of science community. A number of different information-retrieval techniques have been proposed to aid in LBD (Smalheiser, 2017 ; Sebastian et al., 2017 ). Some authors have presented categorizations of different types of “undiscovered public knowledge” or different forms of LBD (Davies, 1989 ; Smalheiser, 2017 ). While these categorizations can be useful in aiding researchers who want to perform literature-based discovery, our typology has a somewhat broader scope in that not all related work necessarily results in LBD. LBD is one potential use case of literature search, and its various methods span across the relationships in the typology presented here, as discussed below.

More broadly, in information retrieval, the notion of “relevance” is central, and some researchers have tried to develop theories around what relevance is—typically conceived of as the relationship between an information need and a document (Saracevic, 1975 , 2016 ; Huang & Soergel, 2013 ). Green ( 1995 ) and Huang and Soergel ( 2013 ) pointed out that most discussions of relevance are around “topic matching,” but that this is only one form of relevance. Green and Bean ( 1995 ) then constructed a typology of different notions of relevance, and Huang ( 2009 ) expanded this to a typology consisting of over 200 notions of relevance. Huang ( 2009 ) considers three broad categories of relationships: (1) “What functional role a piece of information plays in the overall structure of a topic,” (2) “How information contributes to users’ reasoning about a topic,” and (3) “How information connects to a topic semantically” (p. 411). As examples of functional roles, an information source might present a solution to a problem, the cause of an effect, etc. As examples of contributing to reasoning, an information source might provide an analogy to the topic or might be used to deduce something about the topic. While this work is very relevant to the present paper, there are two key differences. First, their work is about the broader concept of relevance between information and needs, while this paper focuses on relevance in academic literature. One would expect that many of the kinds of broader relevance typologies would also hold for research publications, but given the particularities of literature search and the role it plays in the broader process of scientific research, it seems worth studying in its own right. Second, these prior typologies largely focus on the variety of semantic relationships between two topics, while the approach we present here views relevance in terms of operations that operate on knowledge representations of topics. In this sense, the typology I present here can express how to relate different research topics in terms of a small number of mathematically precise operations (that are hopefully easy to remember), rather than a plethora of different possible semantic relationships. The two approaches are complementary, but I contend that the approach taken here is more useful for conceptualizing the evolution of a research project over time.

In computer science and artificial intelligence, there has been a recent thread of work on citation recommendation, concerned with identifying relevant citations given a piece of text and possibly other meta-data (e.g., authors, etc.) (Strohman et al., 2007 ; Liang et al., 2011 ; Ren et al., 2014 ; Bhagavatula et al., 2018 ). Interestingly, this work has not really considered automated techniques for LBD, and it does not cite the vast literature on LBD or on relevance. Indeed, most of the work in this area is concerned with topic matching (finding citations that topically overlap). One notable exception is work by Chan et al. ( 2018 ) and Kang et al. ( 2022 ). Chan et al. ( 2018 ) presented a technique that combines crowdsourcing and machine learning to find analogies between different papers. They utilize a “soft” relational schema, a very coarse-grained representation of a research paper; they explicitly avoid using representations like the one described below, because they can be very difficult to construct for many publications. Kang et al. ( 2022 ) built on this work by training deep learning algorithms on the crowdsourced representations of abstracts to be able to automatically detect the “purpose” and “mechanism” of a paper. An analogy in this context is two papers that have a similar underlying purpose but achieve that purpose through a different mechanism. Kang et al. ( 2022 ) used this to prototype an analogical search engine for scientific literature. While their representation may be useful for LBD, I contend that it can only capture certain kinds of relationships between papers, and, as I discuss further below, some of their methods do not appear to actually look for analogies as per the typology we develop below. As such, our typology can potentially be useful in classifying the different kinds of relationships that various existing LBD and citation recommendation methods can uncover, and the kinds of relationships that they cannot.

3 A representation of a research project

In our representation, a research project or publication \(P \in \Pi \) is represented as a set of entities and relations, \(P = (E, \mathcal {R})\) . An entity conceptually represents any specific topic of relevance to the project, usually expressed as a noun or a noun phrase (e.g., DNA, the civil rights movement, high blood pressure, theorems). Notice that entities can come in different degrees of specificity (e.g., theorems vs. Gödel’s first incompleteness theorem); the important thing is that entities across all topics and publications are represented at the same level of granularity. We allow entities to be hierarchically defined as functions of other entities (e.g., the entity “volume of a cup” can be thought of as the “volume of” function applied to “cup”).

Relations define a relationship between some number of entities, such that the predicate \(R(e_1, e_2, \dots , e_n)\) indicates that \(e_1\) , \(e_2\) , ..., \(e_n\) are related as specified by the relation R . Binary relations are perhaps the most common. For example, in the sentence “stress causes high blood pressure”, “causes” is a relation that takes relates two entities (in this case, “stress” and “high blood pressure”). We might represent this as causes (stress, high blood pressure). As an example of a tertiary relation, consider the sentences “ribosomes translate mRNA into sequences of amino acids” and “Arab translators translated Greek texts into Arabic translations”; they could both be said to use the relation x-translates-y-into-z (though if we think the word “translates” has a very different semantic meaning in these two cases, we could suggest there are two different relations at play here). We also allow for unary relations; for example, “blood pressure is high” can be represented as is-high (blood pressure). Unary relations are called attributes in structure-mapping theory and they effectively allow assigning adjectives to entities; for example, high (blood pressure) would mean “high blood pressure.” With slight abuse of notation, I will use unary relations both as relations (e.g., is-high (blood pressure)) and as attributes (e.g., high (blood pressure)). Finally, we allow for higher-order relations, which take relations as input instead of, or in addition to, entities. causes is a higher-order relation because we can say, for example, causes ( provided ( treatment (subjects), New Curriculum), learn-more-than ( treatment (subjects), control (subjects))).

As with Gentner’s ( 1983 ) structure-mapping theory, the classification of relationships between research has more to do with the structure of the representation (i.e., the presence of certain entities and relations) rather than the semantic meaning of the nodes. However, semantics still play an important role in informing whether a particular relationship is sensible or important in a particular situation. That is, someone without a semantic understanding of a given domain can still apply the operators described below in the sense that one can execute \(4 + 7\) and \(4 \times 7\) , without regard to which operation makes more sense in the given situation. Furthermore, one aspect of semantics is necessary in the application of some of the operators. Namely, there is a general relation, “is a” (or “is an instance of”), which can capture any situation where a particular entity can be categorized as a special case or instance of another entity. Consistent with earlier work on knowledge representation, we will refer to this relation as is-a (Brachman, 1983 ). For example, is-a (Gödel’s first incompleteness theorem, theorem) and is-a (the civil rights movement, historical occurrence). A single entity can be an instance of many entities (e.g., a cat can be considered an animal, a pet, and an Internet phenomenon). The is-a operator is also reflexive (e.g., is-a (cat, cat)). Finally, with slight abuse of notation, we will also have is-a be a higher-order relation that can designate when one relation is an instance of another. For example, is-a ( holds (person, ball), possesses (person, object)), because holding something is a special case of possessing it and a ball is an object. Some of the operators below can only be applied with an understanding of what things are instances of other things; however, when the relationship is more abstract, sometimes even a domain expert will not readily see these connections.

The set of entities and relations that are used in the representation of a research publication will likely not include all entities and relations included in that publication (e.g., all nouns and verbs), but rather they should include the concepts that are focal to that publication. Of course, that is somewhat subjective, but a useful heuristic is to include all entities and relations that are involved in a system of relationships that might be worth providing citations in reference to, as well as any new entities and relations that are being introduced in the paper. For example, in a paper that runs an experiment with seven conditions, the number of seven is probably not an entity that should be included, but in Miller’s ( 1956 ) paper on working memory capacity or a paper on the religious symbolism of the number seven, it likely should be included.

As suggested above, there is no single correct way to represent a research project. In fact, there can be multiple different views of a research project, which induce different representations. Each of these views can be more or less useful depending on how they are to be used. Moreover, even simple relations can be expressed in different ways. For our purposes, there is a relationship between two research projects if there is at least some view of each that permits the relationship. Since we are not concerned with the practical side of how to best represent projects here, we do not worry about how one would go about discovering the “right” views. In practice though, seeing two related papers from the “wrong” viewpoint is one reason why researchers and information retrieval tools might not notice an important relationship.

We can represent these representations graphically using a graph-like structure as shown in Fig.  1 a. Boxes indicate entities, and the text outside of boxes indicate relations. The arrows coming out of a relation point to its arguments in order from left to right. Nested boxes (e.g., “some part of a new thing”) show hierarchically defined entities. For simplicity, we show binary relations as labeled directed edges for asymmetric relations and labeled undirected edges for symmetric relations, as shown in Fig.  1 b.

Examples of how to graphically represent research projects/publications. a An example of a tertiary relation with three entities that would be read as “An old thing can become some part of a new thing through some process.” There are also two unary relations: is-old and is-new . b Two examples of binary relations. The causes relation is asymmetric while the correlated relation is symmetric

This representation could be couched in the language of model-theoretic philosophy of science (Suppes, 1957 , 1960 ), in particular using the partial structures formalism (French, 2000 ; Da Costa & French, 1990 ), which is also often expressed in terms of entities and (partial) relations. Doing so may be appealing since it would connect literature search to an existing framework for discussing scientific theories. The partial structures formalism has also been used in describing analogies and abstractions in science and provides a way to formalize research undergoing change. However, the ideas presented here not only apply to formal scientific theories, but also to non-scientific literature and more nascent representations of scientific topics, and I do not want to associate the typology presented here with a particular interpretation of scientific theories.

4 A typology of related works

We can now describe the different kinds of relationships that can exist between a research project and prior work. Suppose we have a research project \(P = (E_P, \mathcal {R}_P)\) and a piece of literature \(L = (E_L, \mathcal {R}_L)\) . We assume that P is an ongoing project that can potentially change, while L is already published literature and hence static. Below we describe a set of operations that can be used to describe the relationship between P and L . These operations are functions that take the representations of P and L as inputs and output a representation \(\rho \) of the relationship between P and L (as defined by the operation). Since we allow for composing these operations in sequence, some of the operations will actually take as input P , L , and our current representation of the relationship between the two ( \(\rho _i\) ), and will output a modified representation of the relationship ( \(\rho _{i+1}\) ). Moreover, when applying multiple operations in sequence, we may want to keep track of the ongoing relationship, which we can do by merging multiple relationships (i.e., taking the union of entities and the union of relations in the sequence of relationships). After each operation is applied, we can also potentially modify P Footnote 1 , thereby modifying the relationship between P and L as well. The series of operations and modifications reflects the iterative and influential nature of literature search in the research process. The operations, described below, are called intersection, interpretation, expansion, abstraction, reification, analogy, and substitution. Table  1 lists some basic information about the operations, which may be useful when reading the sections below. I do not make any claims that the typology presented here is complete. There might be other operations, or perhaps more useful categorizations of the operations presented here, which can be elucidated upon in future work. In what follows, I will describe each of the operators in words as well as mathematical formalism when needed; readers can safely skip the mathematical formalism and still grasp the key ideas.

4.1 Intersection

The first and probably most prevalent operation is intersection , which outputs a subset of entities that are shared by P and L and a subset of relations shared by the two. Specifically, intersection outputs a representation \(\rho = (E_{PL}, \mathcal {R}_{PL})\) , where \(E_{PL} \subseteq E_P \cap E_L\) and \(\mathcal {R}_{PL} \subseteq \mathcal {R}_P \cap \mathcal {R}_L\) . The exact subset depends on what is determined to be relevant between the two representations. A simple special case of this would be when P and L share just a single entity. For example, suppose P and L both have to do with DNA, but one is about DNA to solve computational problems (Adleman, 1994 ) and the other is about DNA vaccines for coronavirus (Callaway, 2020 ). It is unlikely that these publications have other entities in common. In many such cases, publications are not worth citing, and such an intersection would actually not be relevant. A relationship is worth noting when the degree of overlap is large enough; this can be measured by associating some degree of importance to each entity in P and taking the sum (or some non-linear function) of importances across all the entities in \(\rho \) .

In some cases, overlap in a single entity may be enough to warrant citation or even to alter the course of a research project. For example, one of the examples that Swanson ( 1986 ) gives for undiscovered public knowledge has to do with a potential research publication on the “all swans are white hypothesis,” a hypothesis that states that all swans are white. This hypothesis could be supported inductively if there was a lack of any documented evidence of black swans. As Swanson ( 1986 ) says:

Suppose for the sake of argument that scientists living in a remote part of the world were to publish, in a local wildlife journal, some observations about a family of black swans living on a nearby lake. We suppose further that the report comes from a half-dozen people who are reliable observers, and that they are unaware that other people in the world think that all swans are white. (p. 109)

As shown in Fig.  2 , the potential all-swans-are-white hypothesis publication ( P ) is represented using three entities and two relations, although it can be interpreted as two entities and the relationship between them (“the all-swans-are-white hypothesis is proved by the fact that there is no evidence of black swans”); on the other hand, the article in the wildlife journal ( L ) only concerns itself with black swans and possibly other topics of local interest. As such, the two articles overlap in only one entity: black swans. It just so happens that the existence of black swans is a critical refutation of the theory (i.e., “evidence of black swans” is a very important entity in P ), and so this single article can change the course of the research project (e.g., the authors publish a refutation of the all-swans-are-white hypothesis rather than a proclamation of it).

Notice that the intersection of the two articles was “black swans” not “evidence of black swans.” (The wildlife journal is not trying to present evidence of black swans; it is discussing a piece of wildlife whose existence they never called into question.) The intersection of “black swans” by itself is not necessarily meaningful. Another paper that discusses black swans but provides no evidence for them is of less value to P . How then can we capture the obvious fact that L presents evidence of black swans, even though it is not captured in its representation? The answer lies in the interpretation operation.

Swanson’s ( 1986 ) black swans example as an example of intersection

4.2 Interpretation

An interpretation takes an existing relationship between P and L and adds additional entities and/or relations from P (not included in L ) that can help interpret the current relationship. Namely, if \(\rho _{i} = (E_{\rho _{i}}, \mathcal {R}_{\rho _{i}})\) is the output of a previous operation, then \(\rho _{i+1} = (E_{\rho _{i}} \cup E_{PS}, \mathcal {R}_{\rho _{i}} \cup \mathcal {R}_{PS})\) , where \(E_{PS} \subseteq E_P \setminus E_L\) and \(\mathcal {R}_{PS} \subseteq \mathcal {R}_P \setminus \mathcal {R}_L\) . (I use PS and LS as subscripts to denote subsets of P and L .) A natural use of interpretation is to apply it after an intersection. For example, in the black swans example above, we can interpret the intersection of P and L as being “evidence of black swans.” Clearly, L does present evidence of black swans, but it was not interpreted that way until it was interpreted in light of P . Notice that if a researcher conducting project P were to construct the representation of L , they might do so according to their interpretation, whereby “evidence of black swans” would appear in L . Therefore, interpretation steps may often be implicit or hidden in the particular view of L that a researcher adopts. In this paper, I try to represent prior work in a way that is faithful to the original authors’ meaning, though we must recognize that views of prior work will always be informed by our worldview.

4.3 Expansion

An expansion takes an existing relationship between P and L and adds additional entities and/or relations from L (not included in P ) to potentially expand the content of P or to bring new insights into the picture. Notice that structurally, the expansion operation is equivalent to the interpretation operation with P and L swapped; however, semantically, the two are often quite different. An expansion will often result in a change in P . As a result, it makes the most sense when P is an ongoing research topic (or a follow-up investigation to published work), rather than a final publication. Once P has changed to \(P'\) to incorporate the new entities and relations, what was once an expansion between P and L may be viewed as an intersection between \(P'\) and L . Therefore expansions play developmental roles in the research process, which are often not captured in publications. That is, many research projects may have changed course as a result of particular publications, but the final publication may only refer to the relationship to prior work at the time of publication, rather than the developmental influence of that prior work.

For example, in the related works section above, I acknowledged connections to Chan et al. ( 2018 ); these connections would be viewed as intersections (e.g., both papers have to do with academic literature, analogies, knowledge representation, etc.). However, what I did not state was that reading Chan et al. ( 2018 ) led me to read about structure-mapping theory (Gentner, 1983 ), and the two publications combined (and considered in relation to Swanson ( 1986 )) resulted in the beginnings of this paper. That is, before this paper was even conceived of, the aforementioned prior works resulted in a series of expansions, which turned into the present piece only after many iterations, which involved a series of other operations applied to various publications (some of which are cited, and some of which may not be). This reflects the role of literature search in the messy process that is research. I suspect that researchers rarely document the series of expansions (and other steps) that lead to the final state of a publication.

In fact, at times, some prior work may only play the role of a stepping stone to discovering other, more relevant, prior works. That is, an expansion of P by \(L_1\) may result in an exploration of the new entities in the expansion, which results in discovering \(L_2\) , which intersects with P . At that point, \(L_1\) may no longer really be relevant; that is, the extent of \(L_1\) ’s relevance may be better captured by \(L_2\) .

One broad category of expansions falls under Swanson’s ( 1986 ) second example—“A Missing Link in the Logic of Discovery” or what is often referred to as the ABC model. As Swanson ( 1986 ) originally expressed it:

Suppose the following two reports are published separately and independently, the authors of each report being unaware of the other report: (i) a report that process A causes the result B, and (ii) a separate report that B causes the result C. It follows of course that A leads to, causes, or implies C. That is, the proposition that A causes C objectively exists, at least as a hypothesis. (p. 110)

Swanson gave a specific example of a discovery he made (the first of his several literature-based discoveries in medicine): connecting (a) literature on how fish oil causes a reduction of blood viscosity with (b) literature on how reducing blood viscosity leads to an improvement in symptoms of Raynaud’s syndrome. The intersection of these two literatures is the entity “reduction of blood viscosity.” An expansion adds the causal link to “relief from Raynaud’s syndrome” and that link is then interpreted in light of the connection to “dietary fish oil.” Connecting these two literatures via these steps can result in a change in P as shown in Fig.  3 . Notice that the addition of a new causal relation between dietary fish oil and relief from Raynaud’s syndrome was inferred from this expansion, but had never been experimentally shown or even published about. Two years later, a clinical trial independently confirmed this hypothesis (Swanson & Smalheiser, 1996 ).

Swanson’s ( 1986 ) example of the ABC model as an example of expansion

Literature-based discovery often involves this kind of linking between two “non-interactive literatures,” literatures that are rarely, if ever, cited in the same publications (Swanson & Smalheiser, 1996 ). However, expansion need not always be between two non-interactive literatures. Indeed, researchers may often be unaware of highly relevant work within their own research community (or other interactive literatures) that build upon the concepts they are investigating. Such cases can often be caught by the researchers themselves when conducting a more expansive literature review, or by reviewers during the peer review process, but likely often go undetected.

4.4 Abstraction

An abstraction applies if P contains a subset of entities and relations that are instances of entities and relations in L . In other words, we have an abstraction when L contains a more abstract or generalized representation of part of P . An abstraction can still consist of concrete entities and relations as long as they are more general or more abstract than the entities and relations in P (e.g., as suggested above is-a (cat, animal), is-a (cat, Internet phenomenon), and is-a (the civil rights movement, historical occurrence) can all be single entity abstractions).

Describing an abstraction mathematically requires a bit more care than for previous operations since abstractions must be semantically “consistent” across the entities and relations involved. Formally, an abstraction applies if there is a subset of entities and relations in P —say \(E_{PS} \subseteq E_P\) and \(\mathcal {R}_{PS} \subseteq \mathcal {R}_P\) —and a subset of entities and relations in L —say \(E_{LS} \subseteq E_L\) and \(\mathcal {R}_{LS} \subseteq \mathcal {R}_L\) —such that the following four conditions hold:

For all \(e \in E_{PS}\) , there exists a \(\tilde{e} \in E_{LS}\) such that e is an instance of \(\tilde{e}\) .

For all \(R \in \mathcal {R}_{PS}\) , there exists a \(\tilde{R} \in \mathcal {R}_{LS}\) such that R is an instance of \(\tilde{R}\) .

For all \(R \in \mathcal {R}_{PS}\) , if \(R(e_1, e_2, \dots , e_n)\) , then \(\tilde{R}(\tilde{e}_1, \tilde{e}_2, \dots , \tilde{e}_n)\) , where \(R, e_1, \dots , e_n\) are instances of \(\tilde{R}, \tilde{e},_1 \dots , \tilde{e}_n\) respectively.

At least some \(e \not = \tilde{e}\) or some \(R \not = \tilde{R}\) .

The last condition is required to make sure the abstraction is not simply mapping identical representations (in which case it would just be an intersection). The resulting representation is \(\rho = (E_{PS} \cup E_{LS}, \mathcal {R}_{PS} \cup \mathcal {R}_{LS} \cup \textsc {is-a})\) , where \(\textsc {is-a}(e, \tilde{e})\) and \(\textsc {is-a}(R(e_1, e_2, \dots , e_n), \tilde{R}(\tilde{e}_1, \tilde{e}_2, \dots , \tilde{e}_n))\) , for all e , \(\tilde{e}\) , R , and \(\tilde{R}\) as defined in the conditions above.

Abstractions need not be profound. Consider the black swans example again. The way I presented it above was actually a bit disingenuous: black swans are not the only evidence that disproves the all-swans-are-white hypothesis; any non-white swans would. Thus it might be more accurate to replace the “black swans” entity with “non-white swans” in Fig.  2 a. The relationship between P and L then first involves an abstraction (instead of an intersection)—namely is-a (black swans, non-white swans)—followed by an interpretation, as shown in Fig.  4 . This is a rather trivial kind of abstraction, which likely happens all the time when interpreting prior work in the context of current work.

The black swans example revisited. The relationship between P and L is now an interpretation of an abstraction of L . Notice that we used “are” instead of “is a” simply because the entities are expressed in plural

A more substantial form of abstraction is whenever P reports on empirical findings that can be subsumed into an existing theory described by L . For example, if researchers find that students in a collaborative problem-solving activity learned more than students who were working on the activity on their own, then they might see the ICAP hypothesis (Chi & Wylie, 2014 ), which posits that interactive learning is better than constructive learning, as an abstraction.

Finally, perhaps the most interesting (but also rarest) form of abstraction is when a body of research is interpreted or a problem is solved using some abstract formalism or framework that exists in the literature (often in a different field). For example, a notable example in the history of science is the introduction of group theory to quantum mechanics to solve certain problems related to symmetry (French, 2000 ; Scholz, 2006 ). According to French ( 2000 ):

the relationship between mathematics and physics is represented in terms of an embedding of a scientific theory into a mathematical structure. This effectively gives the theory access to ‘surplus’ mathematical structure which can play an essential role in the further development of theory. (p. 104)

This “surplus structure”—a term originally from Redhead ( 1975 )—is represented in our typology by expansion steps that can follow the abstraction. Namely, once a connection is made between L (say group theory) and P (a particular problem in physics), an expansion can be applied to bring new mathematical machinery from L to bear on P . Furthermore, an interpretation of the abstraction of L in light of P might result in new insights that could lead to further developments in L (if we do not consider L to be static literature). As French ( 2000 ) states, “it is important to acknowledge that both group theory and quantum mechanics were in a state of flux at the time they were brought into contact and both subsequently underwent further development” (p. 110).

4.5 Reification

A reification is the inverse of an abstraction. That is, a reification has the same definition of an abstraction, except that P and L are exchanged. We can say P is reified by L if L is abstracted by P . A reification can occur when prior work might contain a concrete example of a phenomenon, which one’s present work presents in more abstract or general terms. Reifications will often be used when interpreting prior empirical findings in light of a new theoretical framework. For example, when articulating his theory of the structure of scientific revolutions, Kuhn ( 2012 ) drew on myriad concrete historical examples from the history of physics, astronomy, chemistry, and other fields. These findings are reifications of particular components of Kuhn’s theory (e.g., paradigms, anomalies, paradigm shifts, etc.).

A reification can also make sense when one is in a formative stage of a project where some of the specifics have not yet been determined. For example, consider Tu Youyou’s work on finding a cure for malaria in the 1970s for which she won the Nobel Prize in 2015. The problem that Tu and her team were working on is represented in Fig.  5 a. According to Tu ( 2015 ):

After thoroughly reviewing the traditional Chinese medical literature and folk recipes and interviewing experienced Chinese medical practitioners, I collected over two thousand herbal, animal and mineral prescriptions within three months after initiation of the project.

One of the substances that showed some initial promise was sweet wormwood ( qinghao ), which was shown in the literature to cure intermittent fevers, as shown in Fig.  5 b. Therefore sweet wormwood is a reification of a potential cure for malaria, as shown in Fig.  5 c, and this can be interpreted in the broader research of finding a cure for malaria, as shown in Fig.  5 d. Yu went on to identify artemisinin as an actual cure for malaria, but there was an additional step of literature-based discovery needed first, which we will return to later.

The discovery of sweet wormwood as a cure for malaria as an example of reification

4.6 Analogy

An analogy applies when P and L both have a subset of entities and relations that have a shared abstraction. More formally, using the same notation as above, an analogy applies if there exists some other representation \(A = (E_A, \mathcal {R}_A)\) (representing an abstraction) and the following four conditions hold Footnote 2 :

For all \(\tilde{e} \in E_A\) , there exists an \(e \in E_{PS}\) and an \(e' \in E_{LS}\) such that e and \(e'\) are both instances of \(\tilde{e}\) .

For all \(\tilde{R} \in \mathcal {R}_A\) , there exists an \(R \in \mathcal {R}_{PS}\) and an \(R' \in \mathcal {R}_{LS}\) such that R and \(R'\) are both instances of \(\tilde{R}\) .

For all \(\tilde{R} \in \mathcal {R}_{A}\) and for every pair \(R \in \mathcal {R}_{PS}\) and \(R' \in \mathcal {R}_{LS}\) such that R and \(R'\) are both instances of \(\tilde{R}\) , if \(\tilde{R}(\tilde{e}_1, \tilde{e}_2, \dots , \tilde{e}_n)\) then \(R(e_1, e_2, \dots , e_n)\) and \(R'(e'_1, e'_2, \dots , e'_n)\) , where \(e_i\) and \(e'_i\) are instances of \(\tilde{e}_i\) for all i and R and \(R'\) are instances of \(\tilde{R}\) .

At least some \(e \not = e'\) or some \(R \not = R'\) .

We say that \(\textsc {analogous}(e,e')\) if and only if condition 1 holds for e and \(e'\) and similarly we say that \(\textsc {analogous}(R(e_1, e_2, \dots , e_n), R'(e'_1, e'_2, \dots , e'_n))\) if and only if the conditions 2 and 3 above hold for those entities and relations. The representation that results from an analogy operation is \(\rho = (E_{PS} \cup E_{LS}, \mathcal {R}_{PS} \cup \mathcal {R}_{LS} \cup \textsc {analogous})\) .

Analogies can span from shallow analogies between two instances of a similar phenomenon in the same field to deep analogies across scientific fields that share little apparent relation to one another on the surface. The further removed that P and L are from the abstraction A , the deeper the analogy becomes (and typically, the harder to notice). Concretely identifying the abstraction implicit in an analogy is not necessary, and in some cases, it can actually be difficult to do, but I suggest that doing so may be a useful exercise (and could lead to refining the analogy).

Like expansions, analogies can sometimes result in modifying P by looking at the research project in a whole new light. Like expansions, this also means the way in which an analogy might have helped develop P over time may not always be apparent from the final product. Even if a publication discusses an analogy, it may not always be clear if that analogy was instrumental in developing the idea in the first place or if it was an afterthought that the two ideas were related.

An example of an analogy where the impact of prior work on a research project is actually made explicit is the analogy between Thomas Kuhn’s historical philosophy of science and Jean Piaget’s psychological and epistemological theory of how a child develops knowledge. In The Structure of Scientific Revolutions , Kuhn ( 2012 ) gives us a brief sense of his indebtedness to Piaget:

A footnote encountered by chance led me to the experiments by which Jean Piaget has illuminated both the various worlds of the growing child and the process of transition from one to the next. (p. xi)

The extent of this has recently been clarified by historians examining Kuhn’s other works and archival materials (Galison, 2016 ; Burman, 2020 ). For example, Kuhn ( 1977 , as cited in Burman, 2020) states:

Almost twenty years ago I first discovered, very nearly at the same time, both the intellectual interest of the history of science and the psychological studies of Jean Piaget. Ever since that time the two have interacted closely in my mind and in my work. (p. 21)

So what was the nature of this close interaction? One can draw a clear analogy between the two. At risk of oversimplification, a representation of the analogy between Kuhn’s theory and Piaget’s is shown in Fig.  6 , adapted from a mapping given by MacIsaac ( 1991 ). This is not at all to say that this is the precise analogy that Kuhn drew which led to a refinement of his theory as presented in The Structure of Scientific Revolutions . However, he probably made similar mappings that changed over time as he developed his theory. Similar analogies can also be drawn from Kuhn’s theory to gestalt theory and Bruner and Postman’s ( 1949 ) psychological theory of how people perceive incongruities, both of which Kuhn ( 2012 ) explicitly builds off of. Interestingly enough, the Piagetian analogy, while very influential on the development of Kuhn’s theory, was not retained in the final representation of his book, while the analogies to gestalt theory and Bruner and Postman ( 1949 ) were explicitly an important part of his narrative. Note that the relations in P and L are identical in this case, but this need not be the case in general; in fact, they may only be identical because I constructed them that way, but perhaps if the representations were to be derived independently, the relations would be non-identical, but share a common abstraction.

The representation of the analogy between Kuhn’s The Structure of Scientific Revolutions and Piagetian theory. The analogous relations are shown as dotted lines without labels for ease of reading

To provide a more recent example of analogy, we can consider the relationship between the recent machine learning literature on fairness ( P ) in relation to older literature from the 1960s-1970s on fairness in educational and employment testing ( L ). As Hutchinson and Mitchell ( 2019 ) point out, the two literatures share much in common including many mathematical definitions of fairness. To formalize this, Hutchinson and Mitchell ( 2019 ) explicitly construct an analogy between the two literatures:

Test items (questions) are analogous to model features, and item responses analogous to specific activations of those features. Scoring a test is typically a simple linear model which produces a (possibly weighted) sum of the item scores....Because of this correspondence, much of the math is directly comparable; and many of the underlying ideas in earlier fairness work trivially map on to modern day ML fairness. “History doesn’t repeat itself, but it often rhymes”; and by hearing this rhyme, we hope to gain insight into the future of ML fairness. (p. 49)

Their last sentence suggests that the goal of pointing out the relationship between these two literatures are further steps of expansion and interpretation, or in other words, exploiting the “surplus of structure.” Indeed, the authors surface several definitions from test fairness that had not been proposed in machine learning (i.e., an expansion). Notice that in this case, the underlying abstraction may not be immediately obvious (e.g., what is the abstraction underlying both a test item and a feature?); in fact, in some cases, there may not be a simple word or phrase to describe the abstraction, but the fact that a clear analogy can be drawn indicates that there must be some more abstract underlying representation.

Finally, in my own research, I have found that there is an analogy between debates in education research and the bias-variance tradeoff in machine learning (Doroudi, 2020 ). Here an analogy was determined by directly formulating the abstraction (a generalized version of the bias-variance decomposition theorem). This abstraction has four components that any instance must specify: a target, an approximator, a random mechanism, and a source of randomness; once these components are specified, one can derive other phenomena (e.g., the meaning of bias, variance, etc.). This naturally sounds very abstract, but it is more concrete once instantiated in specific contexts. Table  2 gives an example of the analogy between these concepts in machine learning and debates around pedagogy. Once this analogy is drawn, it may be possible to expand techniques that are developed in machine learning to bear on educational debates (Doroudi, 2020 ). One benefit of making the abstraction concrete is that the same abstraction can be used to draw analogies to other fields as well.

4.7 Substitution

The analogy operator as described above can be applied in cases that do not semantically appear to be analogies. For example, consider two papers that use different methods to achieve the same outcome; many of the entities and relations may be the same across the two representations, but the entity (or entities) representing the methods would be different. Colloquially we would probably not say there is an analogy between the two approaches. For this reason, we make a distinction between substitutions and analogies. A substitution operates exactly in the same way as an analogy, but it should be applied when it is more sensible. The analogous relation can be replaced with the substitutes relation for semantic clarity. Therefore, unlike the other operators, the distinction between the analogy and substitution operators is semantic. However, there are typically clear structural differences between the two. In a substitution, typically only one or a few entities and relations will change, and the rest will be identical across P and L . Moreover, a substitution is similar to what Gentner ( 1983 ) terms a literal similarity. Namely, Gentner ( 1983 ) suggests that the difference between a literal similarity and an analogy is typically that a literal similarity will involve a greater number of identical attributes (or unary relations).

Consider the following four scenarios that loosely describe different papers:

Convolutional neural networks are trained to classify histopathological images of breast tissue as benign or malignant (Spanhol et al., 2016 ).

Support vector machines are trained to classify histopathological images of breast tissue as benign or malignant (Aswathy & Jagannath, 2021 ).

Human crowdworkers are trained to classify histopathological images of breast tissue as benign or malignant (Eickhoff, 2014 ).

Pigeons are trained to classify histopathological images of breast tissue as benign or malignant (Levenson et al., 2015 ).

In cases 1 and 2, it would be a stretch to say that there is an analogy between “convolutional neural networks” and “support vector machines,” which are both machine learning algorithms that can be applied to the same classification tasks. Thus, here is a clear case of substitution. However, with case 4, even though one could argue a pigeon is being substituted for a machine learning algorithm, the idea of training pigeons and the idea of training machine learning algorithms both have long histories and are often used for different purposes. Thus, it seems more natural to say pigeons are analogical to neural networks or support vector machines in these scenarios (with the underlying abstraction being a learning agent). Pigeons and support vector machines have a lot fewer attributes in common than convolutional neural networks and support vector machines. Unlike pigeons, the latter two are both algorithms implemented in computer code that were designed specifically for classification tasks. Pigeons, on the other hand, are animals, fly, eat, and make sounds. Some attributes of pigeons are actually important for the training process but not shared by any standard machine learning algorithms, such as their hunger. While we might say getting hungry is analogous to the “reward seeking” or “loss minimizing” property of machine learning algorithms, there is no literal hunger in those algorithms.

Case 3 is less clear-cut. While human crowdworkers are also significantly different from machine learning algorithms, crowdsourcing is often used for tasks where state-of-the-art machine learning is not good enough or a machine learning engineer might want to compare the performance of their algorithm against crowdworkers. On the other hand, human crowdworkers and pigeons share a lot of similar attributes that are lacking in machine learning algorithms. These ambiguities point out that ultimately the decision of whether an analogy or a substitution applies is in the eyes of the beholder. In other words, the degree of overlap in attributes depends on what attributes are most salient to the researcher. If a crowdworker is seen as an alternative to artificial intelligence and its humanity is not at the forefront, then perhaps a substitution would apply. On the other hand, researchers interested in using pigeons’ visual properties as a substitute for human labelers (Levenson et al., 2015 ) could also see a substitution between crowdworkers and pigeons.

As mentioned earlier, Kang et al.’s ( 2022 ) analogical search engine looks for papers that overlap in terms of purpose with a researchers’ study (as represented in the form of a search query). However, if the purpose is virtually identical, then replacing one mechanism for another may often be a substitution, not an analogy, as seen in cases 1 and 2 above. In some cases, such as using pigeons vs. neural networks to classify images, swapping mechanisms may result in an analogy. On the other hand, when the purpose is only similar (but not identical), there is no guarantee that the purpose-mechanism relationship will be analogical across different papers. Footnote 3 Thus, while Kang et al. ( 2022 ) find that their search engine is more likely to identify papers that trigger creative adaptations of the original idea (when compared to a standard keyword-based search engine), it is important to distinguish related work that might result in generating novel ideas and related work that actually has an analogical relationship with the present work.

Returning to Tu’s work on discovering a cure for malaria, she found that wormwood “showed some effects in inhibiting malaria parasites during initial screening, but the result was inconsistent and not reproducible.” Scouring over the relevant literature, she then identified a relevant sentence in Ge Hong’s fifth century A Handbook of Prescriptions for Emergencies : “A handful of Qinghao immersed in two liters of water, wring out the juice and drink it all” (Tu, 2015 ). Tu realized that while herbs are typically boiled, Ge’s recipe did not advocate for boiling it so perhaps the heat killed the active components in the wormwood. This led to a new method for extracting artemisinin from wormwood. To model this we would have to add entities to Fig.  5 that account for the method by which the drug is extracted. In that case, Ge’s method can be seen as a substitution for Tu’s original method. This substitution led to a drastic change in the research direction, eventually resulting in a cure for malaria.

Example of literature search as a sequence of operators applied to a research question on how memory is stored in synapses

5 Putting the pieces together

Now that we have seen the various operations that can relate two pieces of research to one another, it is worth discussing how these operations might be used in sequence over the scope of a research project. To do so, I provide a hypothetical example. As a disclaimer, the example is not from an area I have any expertise in; in fact, I encountered the relationships described below in the process of writing this paper (although not in the exact sequence described below). On the one hand, this suggests that the example may be oversimplified; on the other hand, perhaps it gives a somewhat authentic account of a non-expert navigating a new research field.

Suppose we are interested in conducting a literature review related to the question “how are memories stored in synapses?” This research question can be represented as “memories are stored in synapses through some mechanism” as shown at the top of Fig.  7 . Some of the steps described below are also represented in Fig.  7 ; in those cases, I will mention the number of the step in parentheses. Operator names are italicized below. If the reader wants to assess their understanding of the operators (or perhaps assess the degree to which there could be subjectivity in which operators apply), the reader can guess which operator applies for each step of the figure before reading the rest of this section.

When embarking on this literature search process, we are likely already aware of some answers to the question. For example, “some mechanism” could be reified by “synaptic plasticity” (Step 1). But synaptic plasticity is quite broad and could be reified further by several more specific forms of plasticity, such as “long-term potentiation” (Step 2) and “long-term depression.” Further literature search might reveal a plethora of other mechanisms such as “protein synthesis,” “epigenetic mechanisms,” or “the standard model of synaptic consolidation.” However, these mechanisms are not necessarily mutually exclusive, perhaps leading to a revision of the question formulation to “memories are stored in synapses through a combination of X, Y, ...” (or some more hierarchical representation). On the other hand, some proposed mechanisms may be competing, like “the standard model of synaptic consolidation” and “multiple trace theory” (i.e., one can be substituted for the other). Moreover, we might realize that the “memory” entity can also be reified into particular kinds of memory, like “episodic memory” or “semantic memory.”

Searching the literature further may reveal that there are recent suggestions that memory is not (only) stored in synapses, but could be stored in sub-cellular materials. This might result in a substitution of certain molecules (e.g., “RNA”) for synapse (Step 3 \('\) ). Alternatively, to keep our options open we may apply an abstraction of “synapse,” such as “parts of the brain” (Step 3). “Parts of the brain” can then be reified with many different entities, like “RNA” (Step 4). But it can also be substituted for regions of the brain where memories are stored, like the hippocampus. This may subsequently lead to the realization that rather than just asking how memories are stored, we should also be asking where memories are stored, leading to an expansion of the initial representation.

So far we have primarily considered literature that directly bears on the initial question. But sometimes surprising related works can also be discovered through intersections . For example, once we have established that RNA may be involved in memory, a colleague who is a molecular biologist might point out that there is an intersection with the literature on RNA interference (Step 5). Indeed, Smalheiser et al. ( 2001 ) noticed connections between a series of controversial 1960s studies on RNA-mediated memory transfer and RNAi; Smalheiser was a pioneer of literature-based discovery. We might then posit a relation that was neither present in our initial representation nor in related work: RNAi is potentially involved in the memory storage mechanism (i.e., “some mechanism” in our representation). Although it took over a decade, Smalheiser eventually found evidence to suggest that RNAi could indeed be involved in memory transfer (Smalheiser, 2017 ).

Finally, upon contemplating the initial representation further, the researcher may recognize an analogy to “how is memory stored in computer hardware?” (Step 6) or “how is memory stored in artificial neural networks?” Studying the literature in either of these areas may lead to the addition of new hypothesized mechanisms through an interpretation in light of the analogies. Notice that while in some cases a researcher notices an analogy when examining related literature, in other cases a researcher might think of an analogy, and then search for related literature. The related literature could either be about the analog (e.g., how memory is encoded in artificial neural networks) or about the analogy itself (Langille & Gallistel, 2020 ,e.g., how do theories of memory storage in the human brain relate to theories of memory storage in computer science). In the latter case, we have an intersection applied to the entire analogy .

6 The typology in practice

In this section, we discuss some important considerations for how the representation and typology could be used in practice. In theory, an understanding of the various ways in which one piece of literature may relate to a research topic can inform directions in information retrieval and citation recommendation. Such systems could potentially represent papers in terms of entities and relations by using named entity recognition (Nadeau & Sekine, 2007 ) and relation extraction (Bach & Badaskar, 2007 ); they can also leverage a growing body of work on using knowledge graphs for information retrieval (Reinanda et al., 2020 ). The typology can then inform the kinds of relationships that such systems can explore and possibly recommend to users. However, we reiterate that there is no single way to represent a paper or single way of applying the operators to identify relationships to prior work. As noted above, the choice of what operators apply and hence which relationships to related works will be noticed depends on the view one takes of one’s work and related work. One way to potentially mitigate this challenge is by having users specify their current view of their work in terms of its representation, or perhaps by allowing them to simultaneously represent their work in multiple ways. Furthermore, recognizing that different researchers and papers will use slightly different terms to refer to identical or very similar entities and relations, search engines could try to treat semantically similar phrases as being identical or provide a pre-selected set of entities and relations that they recommend users use.

However, even if the representations of papers are completely aligned, the task of retrieving good analogies and abstractions may be computationally intractable in the worst case (Wareham et al., 2011 ). Indeed, in automated analogical search, simplifications are made to make finding potential analogies more tractable. For example, the MAC/FAC algorithm—which is rooted in structure-mapping theory—first finds several examples that have the most surface-level overlap in terms of relations and then identifies the analogy Footnote 4 that is structurally strongest (Forbus et al., 1995 ). In Kang et al.’s ( 2022 ) analogical search engine, they look for papers that have a similar purpose, where similarity is measured by neural network embeddings rather than looking for a formally analogical structure. Although such algorithms may not be perfect, they could still potentially surface candidate analogies that would be given to a researcher who would ultimately identify when an analogy operator is applicable and useful.

Given the ongoing challenges in automated search, perhaps the typology would be more useful as a conceptual tool for researchers. Huang and Soergel ( 2013 ) found that “teaching users about the different kinds of topical relevance relationships may open their minds and make them better searchers and users of information.” Similarly, perhaps the typology presented here could be used as a tool to familiarize researchers with the different ways in which their research may relate to prior work, and how to use search tools to find such works. As mentioned before, simply representing one’s paper as a network of entities and relations may be a useful exercise to help researchers realize new insights about their research; future experimental studies could confirm whether this is true. Moreover, in discussing the potential value of their analogical search engine, Kang et al. ( 2022 ) mention the importance of “how deeply the human users can reflect on the retrieved analogs...and recognize how different notions of relevance may exist for their own problem context, despite potential dissimilarity on the surface” (p. 125). They suggest that “one approach to explaining relevance might be to surface a small number of core common features between an analog and a problem query” (p. 126). The representation presented here provides a natural way of showing users the potential relevance of related work. For example, when one searches for literature (even using a traditional search engine), representations could be generated on demand for the resulting papers such that they maximally align with the user’s query (at least in terms of number of entities and relations, if not in terms of higher-order relationships). Moreover, if the user specifies multiple research projects, a search engine could potentially represent each paper in terms of the representation that best aligns with each project.

7 Conclusion

I have tried to make the case that literature search is a complex process that can influence and be influenced by research in a variety of ways. By describing research papers and projects in terms of concrete representations, we can formally articulate how different pieces of research might relate to one another. As discussed in the last section, this could have practical ramifications in terms of how search engines could better support the literature search process or how to design training for researchers to improve the way they approach literature search.

Beyond practical applications, the typology presented here could give us insight into the ways in which literature search might iteratively change the course of a research project as a sequence of operations. Although it goes beyond the scope of this paper, it might be worth briefly considering some of the ways in which a research project might be modified as a result of these operations. One form of modification is simply adding new entities and relations to P as a result of an expansion; we can view this as a natural extension of the expansion operator. Several other forms of modifications can fall under the category of logical inference (i.e., deduction , induction , and abduction ). For example, in the black swans example, evidence of black swans triggers a modus ponens argument that proves the “all-swans-are-white” hypothesis is false, thereby changing P . Similarly, in Swanson’s ABC model, we can discern the presence of a new relation through the transitivity of the causal relation. If the representations are well-specified, one can imagine creating an inference engine that can automatically detect such changes in P after coming into contact with related work.

However, literature search cannot be considered in isolation from the other aspects of scientific discovery. Another form of modification to P might be the result of an experimentation operation, whereby a deduced relation is tested. We saw this both in the case of medical research that confirmed the causal link deduced by Swanson, and Tu’s experimental confirmation that wormwood can cure malaria. Finally, there is the construction operation, whereby a new entity or relation is created. Construction can result from either literature search (e.g., where an interpretation of some finding results in the discovery of a new finding, or where the expansion of an analogy results in an analogous entity that was not previously conceived of) or from research itself (e.g., the discovery of a new molecule or a new experimental finding). A thorough understanding of the processes of inference, experimentation, and construction is beyond the scope of this paper, but they begin to give us a hint as to how literature search is an iterative process that interacts with other aspects of the research process.

As pointed out by Swanson ( 1986 ), world 3 is also a world where scientific discovery takes place, by interacting with world 1 (the physical world) and world 2 (the subjective world of mental states). Philosophy of science should try to understand how these worlds interact in the process of scientific discovery; this paper is a step in that direction.

Availability of data and material:

This can be formalized using the partial structures formalism mentioned above (Da Costa & French, 1990 ).

Gentner ( 1983 ) did not explicitly define an analogy in terms of an abstraction, but I believe it is useful to recognize that there is always implicitly an abstraction present, and in many cases, it might be useful to reason about what that abstraction is. Gentner ( 1983 ) further differentiates between abstractions, analogies, and literal similarities. These are differentiated by how many attributes and relations are shared between the two and the degree of abstractness of the entities (i.e., in an abstraction, entities are more abstract). While this is sensible, we allow for abstractions that are more concrete, so long as the entities in one representation are still instances of the entities in the other.

For example, one participant’s research question was how to “Grow plants better by optimizing entry of nanoparticle fertilizers into the plant” (p. 14). One paper identified by analogical search was about identifying plants by applying image analysis techniques to their leaves. It is not clear what the similar purpose is in this case, but regardless, the paper does not obviously share an analogical relationship with the research question. While this paper inspired a novel idea that the researcher thought would be relevant to her project, the relationship is captured by an intersection (through the “plant” entity) and possibly the application of interpretation and expansion operators.

Technically it looks for matches in terms of literal similarity to mimic people’s tendencies to find literally similar matches, but the algorithm could be easily modified to search for analogies.

Adleman, L. M. (1994). Molecular computation of solutions to combinatorial problems. Science, 266 (5187), 1021–1024. https://doi.org/10.1126/science.7973651

Aswathy, M., & Jagannath, M. (2021). An SVM approach towards breast cancer classification from H &E-stained histopathology images based on integrated features. Medical & Biological Engineering & Computing, 59 (9), 1773–1783. https://doi.org/10.1007/s11517-021-02403-0

Bach, N., & Badaskar, S. (2007). A review of relation extraction. Literature Review for Language and Statistics II, 2 , 1–15. https://www.cs.cmu.edu/~nbach/papers/A-survey-on-Relation-Extraction.pdf

Bhagavatula, C., Feldman, S., Power, R., & Ammar, W. (2018, June). Content-based citation recommendation. In M. Walker, H. Ji, & A. Stent (Eds.), Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (pp. 238–251). ACL.

Brachman, R. J. (1983). What IS-A is and isn’t: An analysis of taxonomic links in semantic networks. Computer, 16 (10), 30–36. https://doi.org/10.1109/MC.1983.1654194

Article   Google Scholar  

Bruner, J. S., & Postman, L. (1949). On the perception of incongruity: A paradigm. Journal of Personality, 18 (2), 206–223. https://doi.org/10.1111/j.1467-6494.1949.tb01241.x

Burman, J. T. (2020). On Kuhn’s case, and Piaget’s: A critical two-sited hauntology (or, on impact without reference). History of the Human Sciences, 33 (3–4), 129–159. https://doi.org/10.1177/0952695120911576

Callaway, E. (2020). The race for coronavirus vaccines: A graphical guide. Nature, 576–577. https://doi.org/10.1038/d41586-020-01221-y

Chan, J., Chang, J. C., Hope, T., Shahaf, D., & Kittur, A. (2018). Solvent: A mixed initiative system for finding analogies between research papers. Proceedings of the ACM on Human-Computer Interaction, 2 , 1–21. https://doi.org/10.1145/3274300

Chi, M. T., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49 (4), 219–243. https://doi.org/10.1080/00461520.2014.965823

Da Costa, N. C., & French, S. (1990). The model-theoretic approach in the philosophy of science. Philosophy of Science, 57 (2), 248–265. https://doi.org/10.1086/289546

Davies, R. (1989). The creation of new knowledge by information retrieval and classification. Journal of Documentation . https://doi.org/10.1108/eb026846

Doroudi, S. (2020). The bias-variance tradeoff: How data science can inform educational debates. AERA Open, 6 (4), 2332858420977208. https://doi.org/10.1177/2332858420977208

Eickhoff, C. (2014). Crowd-powered experts: Helping surgeons interpret breast cancer images. In F. Hopfgartner, G. Kazai, U. Kruschwitz, & M. Meder (Eds.), GamifIR ’14: Proceedings of the First International Workshop on Gamification for Information Retrieval (pp. 53–56). ACM. https://doi.org/10.1145/2594776.2594788

Falkenhainer, B., Forbus, K. D., & Gentner, D. (1989). The structure-mapping engine: Algorithm and examples. Artificial Intelligence, 41 (1), 1–63. https://doi.org/10.1016/0004-3702(89)90077-5

Forbus, K. D., Gentner, D., & Law, K. (1995). MAC/FAC: A model of similarity based retrieval. Cognitive Science, 19 (2), 141–205. https://doi.org/10.1207/s15516709cog1902_1

French, S. (2000). The reasonable effectiveness of mathematics: Partial structures and the application of group theory to physics. Synthese, 125 (1), 103–120. https://doi.org/10.1023/a:1005246608001

Galison, P. (2016). Practice all the way down. R.J. Richards & L. Daston (Eds.), Kuhn’s ‘Structure of Scientific Revolutions’ at fifty (pp. 42–70). University of Chicago Press

Gentner, D. (1983). Structure-mapping: A theoretical framework for analogy. Cognitive Science, 7 (2), 155–170. https://doi.org/10.1207/s15516709cog0702_3

Green, R. (1995). Topical relevance relationships. I. Why topic matching fails. Journal of the American Society for Information Science, 46 (9), 646–653. https://doi.org/10.1002/(SICI)1097-4571(199510)46:93C646::AID-ASI2%3E3.0.CO;2-1

Green, R., & Bean, C. A. (1995). Topical relevance relationships. II. An exploratory study and preliminary typology. Journal of the American Society for Information Science, 46 (9), 654–662. https://doi.org/10.1002/(SICI)1097-4571(199510)46:9%3C654::AID-ASI33E3.0.CO;2-3

Huang, X. (2009). Topical relevance, rhetoric, and argumentation: A cross- disciplinary inquiry into patterns of thinking and information structuring. [Doctoroal dissertation, University of Maryland]. Digital Repository at the University of Maryland. https://drum.lib.umd.edu/handle/1903/9577

Huang, X., & Soergel, D. (2013). Relevance: An improved framework for explicating the notion. Journal of the American Society for Information Science and Technology, 64 (1), 18–35. https://doi.org/10.1002/asi.22811

Hutchinson, B., & Mitchell, M. (2019). 50 years of test (un)fairness: Lessons for machine learning. In Proceedings of the conference on fairness, accountability, and transparency (pp. 49–58). ACM. https://doi.org/10.1145/3287560.3287600

Kang, H. B., Qian, X., Hope, T., Shahaf, D., Chan, J., & Kittur, A. (2022). Augmenting scientific creativity with an analogical search engine. ACM Transactions on Computer-Human Interaction, 1 , 1–36. https://doi.org/10.1145/3530013

Ke, Q., Ferrara, E., Radicchi, F., & Flammini, A. (2015). Defining and identifying sleeping beauties in science. Proceedings of the National Academy of Sciences, 112 (24), 7426–7431. https://doi.org/10.1073/pnas.1424329112

Kuhn, T. S. (1977). Concepts of cause in the development of physics. In T. S. Kuhn (Ed.), The essential tension (pp. 21–30). University of Chicago Press. (Original work published 1971. https://doi.org/10.7208/9780226217239-003

Kuhn, T. S. (2012). The structure of scientific revolutions: 50th anniversary edition . University of Chicago Press. (Original work published 1962)

Langille, J. J., & Gallistel, C. R. (2020). Locating the engram: Should we look for plastic synapses or information-storing molecules? Neurobiology of Learning and Memory, 169 , 107164. https://doi.org/10.1016/j.nlm.2020.107164

Levenson, R. M., Krupinski, E. A., Navarro, V. M., & Wasserman, E. A. (2015). Pigeons (columba livia) as trainable observers of pathology and radiology breast cancer images. PLoS ONE, 10 (11), e0141357. https://doi.org/10.1371/journal.pone.0141357

Liang, Y., Li, Q., & Qian, T. (2011). Finding relevant papers based on citation relations. In International conference on web-age information management (pp. 403–414). https://doi.org/10.1371/journal.pone.0141357

MacIsaac, D. (1991). The pedagogical implications of parallels between Kuhn’s philosophy of science and Piagets’ model of cognitive development. Retrieved from http://physicsed.buffalostate.edu/danowner/kuhnpiaget/KP1.html

Merton, R. K. (1963). Resistance to the systematic study of multiple discoveries in science. European Journal of Sociology/Archives Européennes de Sociologie, 4(2) , 237–282. https://doi.org/10.1017/S0003975600000801

Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63 (2), 81. https://doi.org/10.1037/h0043158

Nadeau, D., & Sekine, S. (2007). A survey of named entity recognition and classification. Lingvisticae Investigationes, 30 (1), 3–26. https://doi.org/10.1075/bct.19.03nad

Pask, G. (1988). Learning strategies, teaching strategies, and conceptual or learning style. In R. R. Schmeck (Ed.), Learning strategies and learning styles (pp. 83–100). Springer.

Pask, G., Kallikourdis, D., & Scott, B. C. (1975). The representation of knowables. International Journal of Man-Machine Studies, 7 (1), 15–134. https://doi.org/10.1016/S0020-7373(75)80003-4 .

Popper, K. (1978). Three worlds. [Lecture transcript]. The Tanner Lectures on Human Values. https://tannerlectures.utah.edu/_resources/documents/a-to-z/p/popper80.pdf

Redhead, M. L. (1975). Symmetry in intertheory relations. Synthese, 32, 77–112. https://www.jstor.org/stable/20115097 .

Reinanda, R., Meij, E., de Rijke, M., et al. (2020). Knowledge graphs: An information retrieval perspective (Vol. 14(4), pp. 289–444). Foundations and Trends in Information Retrieval. https://doi.org/10.1561/1500000063

Ren, X., Liu, J., Yu, X., Khandelwal, U., Gu, Q., Wang, L., & Han, J. (2014). Cluscite: Effective citation recommendation by information networkbased clustering. In Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 821–830). https://doi.org/10.1145/2623330.2623630

Sacks, O. (2002). Scotoma: Forgetting and neglect in science. Prematurity in scientific discovery (pp. 70–84). University of California Press. https://doi.org/10.1525/9780520927735-010

Saracevic, T. (1975). Relevance: A review of and a framework for the thinking on the notion in information science. Journal of the American Society for Information Science, 26 (6), 321–343. https://doi.org/10.1002/asi.4630260604

Saracevic, T. (2016). The notion of relevance in information science: Everybody knows what relevance is. But, what is it really ? https://doi.org/10.1007/978-3-031-02302-6

Scholz, E. (2006). Introducing groups into quantum theory (1926–1930). Historia Mathematica, 33 (4), 440–490. https://doi.org/10.1016/j.hm.2005.11.007

Sebastian, Y., Siew, E.-G., & Orimaye, S. O. (2017). Emerging approaches in literature-based discovery: Techniques and performance review. The Knowledge Engineering Review, 32 , e12. https://doi.org/10.1017/S0269888917000042

Smalheiser, N. R. (2017). Rediscovering Don Swanson: The past, present and future of literature-based discovery. Journal of Data and Information Science, 2 (4), 43. https://doi.org/10.15152Fjdis-2017-0019 .

Smalheiser, N. R., Manev, H., & Costa, E. (2001). RNAi and brain function: Was McConnell on the right track? Trends in Neurosciences, 24 (4), 216–218. https://doi.org/10.1016/s0166-2236(00)01739-2

Sowa, J. F. (1976). Conceptual graphs for a data base interface. IBM Journal of Research and Development, 20 (4), 336–357. https://doi.org/10.1147/rd.204.0336

Spanhol, F. A., Oliveira, L. S., Petitjean, C., & Heutte, L. (2016). Breast cancer histopathological image classification using convolutional neural networks. In 2016 International joint conference on neural networks (IJCNN) (pp. 2560–2567). https://doi.org/10.1109/IJCNN.2016.7727519

Spivak, D. I., & Kent, R. E. (2012). Ologs: A categorical framework for knowledge representation. PLoS ONE, 7 (1), e24274. https://doi.org/10.1371/journal.pone.0024274

Strohman, T., Croft, W. B., & Jensen, D. (2007). Recommending citations for academic papers. In Proceedings of the 30th annual international ACM SIGIR conference on research and development in information retrieval (pp. 705–706). https://doi.org/10.1145/1277741.1277868

Suppes, P. (1957). Introduction to logic . D. van Norstrand Co.

Suppes, P. (1960). A comparison of the meaning and uses of models in mathematics and the empirical sciences. Synthese, 12 , 287–301. https://doi.org/10.1007/BF00485107

Swanson, D. R. (1986). Undiscovered public knowledge. The Library Quarterly, 56 (2), 103–118 University of Chicago Press. https://www.jstor.org/stable/4307965

Swanson, D. R., & Smalheiser, N. R. (1996). Undiscovered public knowledge: A ten-year update. In E. Simoudis, J. Han, & U. Fayyad (Eds.), Proceedings of the second international conference on knowledge discovery and data mining (pp. 295–298). https://www.aaai.org/Papers/KDD/1996/KDD96-051.pdf

Tu, Y. (2015). Tu Youyou—Biographical. NobelPrize.org. Retrieved from https://www.nobelprize.org/prizes/medicine/2015/tu/lecture/

Wareham, T., Evans, P., & van Rooij, I. (2011). What does (and doesn’t) make analogical problem solving easy? A complexity-theoretic perspective. The Journal of Problem Solving, 3 (2), 30–70. https://doi.org/10.7771/1932-6246.1091

Download references

Acknowledgements

This material is based upon work supported by the National Science Foundation under Grant No. (2033868). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.

Provided by National Science Foundation, Award Number: 2033868

Author information

Authors and affiliations.

School of Education, University of California, Irvine, 401 E. Peltason Drive, Suite 3200, Irvine, CA, 92617, USA

Shayan Doroudi

You can also search for this author in PubMed   Google Scholar

Contributions

Sole authored publication

Corresponding author

Correspondence to Shayan Doroudi .

Ethics declarations

Conflicts of interest/competing interests, code availability:, additional information, publisher's note.

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

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

Doroudi, S. What is a related work? A typology of relationships in research literature. Synthese 201 , 24 (2023). https://doi.org/10.1007/s11229-022-03976-5

Download citation

Received : 09 September 2021

Accepted : 10 November 2022

Published : 09 January 2023

DOI : https://doi.org/10.1007/s11229-022-03976-5

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

• Literature search
• Literature-based discovery
• Information retrieval
• Abstraction
• Structure-mapping theory
• Find a journal
• Publish with us
• Track your research

Imperial College London Imperial College London

Latest news.

Neutrino discoveries and academic awards for excellence: News from Imperial

Imperial joins European discussion on accelerating innovation

Imperial to strengthen Transatlantic tech cooperation with new hub

• Educational Development Unit
• Teaching toolkit
• Educational research methods
• Before you start

Identifying literature

Before you start - Identifying literature

All educational research requires a thorough review of appropriate literature, by way of contextualising and justifying the intended study. Before you can begin conducting and writing your literature review, you need to ensure that you have systematically identified and sourced a sufficient range of relevant literature; and in doing so, maintain a sufficiently tight control over the boundaries of your search. You also need to ensure that you develop an efficient system for managing, retrieving and referencing the literature that you do use.

Savin-Baden & Howell Major (2013) provide a number of suggestions for how to proceed through each stage of the initial literature search, as summarised in the table below:

Savin-Baden, M. & Howell Major, C. (2013), Chapter 8 – “Literature Review”. In Savin-Baden, M. & Howell Major, C., Qualitative Research.  The essential guide to theory and practice. Abingdon: Routledge (pp. 112-129).

How to Do Research: A Step-By-Step Guide: Get Started

• Get Started
• 1a. Select a Topic
• 1b. Develop Research Questions
• 1c. Identify Keywords
• 1d. Find Background Information
• 1e. Refine a Topic
• 2a. Search Strategies
• 2d. Articles
• 2e. Videos & Images
• 2f. Databases
• 2g. Websites
• 2h. Grey Literature
• 2i. Open Access Materials
• 3a. Evaluate Sources
• 3b. Primary vs. Secondary
• 3c. Types of Periodicals
• 4a. Take Notes
• 4b. Outline the Paper
• 4c. Incorporate Source Material
• 5a. Avoid Plagiarism
• 5b. Zotero & MyBib
• 5c. MLA Formatting
• 5d. MLA Citation Examples
• 5e. APA Formatting
• 5f. APA Citation Examples
• 5g. Annotated Bibliographies

Related Guides

• Elmira College Writing Center Get one-on-one assistance for all types of writing.

Recommended Websites

• Purdue University's Online Writing Lab (OWL)

Research Process Overview

Step 1.  Develop a topic Select a Topic | Develop Research Questions | Identify Keywords | Find Background Information | Refine a Topic

Step 2. Locate information Search Strategies | Books | eBooks | Articles  | Videos & Images | Databases | Websites | Grey Literature

Step 3. Evaluate and analyze information Evaluate Sources | Primary vs Secondary | Types of Periodicals

Step 4. Write, organize, and communicate information Take Notes | Outline the Paper | Incorporate Source Material

Step 5. Cite sources Avoid Plagiarism | Zotero & MyBib | MLA | APA | Chicago Style | Annotated Bibliographies

For research help,  use one of the following options:

Ask the GTL

• Next: Step 1: Develop a Topic >>
• Last Updated: Aug 13, 2024 3:10 PM
• URL: https://libguides.elmira.edu/research

• U.S. Department of Health & Human Services

• Virtual Tour
• Staff Directory
• En Español

You are here

Science, health, and public trust.

September 8, 2021

Explaining How Research Works

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to  [email protected].

Below are some additional resources:

• Discoveries in Basic Science: A Perfectly Imperfect Process
• When Clinical Research Is in the News
• What is Basic Science and Why is it Important?
• ​ What is a Research Organism?
• What Are Clinical Trials and Studies?
• Basic Research – Digital Media Kit
• Decoding Science: How Does Science Know What It Knows? (NAS)
• Can Science Help People Make Decisions ? (NAS)

Connect with Us

• More Social Media from NIH

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Correlational Research

Learning objectives.

• Explain correlational research, including what a correlation coefficient tells us about the relationship between variables

One of the primary methods used to study abnormal behavior is the correlational method.  Correlation means that there is a relationship between two or more variables (such between the variables of negative thinking and depressive symptoms), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from negative one to positive one that indicates the strength and direction of the relationship between variables. The association between two variables can be summarized statistically using the correlation coefficient (abbreviated as  r ).

The number portion of the correlation coefficient indicates the strength of the relationship. The closer the number is to one (be it negative or positive), the more strongly related the variables are, and the more predictable changes in one variable will be as the other variable changes. The closer the number is to zero, the weaker the relationship, and the less predictable the relationships between the variables becomes. For instance, a correlation coefficient of 0.9 indicates a far stronger relationship than a correlation coefficient of 0.3. If the variables are not related to one another at all, the correlation coefficient is zero. The example above about negative thinking and depressive symptoms is an example of two variables that we might expect to have a relationship to each other.  When higher values in one variable (negative thinking) are associated with higher values in the other variable (depressive symptoms), there is a  positive correlation  between the variables.

The sign—positive or negative—of the correlation coefficient indicates the direction of the relationship.  Positive correlations carry positive signs; negative correlations carry negative signs.  A positive correlation means that the variables move in the same direction. Put another way, it means that as one variable increases so does the other, and conversely, when one variable decreases so does the other. A negative correlation means that the variables move in opposite directions. If two variables are negatively correlated, a decrease in one variable is associated with an increase in the other and vice versa.

Other examples of positive correlations are the relationship between depression and disturbance in normal sleep patterns. One might expect then that scores on a measure of depression would be positively correlated with scores on a measure of sleep disturbances.

One might expect a negative correlation to exist between  between depression and self-esteem.  The more depressed people are, the lower their scores are on the Rosenberg self-esteem scale (RSES), a self-esteem measure widely used in social-science research.  Keep in mind that a negative correlation is not the same as no correlation. For example, we would probably find no correlation between  depression  and someone’s   height. 

In correlational research,  scientists passively observe and measure phenomena.    Here, we do not intervene and change behavior, as we do in experiments. In correlational research, we identify patterns of relationships, but we usually cannot infer what causes what. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.

As mentioned earlier, correlations have predictive value. So, what if you wanted to test whether spending on others is related to happiness, but you don’t have $20 to give to each participant? You could use a correlational design—which is exactly what Professor Dunn did, too. She asked people how much of their income they spent on others or donated to charity, and later she asked them how happy they were. Do you think these two variables were related? Yes, they were! The more money people reported spending on others, the happier they were.

More Details about the Correlation

To find out how well two variables correspond, we can plot the relationship between the two scores on what is known as a scatterplot (Figure 1). In the scatterplot, each dot represents a data point. (In this case it’s individuals, but it could be some other unit.) Importantly, each dot provides us with two pieces of information—in this case, information about how good the person rated the past month ( x -axis) and how happy the person felt in the past month ( y -axis). Which variable is plotted on which axis does not matter.

For the example above, the direction of the association is positive. This means that people who perceived the past month as being good reported feeling more happy, whereas people who perceived the month as being bad reported feeling less happy.

In a scatterplot, the dots form a pattern that extends from the bottom left to the upper right (just as they do in Figure 1). The  r  value for a positive correlation is indicated by a positive number (although, the positive sign is usually omitted). Here, the  r  value is 0.81.

Figure 2 shows a  negative correlation,   the association between the average height of males in a country ( y -axis) and the pathogen prevalence, or commonness of disease, of that country ( x -axis). In this scatterplot, each dot represents a country. Notice how the dots extend from the top left to the bottom right. What does this mean in real-world terms? It means that people are shorter in parts of the world where there is more disease. The  r  value for a negative correlation is indicated by a negative number—that is, it has a minus (−) sign in front of it. Here, it is −0.83.

The strength of a correlation has to do with how well the two variables align. Recall that in Professor Dunn’s correlational study, spending on others positively correlated with happiness: the more money people reported spending on others, the happier they reported to be. At this point, you may be thinking to yourself, “I know a very generous person who gave away lots of money to other people but is miserable!” Or maybe you know of a very stingy person who is happy as can be. Yes, there might be exceptions. If an association has many exceptions, it is considered a weak correlation. If an association has few or no exceptions, it is considered a strong correlation. A strong correlation is one in which the two variables always, or almost always, go together. In the example of happiness and how good the month has been, the association is strong. The stronger a correlation is, the tighter the dots in the scatterplot will be arranged along a sloped line. [1]

Problems with correlation

If generosity and happiness are positively correlated, should we conclude that being generous causes happiness? Similarly, if height and pathogen prevalence are negatively correlated, should we conclude that disease causes shortness? From a correlation alone, we can’t be certain. For example, in the first case it may be that happiness causes generosity, or that generosity causes happiness. Or, a third variable might cause both happiness  and  generosity, creating the illusion of a direct link between the two. For example, wealth could be the third variable that causes both greater happiness and greater generosity. This is why correlation does not mean causation—an often repeated phrase among psychologists. [2]

Correlation Does Not Indicate Causation

Correlational research is useful because it allows us to discover the strength and direction of relationships that exist between two variables. However, correlation is limited because establishing the existence of a relationship tells us little about cause and effect . While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable , is actually causing the systematic movement in our variables of interest. In the  depression and negative thinking   example mentioned earlier, stress  is a confounding variable that could account for the relationship between the two variables.   

Even when we cannot point to clear confounding variables, we should not assume that a correlation between two variables implies that one variable causes changes in another. This can be frustrating when a cause-and-effect relationship seems clear and intuitive. Think back to our example about the relationship between depression and disturbance in normal sleep patterns.  It seems reasonable to assume that s leep disturbance might cause a higher score on a measure of depression, just as a high degree of depression might cause more disturbed sleep patterns , but if we were limited to  correlational research , we would be overstepping our bounds by making this assumption.  Both depression and sleep disturbance could be due to an underlying physiological disorder o r any to other third variable that you have not measured .

Unfortunately, people mistakenly make claims of causation as a function of correlations all the time.   While correlational research is invaluable in identifying relationships among variables, a major limitation is the inability to establish causality.  The correlational method does not involve manipulation of the variables of interest. In the previous example, the experimenter does not manipulate people’s depressive symptoms or sleep patterns.  Psychologists want to make statements about cause and effect, but the only way to do that is to conduct an experiment to answer a research question. The next section describes how  investigators use experimental methods in which the experimenter manipulates one or more variables of interest and observes their effects on other variables or outcomes under controlled conditions.

In this video, we discuss one of the best methods psychologists have for predicting behaviors: correlation. But does that mean that a behavior is absolutely going to happen? Let’s find out!

You can view the transcript for “#5 Correlation vs. Causation – Psy 101” here (opens in new window) .

Think It Over

Consider why correlational research is often used in the study of abnormal behavior. If correlational designs do not demonstrate causation, why do researchers make causal claims regarding their results? Are there instances when correlational results could demonstrate causation?

cause-and-effect relationship:  changes in one variable cause the changes in the other variable; can be determined only through an experimental research design

confirmation bias:  tendency to ignore evidence that disproves ideas or beliefs

confounding variable:  unanticipated outside factor that affects both variables of interest,\; often gives the false impression that changes in one variable causes changes in the other variable, when, in actuality, the outside factor causes changes in both variables

correlation: the relationship between two or more variables; when two variables are correlated, one variable changes as the other does

correlation coefficient:  number from -1 to +1, indicating the strength and direction of the relationship between variables, and usually represented by r

negative correlation:  two variables change in different directions, with one becoming larger as the other becomes smaller; a negative correlation is not the same thing as no correlation

positive correlation:  two variables change in the same direction, both becoming either larger or smaller

CC Licensed Content, Shared Previously

• Correlational Research . Authored by : Sonja Ann Miller for Lumen Learning.  Provided by : Lumen Learning.  License :  CC BY: Attribution
• Analyzing Findings.  Authored by : OpenStax College.  Located at :  http://cnx.org/contents/[email protected]:mfArybye@7/Analyzing-Findings .  License :  CC BY: Attribution .  License Terms : Download for free at http://cnx.org/contents/[email protected]
• Research Designs.  Authored by : Christie Napa Scollon .  Provided by : Singapore Management University.  Located at :  https://nobaproject.com/modules/research-designs .  Project : The Noba Project.  License :  CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

All Rights Reserved Content

• Correlation vs. Causality: Freakonomics Movie.  Located at :  https://www.youtube.com/watch?v=lbODqslc4Tg .  License :  Other .  License Terms : Standard YouTube License
• Scollon, C. N. (2020). Research designs. In R. Biswas-Diener & E. Diener (Eds), Noba textbook series: Psychology. Champaign, IL: DEF publishers. Retrieved from http://noba.to/acxb2thy ↵

Correlational Research Copyright © by Meredith Palm is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

Share This Book

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

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

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

Prevent plagiarism. Run a free check.

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

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 September 9, 2024, from https://www.scribbr.com/working-with-sources/finding-sources/

Is this article helpful?

Eoghan Ryan

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

✔ Free APA citation check included ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

Candace Owens: “I really do encourage people to be conspiracy theorists”

Written by Media Matters Staff

Published 09/12/24 10:22 AM EDT

Citation From the September 11, 2024, edition of Candace Owens , posted to Rumble

CANDACE OWENS: This is how you know you're getting close to truth. I mean, what a ridiculous reason to take a video down. You can't say the words satanic cults. Obviously, there is one. That's the only reason why you would say no one can hear this is because there was truth in that. And I will be posting that interview on to X later today, and you can still find that on Spotify, Apple, and here on Rumble. So I advise you listen to it before they try to delete these things off of the internet because I'm still convinced that the World Economic Forum running that simulation that they did a while ago about what would happen if we had an internet pandemic and they had to force shut down the entire internet -- I still think they're going to do that, just like they predicted the COVID pandemic. I think they're essentially running tests to see what would happen if they brought down the internet so that they could sanitize it, as they said in that simulation. They said we're going to have to sanitize the internet if there's just a virus that's all over the web. We, the government, are gonna have to take control just like with COVID. But this time, it's going to be on the web.

So I really do encourage people to be conspiracy theorists. Consider that the government is showing you their hand and are telling you what they want to do because they realize that too many people are waking up to what's happening today. Print things out, buy books, get them into your possession, and make sure that we stay organized, that we have our own websites, that we have our own technology. It's why I'm building my own database. We're gonna have to do that. But don't just rely on the internet. Like I said, buy books, get hard copies, photocopy the things that you need to remember, write them down, go old school, that's really going to be our only guard against what I believe to be a government that fully just wants to wipe out history so that they can just make us live in an ever Orwellian present.

Eating Eggs May Lower Your Risk Of Cognitive Decline, New Research Says

Dietitians credit the food's "anti-inflammatory benefits."

Women's Health may earn commission from the links on this page, but we only feature products we believe in. Why Trust Us?

About two out of three Americans have some level of cognitive decline by the age of 70. Given that, it’s understandable to want to keep your mind sharp as you age. Now, a new study suggests that eating eggs may help.

The study, which was published in the journal Nutrients , found a link between eating eggs and a lowered risk of cognitive decline as you age. It seems random, but given how easily accessible the ingredient is, this is definitely worth paying attention to. Here’s what the study found—plus, how you can incorporate more eggs into your diet.

Meet the experts : Scott Keatley, RD, is co-owner of Keatley Medical Nutrition Therapy . Jessica Cording, RD , is the author of The Little Book of Game-Changers . Keri Gans, RD , is the author of The Small Change Diet .

What did the study find?

For the study, researchers analyzed data from 890 adults over 55 who participated in a long-term observational study called the Rancho Bernardo Study. The researchers looked at how often the participants ate eggs, as well as the results of performance tests that looked at things like executive function, language, recall, and mental flexibility.

When looking at dietary patterns, the researchers discovered that 16.5 percent of women and 14 percent of men said they never ate eggs, but nearly four percent of women and seven percent of men said they had eggs more than five times a week.

After crunching the data, the researchers found that women who ate more eggs had less of a drop in fluency scores—which look at things like executive function and semantic memory (i.e. recalling words, concepts, and numbers)—over time. The researchers specifically found that the risk dropped by 0.1 for every category of egg consumption.

What does that mean? Basically, eating more eggs was linked to a lower risk of cognitive decline.

Do eggs prevent cognitive decline?

It’s tough to say based on this study alone that eggs prevent cognitive decline. In fact, the study simply found that there was a link, but didn’t prove that eating eggs actually caused the lower risk.

However, research has found that some nutrients in eggs can help support brain function. Choline, which is found in the egg yolk , has been linked to better cognition, and eggs in general are thought of as a brain-friendly food.

"Research has found this nutrient to have anti-inflammatory benefits which may help protect against cognitive decline," explains Keri Gans, RD , author of The Small Change Diet .

A 2021 observational study published in the Journal of Nutritional Science also found that people who ate an intermediate number of eggs (up to 1.5 eggs a week) had lower rates of cognitive decline than those who ate about half an egg or less on a weekly basis.

“Eggs are one of the best sources of choline, a nutrient that is crucial for brain development and function,” explains Scott Keatley, RD , co-owner of Keatley Medical Nutrition Therapy. “Choline is a precursor to acetylcholine, a neurotransmitter involved in memory and learning.”

Eggs also contain vitamin B12, “which is important for maintaining the health of nerve cells and can help prevent memory loss and cognitive decline,” Keatley says. They also have lutein and zeaxanthin, antioxidants that help protect against oxidative stress and inflammation. Both of those are linked to cognitive decline, Keatley says.

“Eggs are a really good source of protein and fat, too,” says Jessica Cording, RD , is the author of The Little Book of Game-Changers . “That’s important for blood sugar stability. We’ve learned in recent years that blood sugar plays a role in cognitive health.”

Should I incorporate eggs into my diet?

Eggs are thought of as an overall healthy food and a good source of protein, Keatley says.

“They are nutrient-dense, providing high-quality protein and essential nutrients such as vitamins A, D, E, and K, along with minerals like selenium and zinc,” he explains. “The protein and fat content in eggs can aid in satiety and weight management by helping you feel full longer. Additionally, the amino acids found in eggs support muscle repair and growth, which is particularly beneficial for maintaining muscle mass as you age.”

If you’re looking for ways to get more eggs in your life , Keatley recommends eating them scrambled, poached, or boiled. You can also add them to a veggie omelet or use them as a topping for avocado toast .

“ Hard-boiled eggs make a convenient and nutritious snack option,” Keatley points out. “They can also be chopped and added to salads for extra protein and flavor.”

If you’re not in the habit of eating eggs, Cording suggests hard-boiling a few in advance so you can grab and go, or making egg-and-veggie cups in muffin tins for a quick snack.

Cording says that most people can safely consume up to seven eggs a week without worrying about a poor impact on their cholesterol levels. As a result, there are plenty of chances to load up on eggs when the mood strikes.

Why Is Puberty Starting Earlier And Earlier?

Zepbound May Now Be Easier to Get—And Cheaper

‘My Back Pain Turned Out To Be A Rare Disease’

Are We Entering The Fiber Supplement Renaissance?

Are Tampons Safe? Study Finds Arsenic, Lead

Where Taylor Swift Stands On Reproductive Rights

The Red Light Therapy Trend, Explained By Experts

How Dense Breasts Affect Your Breast Cancer Risk

Best Sauna Blankets, Tested By Experts And Editors

New Study Says Coffee May Help With Muscle Mass

Selena Gomez Opens Up About Not Carrying Children

Kate Middleton's Cancer Diagnosis, Explained

Musk ambrette may be linked to rise in early puberty, study finds: What products contain it?

Girls have been hitting puberty at increasingly younger ages over the past few decades. new research looks at environmental factors that may play a role., by maura hohman | today • published september 12, 2024 • updated on september 12, 2024 at 2:55 pm.

A new study points to a possible factor in the trend of children reaching puberty at younger ages in recent decades. The first-of-its-kind research found that a common chemical, musk ambrette, used to add scent to a wide range of products, may cause the body to release puberty-related hormones earlier than it would otherwise.

The research, published in the journal Endocrinology, is the first to look at how chemicals found in the environment may affect the brain, possibly leading to early puberty, Dr. Natalie Shaw, a pediatric endocrinologist at the National Institute of Environmental Health Sciences and co-senior author of the study,  told NBC News .

However, it's too early to say whether musk ambrette is definitely playing a role in the early puberty trend, experts stress — though there may be some small steps that parents can take to err on the side of caution.

24/7 New York news stream: Watch NBC 4 free wherever you are

Here’s what to know about the research, musk ambrette and the products that contain it.

Puberty starting earlier in girls and boys

Research from 2020 shows  that the average age of starting puberty for girls has decreased by about three months each decade from 1977 to 2013.  A study from 2012 found  that boys were hitting puberty anywhere from six months to two years earlier than previous research had indicated.

Get Tri-state area news delivered to your inbox. Sign up for NBC New York's News Headlines newsletter.

And a  large study in May 2024 published in JAMA , which looked at over 70,000 females born between 1950 and 2005, found that the average age at which girls had their first periods has decreased, and it's taking longer on average for periods to become regular.

Dick Van Dyke says this is the ‘secret weapon' for his health at 98 years old

Boar's Head to stop making liverwurst, close plant linked to deadly listeria outbreak

The reason behind the drop in age at which children are starting puberty has eluded experts for years. Some have pointed to the rise in obesity in children, less nutritious diets, and exposure to phthalates, a substance added to plastics, but nothing is proven.

Shaw believes that because the change in puberty onset has happened so quickly, it's likely due to "environmental factors," she told NBC News.

Starting puberty early has been linked to adverse health outcomes, such as increased risk of breast, endometrial and testicular cancers; diabetes; heart disease; obesity; and psychological issues.

Musk ambrette may play a role in rise in early puberty, new research finds

To conduct the study, the researchers looked at over 10,000 compounds using a library of licensed pharmaceuticals, environmental chemicals and dietary supplements.

They found that musk ambrette, which is a synthetic form of musk, may be able to attach to a receptor in the brain associated with puberty and prompt it to release a hormone called  GnRH , which affects the sexual maturation of organs and production of sex hormones, like estrogen, testosterone and progesterone.

"The ability of these compounds to stimulate these brain receptors raises the possibility that they may prematurely activate the reproductive axis in children," Shaw tells TODAY.com via email.

There were several types of chemicals that the researchers identified that could influence puberty, including cholinergic agonists, a type of medicine, and musk ambrette.

"Musk ambrette is of potential concern for children because it can be found in personal care products. A limited number of studies in rats also suggest that it can cross the blood-brain barrier. Children are less likely to encounter cholinergic agonists in their daily lives," Shaw explains.

"It is important to conduct confirmatory studies in girls with early puberty, but these compounds deserve greater attention," she adds.

What is musk ambrette?

Musk ambrette is a synthetic form of musk. It's often used to add scent to personal care and household products or as a flavoring food additive, Michael Hansen, Ph.D., senior scientist at Consumer Reports, tells TODAY.com.

The Flavor and Extract Manufacturer Association (FEMA), a major flavor trade group in the U.S.,  does not give musk ambrette its "generally recognized as safe"  designation. The European Union has prohibited the use of musk ambrette in cosmetics, and Canada has also restricted it.

"Exposure to (musk ambrette compounds) is also of concern because they can bioaccumulate in human tissues," Shaw explains. "Studies have detected these compounds in maternal blood, umbilical cord blood, and breast milk, highlighting potential risks for children."

What products contain musk ambrette?

A range of products in the U.S. may contain musk ambrette. According to Hansen and Shaw, these include:

• Air fresheners
• Cleaning products
• Perfumes, especially inexpensive or counterfeit fragrances
• Essential oils
• Cosmetics and other scented personal care products, like shampoos, deodorant and body wash

“If I had to guess, I would suspect that the bulk of the exposure (to musk ambrette) is coming in through personal care products," Hansen says. "Since it's a fragrance, that means ... you're inhaling it. ... That goes straight into the mucous membranes (in the nose), which are far easier for chemicals to get to the brain."

What can parents do?

Some experts say it's too early in the research to suggest that parents consider taking action to reduce their children's exposure to musk ambrette, and it would also be premature to ban or restrict it, based on this research.

However, Shaw and Hansen both agree there's no harm in trying to limit kids' exposure to the chemical and its related compounds, such as musk xylene and musk ketone. And Hansen says the research ideally should lead to follow-up studies looking at musk ambrette exposure in communities more likely to experience early puberty.

In the mean time, Hansen suggests avoiding products that have musk ambrette on the ingredients label. However, know that some products that use musk ambrette may only list it as synthetic or natural fragrance or flavoring, Hansen adds.

So, you may want to consider just cutting back on scented products where the scent isn't necessary, such as lotions, shampoos and body washes.

This article first appeared on  TODAY.com . Read more from TODAY here:

• Snoop Dogg attends his grandkids' birthday parties ... in costume
• Why this grandma refuses to buy her grandchildren birthday gifts
• Carson Daly brings son Jackson, 15, to VMAs: 'We're having a blast'

This article tagged under:

• Diversity & Inclusion
• Community Values
• Visiting MIT Physics
• People Directory
• Faculty Directory
• Faculty Awards
• History of MIT Physics
• Policies and Procedures
• Departmental Committees
• Academic Programs Team
• Finance Team
• Meet the Academic Programs Team
• Prospective Students
• Requirements
• Employment Opportunities
• Research Opportunities
• Graduate Admissions
• Doctoral Guidelines
• Financial Support
• Graduate Student Resources
• PhD in Physics, Statistics, and Data Science
• MIT LEAPS Program
• Physics Student Groups
• for Undergraduate Students
• for Graduate Students
• Mentoring Programs Info for Faculty
• Non-degree Programs
• Student Awards & Honors
• Astrophysics Observation, Instrumentation, and Experiment
• Astrophysics Theory
• Atomic Physics
• Condensed Matter Experiment
• Condensed Matter Theory
• High Energy and Particle Theory
• Nuclear Physics Experiment
• Particle Physics Experiment
• Plasma Physics
• Quantum Gravity and Field Theory
• Quantum Information Science
• Strong Interactions and Nuclear Theory
• Center for Theoretical Physics
• Affiliated Labs & Centers
• Program Founder
• Competition
• Donor Profiles
• Patrons of Physics Fellows Society
• Giving Opportunties
• Latest Physics News
• Physics Journal: Fall 2023 Edition
• Events Calendar
• Physics Colloquia
• Search for: Search

Study: Early dark energy could resolve cosmology’s two biggest puzzles

In the universe’s first billion years, this brief and mysterious force could have produced more bright galaxies than theory predicts..

A new study by MIT physicists proposes that a mysterious force known as early dark energy could solve two of the biggest puzzles in cosmology and fill in some major gaps in our understanding of how the early universe evolved.

One puzzle in question is the “Hubble tension,” which refers to a mismatch in measurements of how fast the universe is expanding. The other involves observations of numerous early, bright galaxies that existed at a time when the early universe should have been much less populated.

Now, the MIT team has found that both puzzles could be resolved if the early universe had one extra, fleeting ingredient: early dark energy. Dark energy is an unknown form of energy that physicists suspect is driving the expansion of the universe today. Early dark energy is a similar, hypothetical phenomenon that may have made only a brief appearance, influencing the expansion of the universe in its first moments before disappearing entirely.

Some physicists have suspected that early dark energy could be the key to solving the Hubble tension, as the mysterious force could accelerate the early expansion of the universe by an amount that would resolve the measurement mismatch.

The MIT researchers have now found that early dark energy could also explain the baffling number of bright galaxies that astronomers have observed in the early universe. In their new study, reported today in the Monthly Notices of the Royal Astronomical Society , the team modeled the formation of galaxies in the universe’s first few hundred million years. When they incorporated a dark energy component only in that earliest sliver of time, they found the number of galaxies that arose from the primordial environment bloomed to fit astronomers’ observations.

“ You have these two looming open-ended puzzles,” says study co-author Rohan Naidu , a postdoc in MIT’s Kavli Institute for Astrophysics and Space Research. “We find that in fact, early dark energy is a very elegant and sparse solution to two of the most pressing problems in cosmology.”

The study’s co-authors include lead author and Kavli postdoc Xuejian (Jacob) Shen, and MIT professor of physics Mark Vogelsberger , along with Michael Boylan-Kolchin at the University of Texas at Austin, and Sandro Tacchella at the University of Cambridge.

Big city lights

Based on standard cosmological and galaxy formation models, the universe should have taken its time spinning up the first galaxies. It would have taken billions of years for primordial gas to coalesce into galaxies as large and bright as the Milky Way.

But in 2023, NASA’s James Webb Space Telescope (JWST) made a startling observation. With an ability to peer farther back in time than any observatory to date, the telescope uncovered a surprising number of bright galaxies as large as the modern Milky Way within the first 500 million years, when the universe was just 3 percent of its current age.

“The bright galaxies that JWST saw would be like seeing a clustering of lights around big cities, whereas theory predicts something like the light around more rural settings like Yellowstone National Park,” Shen says. “And we don’t expect that clustering of light so early on.”

For physicists, the observations imply that there is either something fundamentally wrong with the physics underlying the models or a missing ingredient in the early universe that scientists have not accounted for. The MIT team explored the possibility of the latter, and whether the missing ingredient might be early dark energy.

Physicists have proposed that early dark energy is a sort of antigravitational force that is turned on only at very early times. This force would counteract gravity’s inward pull and accelerate the early expansion of the universe, in a way that would resolve the mismatch in measurements. Early dark energy, therefore, is considered the most likely solution to the Hubble tension.

Galaxy skeleton

The MIT team explored whether early dark energy could also be the key to explaining the unexpected population of large, bright galaxies detected by JWST. In their new study, the physicists considered how early dark energy might affect the early structure of the universe that gave rise to the first galaxies. They focused on the formation of dark matter halos — regions of space where gravity happens to be stronger, and where matter begins to accumulate.

“We believe that dark matter halos are the invisible skeleton of the universe,” Shen explains. “Dark matter structures form first, and then galaxies form within these structures. So, we expect the number of bright galaxies should be proportional to the number of big dark matter halos.”

The team developed an empirical framework for early galaxy formation, which predicts the number, luminosity, and size of galaxies that should form in the early universe, given some measures of “cosmological parameters.” Cosmological parameters are the basic ingredients, or mathematical terms, that describe the evolution of the universe.

Physicists have determined that there are at least six main cosmological parameters, one of which is the Hubble constant — a term that describes the universe’s rate of expansion. Other parameters describe density fluctuations in the primordial soup, immediately after the Big Bang, from which dark matter halos eventually form.

The MIT team reasoned that if early dark energy affects the universe’s early expansion rate, in a way that resolves the Hubble tension, then it could affect the balance of the other cosmological parameters, in a way that might increase the number of bright galaxies that appear at early times. To test their theory, they incorporated a model of early dark energy (the same one that happens to resolve the Hubble tension) into an empirical galaxy formation framework to see how the earliest dark matter structures evolve and give rise to the first galaxies.

“What we show is, the skeletal structure of the early universe is altered in a subtle way where the amplitude of fluctuations goes up, and you get bigger halos, and brighter galaxies that are in place at earlier times, more so than in our more vanilla models,” Naidu says. “It means things were more abundant, and more clustered in the early universe.”

“A priori, I would not have expected the abundance of JWST’s early bright galaxies to have anything to do with early dark energy, but their observation that EDE pushes cosmological parameters in a direction that boosts the early-galaxy abundance is interesting,” says Marc Kamionkowski, professor of theoretical physics at Johns Hopkins University, who was not involved with the study. “I think more work will need to be done to establish a link between early galaxies and EDE, but regardless of how things turn out, it’s a clever — and hopefully ultimately fruitful — thing to try.”

“ We demonstrated the potential of early dark energy as a unified solution to the two major issues faced by cosmology. This might be an evidence for its existence if the observational findings of JWST get further consolidated,” Vogelsberger concludes. “In the future, we can incorporate this into large cosmological simulations to see what detailed predictions we get.”

This research was supported, in part, by NASA and the National Science Foundation.

• Paper: “Early Galaxies and Early Dark Energy: A Unified Solution to the Hubble Tension and Puzzles of Massive Bright Galaxies revealed by JWST”

Related News

Novel Architecture Makes Neural Networks More Understandable

Atoms on the edge

Study predicts a new quantum anomalous crystal in fractionally filled moiré superlattices