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Scopus Search

Scopus quickly delivers the information you're looking for from over 92m records. Updated daily, Scopus features state-of-the-art search tools and filters to empower research efficiency.

Increase research efficiency

Having access to comprehensive content and high-quality data is only effective if you can easily find the information you need. Uncovering trends, discovering sources and potential collaborators, and building deeper insights require effective search tools that can identify the right results.

Identify trends for key topics

Scopus’ literature search is built to distill massive amounts of information down to the most relevant documents and information in less time.

With Scopus you can search and filter results in the following ways:

Document search : Search directly from the homepage and use detailed search options to ensure you find the document(s) you want

Author search : Search for a specific author by name or by Open Research and Contributor Identifier ID (ORCID)

Affiliation search : Identify and assess an affiliation’s scholarly output, collaborating institutions and top authors

Advanced search : Narrow the scope of your search using field codes, proximity operators and/or Boolean operators

Refine results : Scopus makes it easy to refine your results list to specific categories of documents

Language interface : The Scopus interface is available in Chinese and Japanese; content is not localized, but you can switch the interface to one of these language options (and switch back to English, the default language) at the bottom of any Scopus page

Quick reference guide

Learn how to easily start your search from the homepage and use all the features in Scopus with this handy Quick Reference Guide.

Download the guide   opens in new tab/window .

Learn how Scopus can help your organization achieve its goals.

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Search Help

Get the most out of Google Scholar with some helpful tips on searches, email alerts, citation export, and more.

Finding recent papers

Your search results are normally sorted by relevance, not by date. To find newer articles, try the following options in the left sidebar:

• click "Since Year" to show only recently published papers, sorted by relevance;
• click "Sort by date" to show just the new additions, sorted by date;
• click the envelope icon to have new results periodically delivered by email.

Locating the full text of an article

Abstracts are freely available for most of the articles. Alas, reading the entire article may require a subscription. Here're a few things to try:

• click a library link, e.g., "FindIt@Harvard", to the right of the search result;
• click a link labeled [PDF] to the right of the search result;
• click "All versions" under the search result and check out the alternative sources;
• click "Related articles" or "Cited by" under the search result to explore similar articles.

If you're affiliated with a university, but don't see links such as "FindIt@Harvard", please check with your local library about the best way to access their online subscriptions. You may need to do search from a computer on campus, or to configure your browser to use a library proxy.

Getting better answers

If you're new to the subject, it may be helpful to pick up the terminology from secondary sources. E.g., a Wikipedia article for "overweight" might suggest a Scholar search for "pediatric hyperalimentation".

If the search results are too specific for your needs, check out what they're citing in their "References" sections. Referenced works are often more general in nature.

Similarly, if the search results are too basic for you, click "Cited by" to see newer papers that referenced them. These newer papers will often be more specific.

Explore! There's rarely a single answer to a research question. Click "Related articles" or "Cited by" to see closely related work, or search for author's name and see what else they have written.

Searching Google Scholar

Use the "author:" operator, e.g., author:"d knuth" or author:"donald e knuth".

Put the paper's title in quotations: "A History of the China Sea".

You'll often get better results if you search only recent articles, but still sort them by relevance, not by date. E.g., click "Since 2018" in the left sidebar of the search results page.

To see the absolutely newest articles first, click "Sort by date" in the sidebar. If you use this feature a lot, you may also find it useful to setup email alerts to have new results automatically sent to you.

Note: On smaller screens that don't show the sidebar, these options are available in the dropdown menu labelled "Year" right below the search button.

Select the "Case law" option on the homepage or in the side drawer on the search results page.

It finds documents similar to the given search result.

It's in the side drawer. The advanced search window lets you search in the author, title, and publication fields, as well as limit your search results by date.

Select the "Case law" option and do a keyword search over all jurisdictions. Then, click the "Select courts" link in the left sidebar on the search results page.

Tip: To quickly search a frequently used selection of courts, bookmark a search results page with the desired selection.

Access to articles

For each Scholar search result, we try to find a version of the article that you can read. These access links are labelled [PDF] or [HTML] and appear to the right of the search result. For example:

A paper that you need to read

Access links cover a wide variety of ways in which articles may be available to you - articles that your library subscribes to, open access articles, free-to-read articles from publishers, preprints, articles in repositories, etc.

When you are on a campus network, access links automatically include your library subscriptions and direct you to subscribed versions of articles. On-campus access links cover subscriptions from primary publishers as well as aggregators.

Off-campus access

Off-campus access links let you take your library subscriptions with you when you are at home or traveling. You can read subscribed articles when you are off-campus just as easily as when you are on-campus. Off-campus access links work by recording your subscriptions when you visit Scholar while on-campus, and looking up the recorded subscriptions later when you are off-campus.

We use the recorded subscriptions to provide you with the same subscribed access links as you see on campus. We also indicate your subscription access to participating publishers so that they can allow you to read the full-text of these articles without logging in or using a proxy. The recorded subscription information expires after 30 days and is automatically deleted.

In addition to Google Scholar search results, off-campus access links can also appear on articles from publishers participating in the off-campus subscription access program. Look for links labeled [PDF] or [HTML] on the right hand side of article pages.

Anne Author , John Doe , Jane Smith , Someone Else

In this fascinating paper, we investigate various topics that would be of interest to you. We also describe new methods relevant to your project, and attempt to address several questions which you would also like to know the answer to. Lastly, we analyze …

You can disable off-campus access links on the Scholar settings page . Disabling off-campus access links will turn off recording of your library subscriptions. It will also turn off indicating subscription access to participating publishers. Once off-campus access links are disabled, you may need to identify and configure an alternate mechanism (e.g., an institutional proxy or VPN) to access your library subscriptions while off-campus.

Email Alerts

Do a search for the topic of interest, e.g., "M Theory"; click the envelope icon in the sidebar of the search results page; enter your email address, and click "Create alert". We'll then periodically email you newly published papers that match your search criteria.

No, you can enter any email address of your choice. If the email address isn't a Google account or doesn't match your Google account, then we'll email you a verification link, which you'll need to click to start receiving alerts.

This works best if you create a public profile , which is free and quick to do. Once you get to the homepage with your photo, click "Follow" next to your name, select "New citations to my articles", and click "Done". We will then email you when we find new articles that cite yours.

Search for the title of your paper, e.g., "Anti de Sitter space and holography"; click on the "Cited by" link at the bottom of the search result; and then click on the envelope icon in the left sidebar of the search results page.

First, do a search for your colleague's name, and see if they have a Scholar profile. If they do, click on it, click the "Follow" button next to their name, select "New articles by this author", and click "Done".

If they don't have a profile, do a search by author, e.g., [author:s-hawking], and click on the mighty envelope in the left sidebar of the search results page. If you find that several different people share the same name, you may need to add co-author names or topical keywords to limit results to the author you wish to follow.

We send the alerts right after we add new papers to Google Scholar. This usually happens several times a week, except that our search robots meticulously observe holidays.

There's a link to cancel the alert at the bottom of every notification email.

If you created alerts using a Google account, you can manage them all here . If you're not using a Google account, you'll need to unsubscribe from the individual alerts and subscribe to the new ones.

Google Scholar library

Google Scholar library is your personal collection of articles. You can save articles right off the search page, organize them by adding labels, and use the power of Scholar search to quickly find just the one you want - at any time and from anywhere. You decide what goes into your library, and we’ll keep the links up to date.

You get all the goodies that come with Scholar search results - links to PDF and to your university's subscriptions, formatted citations, citing articles, and more!

Library help

Find the article you want to add in Google Scholar and click the “Save” button under the search result.

Click “My library” at the top of the page or in the side drawer to view all articles in your library. To search the full text of these articles, enter your query as usual in the search box.

Find the article you want to remove, and then click the “Delete” button under it.

• To add a label to an article, find the article in your library, click the “Label” button under it, select the label you want to apply, and click “Done”.
• To view all the articles with a specific label, click the label name in the left sidebar of your library page.
• To remove a label from an article, click the “Label” button under it, deselect the label you want to remove, and click “Done”.
• To add, edit, or delete labels, click “Manage labels” in the left column of your library page.

Only you can see the articles in your library. If you create a Scholar profile and make it public, then the articles in your public profile (and only those articles) will be visible to everyone.

Your profile contains all the articles you have written yourself. It’s a way to present your work to others, as well as to keep track of citations to it. Your library is a way to organize the articles that you’d like to read or cite, not necessarily the ones you’ve written.

Citation Export

Click the "Cite" button under the search result and then select your bibliography manager at the bottom of the popup. We currently support BibTeX, EndNote, RefMan, and RefWorks.

Err, no, please respect our robots.txt when you access Google Scholar using automated software. As the wearers of crawler's shoes and webmaster's hat, we cannot recommend adherence to web standards highly enough.

Sorry, we're unable to provide bulk access. You'll need to make an arrangement directly with the source of the data you're interested in. Keep in mind that a lot of the records in Google Scholar come from commercial subscription services.

Sorry, we can only show up to 1,000 results for any particular search query. Try a different query to get more results.

Content Coverage

Google Scholar includes journal and conference papers, theses and dissertations, academic books, pre-prints, abstracts, technical reports and other scholarly literature from all broad areas of research. You'll find works from a wide variety of academic publishers, professional societies and university repositories, as well as scholarly articles available anywhere across the web. Google Scholar also includes court opinions and patents.

We index research articles and abstracts from most major academic publishers and repositories worldwide, including both free and subscription sources. To check current coverage of a specific source in Google Scholar, search for a sample of their article titles in quotes.

While we try to be comprehensive, it isn't possible to guarantee uninterrupted coverage of any particular source. We index articles from sources all over the web and link to these websites in our search results. If one of these websites becomes unavailable to our search robots or to a large number of web users, we have to remove it from Google Scholar until it becomes available again.

Our meticulous search robots generally try to index every paper from every website they visit, including most major sources and also many lesser known ones.

That said, Google Scholar is primarily a search of academic papers. Shorter articles, such as book reviews, news sections, editorials, announcements and letters, may or may not be included. Untitled documents and documents without authors are usually not included. Website URLs that aren't available to our search robots or to the majority of web users are, obviously, not included either. Nor do we include websites that require you to sign up for an account, install a browser plugin, watch four colorful ads, and turn around three times and say coo-coo before you can read the listing of titles scanned at 10 DPI... You get the idea, we cover academic papers from sensible websites.

That's usually because we index many of these papers from other websites, such as the websites of their primary publishers. The "site:" operator currently only searches the primary version of each paper.

It could also be that the papers are located on examplejournals.gov, not on example.gov. Please make sure you're searching for the "right" website.

That said, the best way to check coverage of a specific source is to search for a sample of their papers using the title of the paper.

Ahem, we index papers, not journals. You should also ask about our coverage of universities, research groups, proteins, seminal breakthroughs, and other dimensions that are of interest to users. All such questions are best answered by searching for a statistical sample of papers that has the property of interest - journal, author, protein, etc. Many coverage comparisons are available if you search for [allintitle:"google scholar"], but some of them are more statistically valid than others.

Currently, Google Scholar allows you to search and read published opinions of US state appellate and supreme court cases since 1950, US federal district, appellate, tax and bankruptcy courts since 1923 and US Supreme Court cases since 1791. In addition, it includes citations for cases cited by indexed opinions or journal articles which allows you to find influential cases (usually older or international) which are not yet online or publicly available.

Legal opinions in Google Scholar are provided for informational purposes only and should not be relied on as a substitute for legal advice from a licensed lawyer. Google does not warrant that the information is complete or accurate.

We normally add new papers several times a week. However, updates to existing records take 6-9 months to a year or longer, because in order to update our records, we need to first recrawl them from the source website. For many larger websites, the speed at which we can update their records is limited by the crawl rate that they allow.

Inclusion and Corrections

We apologize, and we assure you the error was unintentional. Automated extraction of information from articles in diverse fields can be tricky, so an error sometimes sneaks through.

Please write to the owner of the website where the erroneous search result is coming from, and encourage them to provide correct bibliographic data to us, as described in the technical guidelines . Once the data is corrected on their website, it usually takes 6-9 months to a year or longer for it to be updated in Google Scholar. We appreciate your help and your patience.

If you can't find your papers when you search for them by title and by author, please refer your publisher to our technical guidelines .

You can also deposit your papers into your institutional repository or put their PDF versions on your personal website, but please follow your publisher's requirements when you do so. See our technical guidelines for more details on the inclusion process.

We normally add new papers several times a week; however, it might take us some time to crawl larger websites, and corrections to already included papers can take 6-9 months to a year or longer.

Google Scholar generally reflects the state of the web as it is currently visible to our search robots and to the majority of users. When you're searching for relevant papers to read, you wouldn't want it any other way!

If your citation counts have gone down, chances are that either your paper or papers that cite it have either disappeared from the web entirely, or have become unavailable to our search robots, or, perhaps, have been reformatted in a way that made it difficult for our automated software to identify their bibliographic data and references. If you wish to correct this, you'll need to identify the specific documents with indexing problems and ask your publisher to fix them. Please refer to the technical guidelines .

Please do let us know . Please include the URL for the opinion, the corrected information and a source where we can verify the correction.

We're only able to make corrections to court opinions that are hosted on our own website. For corrections to academic papers, books, dissertations and other third-party material, click on the search result in question and contact the owner of the website where the document came from. For corrections to books from Google Book Search, click on the book's title and locate the link to provide feedback at the bottom of the book's page.

General Questions

These are articles which other scholarly articles have referred to, but which we haven't found online. To exclude them from your search results, uncheck the "include citations" box on the left sidebar.

First, click on links labeled [PDF] or [HTML] to the right of the search result's title. Also, check out the "All versions" link at the bottom of the search result.

Second, if you're affiliated with a university, using a computer on campus will often let you access your library's online subscriptions. Look for links labeled with your library's name to the right of the search result's title. Also, see if there's a link to the full text on the publisher's page with the abstract.

Keep in mind that final published versions are often only available to subscribers, and that some articles are not available online at all. Good luck!

Technically, your web browser remembers your settings in a "cookie" on your computer's disk, and sends this cookie to our website along with every search. Check that your browser isn't configured to discard our cookies. Also, check if disabling various proxies or overly helpful privacy settings does the trick. Either way, your settings are stored on your computer, not on our servers, so a long hard look at your browser's preferences or internet options should help cure the machine's forgetfulness.

Not even close. That phrase is our acknowledgement that much of scholarly research involves building on what others have already discovered. It's taken from Sir Isaac Newton's famous quote, "If I have seen further, it is by standing on the shoulders of giants."

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Reference management. Clean and simple.

The top list of academic search engines

1. Google Scholar

4. science.gov, 5. semantic scholar, 6. baidu scholar, get the most out of academic search engines, frequently asked questions about academic search engines, related articles.

Academic search engines have become the number one resource to turn to in order to find research papers and other scholarly sources. While classic academic databases like Web of Science and Scopus are locked behind paywalls, Google Scholar and others can be accessed free of charge. In order to help you get your research done fast, we have compiled the top list of free academic search engines.

Google Scholar is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only lets you find research papers for all academic disciplines for free but also often provides links to full-text PDF files.

• Coverage: approx. 200 million articles
• Abstracts: only a snippet of the abstract is available
• Related articles: ✔
• References: ✔
• Cited by: ✔
• Links to full text: ✔
• Export formats: APA, MLA, Chicago, Harvard, Vancouver, RIS, BibTeX

BASE is hosted at Bielefeld University in Germany. That is also where its name stems from (Bielefeld Academic Search Engine).

• Coverage: approx. 136 million articles (contains duplicates)
• Abstracts: ✔
• Related articles: ✘
• References: ✘
• Cited by: ✘
• Export formats: RIS, BibTeX

CORE is an academic search engine dedicated to open-access research papers. For each search result, a link to the full-text PDF or full-text web page is provided.

• Coverage: approx. 136 million articles
• Links to full text: ✔ (all articles in CORE are open access)
• Export formats: BibTeX

Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need anymore to query all those resources separately!

• Coverage: approx. 200 million articles and reports
• Links to full text: ✔ (available for some databases)
• Export formats: APA, MLA, RIS, BibTeX (available for some databases)

Semantic Scholar is the new kid on the block. Its mission is to provide more relevant and impactful search results using AI-powered algorithms that find hidden connections and links between research topics.

• Coverage: approx. 40 million articles
• Export formats: APA, MLA, Chicago, BibTeX

Although Baidu Scholar's interface is in Chinese, its index contains research papers in English as well as Chinese.

• Coverage: no detailed statistics available, approx. 100 million articles
• Abstracts: only snippets of the abstract are available
• Export formats: APA, MLA, RIS, BibTeX

RefSeek searches more than one billion documents from academic and organizational websites. Its clean interface makes it especially easy to use for students and new researchers.

• Coverage: no detailed statistics available, approx. 1 billion documents
• Abstracts: only snippets of the article are available
• Export formats: not available

Consider using a reference manager like Paperpile to save, organize, and cite your references. Paperpile integrates with Google Scholar and many popular databases, so you can save references and PDFs directly to your library using the Paperpile buttons:

Google Scholar is an academic search engine, and it is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only let's you find research papers for all academic disciplines for free, but also often provides links to full text PDF file.

Semantic Scholar is a free, AI-powered research tool for scientific literature developed at the Allen Institute for AI. Sematic Scholar was publicly released in 2015 and uses advances in natural language processing to provide summaries for scholarly papers.

BASE , as its name suggest is an academic search engine. It is hosted at Bielefeld University in Germany and that's where it name stems from (Bielefeld Academic Search Engine).

CORE is an academic search engine dedicated to open access research papers. For each search result a link to the full text PDF or full text web page is provided.

Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need any more to query all those resources separately!

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• 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/

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Finding Scholarly Articles: Home

What's a Scholarly Article?

Your professor has specified that you are to use scholarly (or primary research or peer-reviewed or refereed or academic) articles only in your paper. What does that mean?

Scholarly or primary research articles are peer-reviewed , which means that they have gone through the process of being read by reviewers or referees  before being accepted for publication. When a scholar submits an article to a scholarly journal, the manuscript is sent to experts in that field to read and decide if the research is valid and the article should be published. Typically the reviewers indicate to the journal editors whether they think the article should be accepted, sent back for revisions, or rejected.

To decide whether an article is a primary research article, look for the following:

• The author’s (or authors') credentials and academic affiliation(s) should be given;
• There should be an abstract summarizing the research;
• The methods and materials used should be given, often in a separate section;
• There are citations within the text or footnotes referencing sources used;
• Results of the research are given;
• There should be discussion   and  conclusion ;
• With a bibliography or list of references at the end.

Caution: even though a journal may be peer-reviewed, not all the items in it will be. For instance, there might be editorials, book reviews, news reports, etc. Check for the parts of the article to be sure.   

You can limit your search results to primary research, peer-reviewed or refereed articles in many databases. To search for scholarly articles in  HOLLIS , type your keywords in the box at the top, and select  Catalog&Articles  from the choices that appear next.   On the search results screen, look for the  Show Only section on the right and click on  Peer-reviewed articles . (Make sure to  login in with your HarvardKey to get full-text of the articles that Harvard has purchased.)

Many of the databases that Harvard offers have similar features to limit to peer-reviewed or scholarly articles.  For example in Academic Search Premier , click on the box for Scholarly (Peer Reviewed) Journals  on the search screen.

Review articles are another great way to find scholarly primary research articles.   Review articles are not considered "primary research", but they pull together primary research articles on a topic, summarize and analyze them.  In Google Scholar , click on Review Articles  at the left of the search results screen. Ask your professor whether review articles can be cited for an assignment.

A note about Google searching.  A regular Google search turns up a broad variety of results, which can include scholarly articles but Google results also contain commercial and popular sources which may be misleading, outdated, etc.  Use Google Scholar  through the Harvard Library instead.

About Wikipedia .  W ikipedia is not considered scholarly, and should not be cited, but it frequently includes references to scholarly articles. Before using those references for an assignment, double check by finding them in Hollis or a more specific subject  database .

Still not sure about a source? Consult the course syllabus for guidance, contact your professor or teaching fellow, or use the Ask A Librarian service.

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• v.106(4); 2018 Oct

A systematic approach to searching: an efficient and complete method to develop literature searches

Associated data.

Creating search strategies for systematic reviews, finding the best balance between sensitivity and specificity, and translating search strategies between databases is challenging. Several methods describe standards for systematic search strategies, but a consistent approach for creating an exhaustive search strategy has not yet been fully described in enough detail to be fully replicable. The authors have established a method that describes step by step the process of developing a systematic search strategy as needed in the systematic review. This method describes how single-line search strategies can be prepared in a text document by typing search syntax (such as field codes, parentheses, and Boolean operators) before copying and pasting search terms (keywords and free-text synonyms) that are found in the thesaurus. To help ensure term completeness, we developed a novel optimization technique that is mainly based on comparing the results retrieved by thesaurus terms with those retrieved by the free-text search words to identify potentially relevant candidate search terms. Macros in Microsoft Word have been developed to convert syntaxes between databases and interfaces almost automatically. This method helps information specialists in developing librarian-mediated searches for systematic reviews as well as medical and health care practitioners who are searching for evidence to answer clinical questions. The described method can be used to create complex and comprehensive search strategies for different databases and interfaces, such as those that are needed when searching for relevant references for systematic reviews, and will assist both information specialists and practitioners when they are searching the biomedical literature.

INTRODUCTION

Librarians and information specialists are often involved in the process of preparing and completing systematic reviews (SRs), where one of their main tasks is to identify relevant references to include in the review [ 1 ]. Although several recommendations for the process of searching have been published [ 2 – 6 ], none describe the development of a systematic search strategy from start to finish.

Traditional methods of SR search strategy development and execution are highly time consuming, reportedly requiring up to 100 hours or more [ 7 , 8 ]. The authors wanted to develop systematic and exhaustive search strategies more efficiently, while preserving the high sensitivity that SR search strategies necessitate. In this article, we describe the method developed at Erasmus University Medical Center (MC) and demonstrate its use through an example search. The efficiency of the search method and outcome of 73 searches that have resulted in published reviews are described in a separate article [ 9 ].

As we aimed to describe the creation of systematic searches in full detail, the method starts at a basic level with the analysis of the research question and the creation of search terms. Readers who are new to SR searching are advised to follow all steps described. More experienced searchers can consider the basic steps to be existing knowledge that will already be part of their normal workflow, although step 4 probably differs from general practice. Experienced searchers will gain the most from reading about the novelties in the method as described in steps 10–13 and comparing the examples given in the supplementary appendix to their own practice.

CREATING A SYSTEMATIC SEARCH STRATEGY

Our methodology for planning and creating a multi-database search strategy consists of the following steps:

• Determine a clear and focused question
• Describe the articles that can answer the question
• Decide which key concepts address the different elements of the question
• Decide which elements should be used for the best results
• Choose an appropriate database and interface to start with
• Document the search process in a text document
• Identify appropriate index terms in the thesaurus of the first database
• Identify synonyms in the thesaurus
• Add variations in search terms
• Use database-appropriate syntax, with parentheses, Boolean operators, and field codes
• Optimize the search
• Evaluate the initial results
• Check for errors
• Translate to other databases
• Test and reiterate

Each step in the process is reflected by an example search described in the supplementary appendix .

1. Determine a clear and focused question

A systematic search can best be applied to a well-defined and precise research or clinical question. Questions that are too broad or too vague cannot be answered easily in a systematic way and will generally result in an overwhelming number of search results. On the other hand, a question that is too specific will result into too few or even zero search results. Various papers describe this process in more detail [ 10 – 12 ].

2. Describe the articles that can answer the question

Although not all clinical or research questions can be answered in the literature, the next step is to presume that the answer can indeed be found in published studies. A good starting point for a search is hypothesizing what the research that can answer the question would look like. These hypothetical (when possible, combined with known) articles can be used as guidance for constructing the search strategy.

3. Decide which key concepts address the different elements of the question

Key concepts are the topics or components that the desired articles should address, such as diseases or conditions, actions, substances, settings, domains (e.g., therapy, diagnosis, etiology), or study types. Key concepts from the research question can be grouped to create elements in the search strategy.

Elements in a search strategy do not necessarily follow the patient, intervention, comparison, outcome (PICO) structure or any other related structure. Using the PICO or another similar framework as guidance can be helpful to consider, especially in the inclusion and exclusion review stage of the SR, but this is not necessary for good search strategy development [ 13 – 15 ]. Sometimes concepts from different parts of the PICO structure can be grouped together into one search element, such as when the desired outcome is frequently described in a certain study type.

4. Decide which elements should be used for the best results

Not all elements of a research question should necessarily be used in the search strategy. Some elements are less important than others or may unnecessarily complicate or restrict a search strategy. Adding an element to a search strategy increases the chance of missing relevant references. Therefore, the number of elements in a search strategy should remain as low as possible to optimize recall.

Using the schema in Figure 1 , elements can be ordered by their specificity and importance to determine the best search approach. Whether an element is more specific or more general can be measured objectively by the number of hits retrieved in a database when searching for a key term representing that element. Depending on the research question, certain elements are more important than others. If articles (hypothetically or known) exist that can answer the question but lack a certain element in their titles, abstracts, or keywords, that element is unimportant to the question. An element can also be unimportant because of expected bias or an overlap with another element.

Schema for determining the optimal order of elements

Bias in elements

The choice of elements in a search strategy can introduce bias through use of overly specific terminology or terms often associated with positive outcomes. For the question “does prolonged breastfeeding improve intelligence outcomes in children?,” searching specifically for the element of duration will introduce bias, as articles that find a positive effect of prolonged breastfeeding will be much more likely to mention time factors in their titles or abstracts.

Overlapping elements

Elements in a question sometimes overlap in their meaning. Sometimes certain therapies are interventions for one specific disease. The Lichtenstein technique, for example, is a repair method for inguinal hernias. There is no need to include an element of “inguinal hernias” to a search for the effectiveness of the Lichtenstein therapy. Likewise, sometimes certain diseases are only found in certain populations. Adding such an overlapping element could lead to missing relevant references.

The elements to use in a search strategy can be found in the plot of elements in Figure 1 , by following the top row from left to right. For this method, we recommend starting with the most important and specific elements. Then, continue with more general and important elements until the number of results is acceptable for screening. Determining how many results are acceptable for screening is often a matter of negotiation with the SR team.

5. Choose an appropriate database and interface to start with

Important factors for choosing databases to use are the coverage and the presence of a thesaurus. For medically oriented searches, the coverage and recall of Embase, which includes the MEDLINE database, are superior to those of MEDLINE [ 16 ]. Each of these two databases has its own thesaurus with its own unique definitions and structure. Because of the complexity of the Embase thesaurus, Emtree, which contains much more specific thesaurus terms than the MEDLINE Medical Subject Headings (MeSH) thesaurus, translation from Emtree to MeSH is easier than the other way around. Therefore, we recommend starting in Embase.

MEDLINE and Embase are available through many different vendors and interfaces. The choice of an interface and primary database is often determined by the searcher’s accessibility. For our method, an interface that allows searching with proximity operators is desirable, and full functionality of the thesaurus, including explosion of narrower terms, is crucial. We recommend developing a personal workflow that always starts with one specific database and interface.

6. Document the search process in a text document

We advise designing and creating the complete search strategies in a log document, instead of directly in the database itself, to register the steps taken and to make searches accountable and reproducible. The developed search strategies can be copied and pasted into the desired databases from the log document. This way, the searcher is in control of the whole process. Any change to the search strategy should be done in the log document, assuring that the search strategy in the log is always the most recent.

7. Identify appropriate index terms in the thesaurus of the first database

Searches should start by identifying appropriate thesaurus terms for the desired elements. The thesaurus of the database is searched for matching index terms for each key concept. We advise restricting the initial terms to the most important and most relevant terms. Later in the process, more general terms can be added in the optimization process, in which the effect on the number of hits, and thus the desirability of adding these terms, can be evaluated more easily.

Several factors can complicate the identification of thesaurus terms. Sometimes, one thesaurus term is found that exactly describes a specific element. In contrast, especially in more general elements, multiple thesaurus terms can be found to describe one element. If no relevant thesaurus terms have been found for an element, free-text terms can be used, and possible thesaurus terms found in the resulting references can be added later (step 11).

Sometimes, no distinct thesaurus term is available for a specific key concept that describes the concept in enough detail. In Emtree, one thesaurus term often combines two or more elements. The easiest solution for combining these terms for a sensitive search is to use such a thesaurus term in all elements where it is relevant. Examples are given in the supplementary appendix .

8. Identify synonyms in the thesaurus

Most thesauri offer a list of synonyms on their term details page (named Synonyms in Emtree and Entry Terms in MeSH). To create a sensitive search strategy for SRs, these terms need to be searched as free-text keywords in the title and abstract fields, in addition to searching their associated thesaurus terms.

The Emtree thesaurus contains more synonyms (300,000) than MeSH does (220,000) [ 17 ]. The difference in number of terms is even higher considering that many synonyms in MeSH are permuted terms (i.e., inversions of phrases using commas).

Thesaurus terms are ordered in a tree structure. When searching for a more general thesaurus term, the more specific (narrower) terms in the branches below that term will also be searched (this is frequently referred to as “exploding” a thesaurus term). However, to perform a sensitive search, all relevant variations of the narrower terms must be searched as free-text keywords in the title or abstract, in addition to relying on the exploded thesaurus term. Thus, all articles that describe a certain narrower topic in their titles and abstracts will already be retrieved before MeSH terms are added.

9. Add variations in search terms (e.g., truncation, spelling differences, abbreviations, opposites)

Truncation allows a searcher to search for words beginning with the same word stem. A search for therap* will, thus, retrieve therapy, therapies, therapeutic, and all other words starting with “therap.” Do not truncate a word stem that is too short. Also, limitations of interfaces should be taken into account, especially in PubMed, where the number of search term variations that can be found by truncation is limited to 600.

Databases contain references to articles using both standard British and American English spellings. Both need to be searched as free-text terms in the title and abstract. Alternatively, many interfaces offer a certain code to replace zero or one characters, allowing a search for “pediatric” or “paediatric” as “p?ediatric.” Table 1 provides a detailed description of the syntax for different interfaces.

Field codes in five most used interfaces for biomedical literature searching

Searching for abbreviations can identify extra, relevant references and retrieve more irrelevant ones. The search can be more focused by combining the abbreviation with an important word that is relevant to its meaning or by using the Boolean “NOT” to exclude frequently observed, clearly irrelevant results. We advise that searchers do not exclude all possible irrelevant meanings, as it is very time consuming to identify all the variations, it will result in unnecessarily complicated search strategies, and it may lead to erroneously narrowing the search and, thereby, reduce recall.

Searching partial abbreviations can be useful for retrieving relevant references. For example, it is very likely that an article would mention osteoarthritis (OA) early in the abstract, replacing all further occurrences of osteoarthritis with OA . Therefore, it may not contain the phrase “hip osteoarthritis” but only “hip oa.”

It is also important to search for the opposites of search terms to avoid bias. When searching for “disease recurrence,” articles about “disease free” may be relevant as well. When the desired outcome is survival , articles about mortality may be relevant.

10. Use database-appropriate syntax, with parentheses, Boolean operators, and field codes

Different interfaces require different syntaxes, the special set of rules and symbols unique to each database that define how a correctly constructed search operates. Common syntax components include the use of parentheses and Boolean operators such as “AND,” “OR,” and “NOT,” which are available in all major interfaces. An overview of different syntaxes for four major interfaces for bibliographic medical databases (PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest) is shown in Table 1 .

Creating the appropriate syntax for each database, in combination with the selected terms as described in steps 7–9, can be challenging. Following the method outlined below simplifies the process:

• Create single-line queries in a text document (not combining multiple record sets), which allows immediate checking of the relevance of retrieved references and efficient optimization.
• Type the syntax (Boolean operators, parentheses, and field codes) before adding terms, which reduces the chance that errors are made in the syntax, especially in the number of parentheses.
• Use predefined proximity structures including parentheses, such as (() ADJ3 ()) in Ovid, that can be reused in the query when necessary.
• Use thesaurus terms separately from free-text terms of each element. Start an element with all thesaurus terms (using “OR”) and follow with the free-text terms. This allows the unique optimization methods as described in step 11.
• When adding terms to an existing search strategy, pay close attention to the position of the cursor. Make sure to place it appropriately either in the thesaurus terms section, in the title/abstract section, or as an addition (broadening) to an existing proximity search.

The supplementary appendix explains the method of building a query in more detail, step by step for different interfaces: PubMed, Ovid, EBSCOhost, Embase.com, and ProQuest. This method results in a basic search strategy designed to retrieve some relevant references upon which a more thorough search strategy can be built with optimization such as described in step 11.

11. Optimize the search

The most important question when performing a systematic search is whether all (or most) potentially relevant articles have been retrieved by the search strategy. This is also the most difficult question to answer, since it is unknown which and how many articles are relevant. It is, therefore, wise first to broaden the initial search strategy, making the search more sensitive, and then check if new relevant articles are found by comparing the set results (i.e., search for Strategy #2 NOT Strategy #1 to see the unique results).

A search strategy should be tested for completeness. Therefore, it is necessary to identify extra, possibly relevant search terms and add them to the test search in an OR relationship with the already used search terms. A good place to start, and a well-known strategy, is scanning the top retrieved articles when sorted by relevance, looking for additional relevant synonyms that could be added to the search strategy.

We have developed a unique optimization method that has not been described before in the literature. This method often adds valuable extra terms to our search strategy and, therefore, extra, relevant references to our search results. Extra synonyms can be found in articles that have been assigned a certain set of thesaurus terms but that lack synonyms in the title and/or abstract that are already present in the current search strategy. Searching for thesaurus terms NOT free-text terms will help identify missed free-text terms in the title or abstract. Searching for free-text terms NOT thesaurus terms will help identify missed thesaurus terms. If this is done repeatedly for each element, leaving the rest of the query unchanged, this method will help add numerous relevant terms to the query. These steps are explained in detail for five different search platforms in the supplementary appendix .

12. Evaluate the initial results

The results should now contain relevant references. If the interface allows relevance ranking, use that in the evaluation. If you know some relevant references that should be included in the research, search for those references specifically; for example, combine a specific (first) author name with a page number and the publication year. Check whether those references are retrieved by the search. If the known relevant references are not retrieved by the search, adapt the search so that they are. If it is unclear which element should be adapted to retrieve a certain article, combine that article with each element separately.

Different outcomes are desired for different types of research questions. For instance, in the case of clinical question answering, the researcher will not be satisfied with many references that contain a lot of irrelevant references. A clinical search should be rather specific and is allowed to miss a relevant reference. In the case of an SR, the researchers do not want to miss any relevant reference and are willing to handle many irrelevant references to do so. The search for references to include in an SR should be very sensitive: no included reference should be missed. A search that is too specific or too sensitive for the intended goal can be adapted to become more sensitive or specific. Steps to increase sensitivity or specificity of a search strategy can be found in the supplementary appendix .

13. Check for errors

Errors might not be easily detected. Sometimes clues can be found in the number of results, either when the number of results is much higher or lower than expected or when many retrieved references are not relevant. However, the number expected is often unknown, and very sensitive search strategies will always retrieve many irrelevant articles. Each query should, therefore, be checked for errors.

One of the most frequently occurring errors is missing the Boolean operator “OR.” When no “OR” is added between two search terms, many interfaces automatically add an “AND,” which unintentionally reduces the number of results and likely misses relevant references. One good strategy to identify missing “OR”s is to go to the web page containing the full search strategy, as translated by the database, and using Ctrl-F search for “AND.” Check whether the occurrences of the “AND” operator are deliberate.

Ideally, search strategies should be checked by other information specialists [ 18 ]. The Peer Review of Electronic Search Strategies (PRESS) checklist offers good guidance for this process [ 4 ]. Apart from the syntax (especially Boolean operators and field codes) of the search strategy, it is wise to have the search terms checked by the clinician or researcher familiar with the topic. At Erasmus MC, researchers and clinicians are involved during the complete process of structuring and optimizing the search strategy. Each word is added after the combined decision of the searcher and the researcher, with the possibility of directly comparing results with and without the new term.

14. Translate to other databases

To retrieve as many relevant references as possible, one has to search multiple databases. Translation of complex and exhaustive queries between different databases can be very time consuming and cumbersome. The single-line search strategy approach detailed above allows quick translations using the find and replace method in Microsoft Word (<Ctrl-H>).

At Erasmus MC, macros based on the find-and-replace method in Microsoft Word have been developed for easy and fast translation between the most used databases for biomedical and health sciences questions. The schema that is followed for the translation between databases is shown in Figure 2 . Most databases simply follow the structure set by the Embase.com search strategy. The translation from Emtree terms to MeSH terms for MEDLINE in Ovid often identifies new terms that need to be added to the Embase.com search strategy before the translation to other databases.

Schematic representation of translation between databases used at Erasmus University Medical Center

Dotted lines represent databases that are used in less than 80% of the searches.

Using five different macros, a thoroughly optimized query in Embase.com can be relatively quickly translated into eight major databases. Basic search strategies will be created to use in many, mostly smaller, databases, because such niche databases often do not have extensive thesauri or advanced syntax options. Also, there is not much need to use extensive syntax because the number of hits and, therefore, the amount of noise in these databases is generally low. In MEDLINE (Ovid), PsycINFO (Ovid), and CINAHL (EBSCOhost), the thesaurus terms must be adapted manually, as each database has its own custom thesaurus. These macros and instructions for their installation, use, and adaptation are available at bit.ly/databasemacros.

15. Test and reiterate

Ideally, exhaustive search strategies should retrieve all references that are covered in a specific database. For SR search strategies, checking searches for their recall is advised. This can be done after included references have been determined by the authors of the systematic review. If additional papers have been identified through other non-database methods (i.e., checking references in included studies), results that were not identified by the database searches should be examined. If these results were available in the databases but not located by the search strategy, the search strategy should be adapted to try to retrieve these results, as they may contain terms that were omitted in the original search strategies. This may enable the identification of additional relevant results.

A methodology for creating exhaustive search strategies has been created that describes all steps of the search process, starting with a question and resulting in thorough search strategies in multiple databases. Many of the steps described are not new, but together, they form a strong method creating high-quality, robust searches in a relatively short time frame.

Our methodology is intended to create thoroughness for literature searches. The optimization method, as described in step 11, will identify missed synonyms or thesaurus terms, unlike any other method that largely depends on predetermined keywords and synonyms. Using this method results in a much quicker search process, compared to traditional methods, especially because of the easier translation between databases and interfaces (step 13). The method is not a guarantee for speed, since speed depends on many factors, including experience. However, by following the steps and using the tools as described above, searchers can gain confidence first and increase speed through practice.

What is new?

This method encourages searchers to start their search development process using empty syntax first and later adding the thesaurus terms and free-text synonyms. We feel this helps the searcher to focus on the search terms, instead of on the structure of the search query. The optimization method in which new terms are found in the already retrieved articles is used in some other institutes as well but has to our knowledge not been described in the literature. The macros to translate search strategies between interfaces are unique in this method.

What is different compared to common practice?

Traditionally, librarians and information specialists have focused on creating complex, multi-line (also called line-by-line) search strategies, consisting of multiple record sets, and this method is frequently advised in the literature and handbooks [ 2 , 19 – 21 ]. Our method, instead, uses single-line searches, which is critical to its success. Single-line search strategies can be easily adapted by adding or dropping a term without having to recode numbers of record sets, which would be necessary in multi-line searches. They can easily be saved in a text document and repeated by copying and pasting for search updates. Single-line search strategies also allow easy translation to other syntaxes using find-and-replace technology to update field codes and other syntax elements or using macros (step 13).

When constructing a search strategy, the searcher might experience that certain parentheses in the syntax are unnecessary, such as parentheses around all search terms in the title/abstract portion, if there is only one such term, there are double parentheses in the proximity statement, or one of the word groups exists for only one word. One might be tempted to omit those parentheses for ease of reading and management. However, during the optimization process, the searcher is likely to find extra synonyms that might consist of one word. To add those terms to the first query (with reduced parentheses) requires adding extra parentheses (meticulously placing and counting them), whereas, in the latter search, it only requires proper placement of those terms.

Many search methods highly depend on the PICO framework. Research states that often PICO or PICOS is not suitable for every question [ 22 , 23 ]. There are other acronyms than PICO—such as sample, phenomenon of interest, design, evaluation, research type (SPIDER) [ 24 ]—but each is just a variant. In our method, the most important and specific elements of a question are being analyzed for building the best search strategy.

Though it is generally recommended that searchers search both MEDLINE and Embase, most use MEDLINE as the starting point. It is considered the gold standard for biomedical searching, partially due to historical reasons, since it was the first of its kind, and more so now that it is freely available via the PubMed interface. Our method can be used with any database as a starting point, but we use Embase instead of MEDLINE or another database for a number of reasons. First, Embase provides both unique content and the complete content of MEDLINE. Therefore, searching Embase will be, by definition, more complete than searching MEDLINE only. Second, the number of terms in Emtree (the Embase thesaurus) is three times as high as that of MeSH (the MEDLINE thesaurus). It is easier to find MeSH terms after all relevant Emtree terms have been identified than to start with MeSH and translate to Emtree.

At Erasmus MC, the researchers sit next to the information specialist during most of the search strategy design process. This way, the researchers can deliver immediate feedback on the relevance of proposed search terms and retrieved references. The search team then combines knowledge about databases with knowledge about the research topic, which is an important condition to create the highest quality searches.

Limitations of the method

One disadvantage of single-line searches compared to multi-line search strategies is that errors are harder to recognize. However, with the methods for optimization as described (step 11), errors are recognized easily because missed synonyms and spelling errors will be identified during the process. Also problematic is that more parentheses are needed, making it more difficult for the searcher and others to assess the logic of the search strategy. However, as parentheses and field codes are typed before the search terms are added (step 10), errors in parentheses can be prevented.

Our methodology works best if used in an interface that allows proximity searching. It is recommended that searchers with access to an interface with proximity searching capabilities select one of those as the initial database to develop and optimize the search strategy. Because the PubMed interface does not allow proximity searches, phrases or Boolean “AND” combinations are required. Phrase searching complicates the process and is more specific, with the higher risk of missing relevant articles, and using Boolean “AND” combinations increases sensitivity but at an often high loss of specificity. Due to some searchers’ lack of access to expensive databases or interfaces, the freely available PubMed interface may be necessary to use, though it should never be the sole database used for an SR [ 2 , 16 , 25 ]. A limitation of our method is that it works best with subscription-based and licensed resources.

Another limitation is the customization of the macros to a specific institution’s resources. The macros for the translation between different database interfaces only work between the interfaces as described. To mitigate this, we recommend using the find-and-replace functionality of text editors like Microsoft Word to ease the translation of syntaxes between other databases. Depending on one’s institutional resources, custom macros can be developed using similar methods.

Results of the method

Whether this method results in exhaustive searches where no important article is missed is difficult to determine, because the number of relevant articles is unknown for any topic. A comparison of several parameters of 73 published reviews that were based on a search developed with this method to 258 reviews that acknowledged information specialists from other Dutch academic hospitals shows that the performance of the searches following our method is comparable to those performed in other institutes but that the time needed to develop the search strategies was much shorter than the time reported for the other reviews [ 9 ].

CONCLUSIONS

With the described method, searchers can gain confidence in their search strategies by finding many relevant words and creating exhaustive search strategies quickly. The approach can be used when performing SR searches or for other purposes such as answering clinical questions, with different expectations of the search’s precision and recall. This method, with practice, provides a stepwise approach that facilitates the search strategy development process from question clarification to final iteration and beyond.

SUPPLEMENTAL FILE

Acknowledgments.

We highly appreciate the work that was done by our former colleague Louis Volkers, who in his twenty years as an information specialist in Erasmus MC laid the basis for our method. We thank Professor Oscar Franco for reviewing earlier drafts of this article.

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The Library Research Process, Step-by-Step

• Finding Articles
• Finding & Exploring a Topic
• Finding Books
• Evaluating Sources
• Reading Scholarly Articles
• Understanding & Using a Citation Style

Peer Reviewed and Scholarly Articles

What are they? Peer-reviewed articles, also known as scholarly or refereed articles are papers that describe a research study. 

Why are peer-reviewed articles useful? They report on original research that have been reviewed by other experts before they are accepted for publication, so you can reasonably be assured that they contain valid information. 

How do you find them?  Many of the library's databases contain scholarly articles! You'll find more about searching databases below.

Watch: Peer Review in 3 Minutes

Why watch this video?

We are often told that scholarly and peer-reviewed sources are the most credible, but, it's sometimes hard to understand why they are credible and why we should trust these sources more than others. This video takes an in depth approach at explaining the peer review process. 

Hot Tip: Check out the Reading Scholarly Articles page for guidance on how to read and understand a scholarly article.

Using Library Databases

What Are Library Databases? 

Databases are similar to search engines but primarily search scholarly journals, magazines, newspapers and other sources. Some databases are subject specific while others are multi-disciplinary (searching across multiple fields and content types). 

You can view our most popularly used databases on the Library's Home Page , or view a list of all of our databases organized by subject or alphabetically at  U-M Library Databases .

Popular Multidisciplinary Databases

Many students use ProQuest , JSTOR , and Google Scholar for their initial search needs. These are multi-disciplinary and not subject-specific, and they can supply a very large number of  search results.

Subject-Specific Databases

Some popular subject-specific databases include PsycINFO for psychology and psychiatry related topics and  PubMed for health sciences topics. 

Why Should You Use Library Databases?

Unlike a Google search, the Library Databases will grant you access to high quality credible sources. 

The sources you'll find in library databases include:

• Scholarly journal articles
• Newspaper articles
• Theses & dissertations
• Empirical evidence

Database Filters & Limits Most databases have Filters/Limits. You can use these to narrow down your search to the specific dates, article type, or population that you are researching.

Here is an example of limits in a database, all databases look slightly different but most have these options:

Keywords and Starting a Search

What are Keywords?

• Natural language words that describe your topic 
• Allows for a more flexible search - looks for anywhere the words appear in the record
• Can lead to a broader search, but may yield irrelevant results

Keyword searching  is how we normally start a search. Pull out important words or phrases from your topic to find your keywords.

Tips for Searching with Keywords:

• Example: "climate change"
• Example:  "climate change" AND policy
• Example: comput* will return all words starting with four letters; computing, computer, compute, etc.  
• Example: wom?n will find both woman and women.

What are Subject Headings?

• Pre-defined "controlled vocabulary" that describe what an item is  about 
• Makes for a less flexible search - only the subject fields will be searched
• Targeted search; results are usually more relevant to the topic, but may miss some variations

Subject Terms and/or Headings are pre-defined terms that are used to describe the content of an item. These terms are a controlled vocabulary and function similarly to hashtags on social media. Look carefully at the results from your search. If you find an article that is relevant to the topic you want to write about, take a look at the subject headings. 

Hot Tip: Make a copy of this Google Doc to help you find and develop your topic's keywords.

More Database Recommendations

Need articles for your library research project, but not sure where to start? We recommend these top ten article databases for kicking off your research. If you can't find what you need searching in one of these top ten databases, browse the list of all library databases by subject (academic discipline) or title .

• U-M Library Articles Search This link opens in a new window Use Articles Search to locate scholarly and popular articles, as well as reference works and materials from open access archives.
• ABI/INFORM Global This link opens in a new window Indexes 3,000+ business-related periodicals (with full text for 2,000+), including Wall Street Journal.
• Academic OneFile This link opens in a new window Provides indexing for over 8,000 scholarly journals, industry periodicals, general interest magazines and newspapers.
• Access World News [NewsBank] This link opens in a new window Full text of 600+ U.S. newspapers and 260+ English-language newspapers from other countries worldwide.
• CQ Researcher This link opens in a new window Noted for its in-depth, unbiased coverage of health, social trends, criminal justice, international affairs, education, the environment, technology, and the economy.
• Gale Health and Wellness This link opens in a new window
• Humanities Abstracts (with Full Text) This link opens in a new window Covers 700 periodicals in art, film, journalism, linguistics, music, performing arts, philosophy, religion, history, literature, etc.
• JSTOR This link opens in a new window Full-text access to the archives of 2,600+ journals and 35,000+ books in the arts, humanities, social sciences and sciences.
• ProQuest Research Library This link opens in a new window Indexes over 5,000 journals and magazines, academic and popular, with full text included for over 3,600.
• PsycInfo (APA) This link opens in a new window Premier resource for surveying the literature of psychology and adjunct fields. Covers 1887-present. Produced by the APA.

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Document Search

Search for records from our product indexes. Successful searches are added to the Search History table. Remember to follow all applicable search rules when creating search queries.

Adding a new field sets the second field to the AND operator. You can change the AND operator to OR or NOT.

Your settings are applied to all product databases in your subscription package; administrators may set one to three search fields to display as the default search fields for their institution.

• Cited Reference Search
• Interface Language
• Search Fields
• Search Operator Precedence

To perform a document search, select the field you want to search and type a term in the search field. To add more than one search criterion, click Add Row . Select a Boolean operator and click Search .

The Web of Science Core Collection and All Database Search includes AI enabled Topic and Keyword suggestions. This feature is available to all users who perform basic or advanced search in All Data Bases and WoS Core Collection on Web of Science.

Users can modify search by selecting from algorithm generated author keywords and topic suggestions or by inputing free text in the search box. This feature enhances search experience by providing search term suggestions that can help narrow down search and improve search results relevance.

Quick add keywords

On the search results page, users will be presented with a list of keywords. These additional keywords are provided as relevant selections to the search, thus helping users to complete or modify query quickly and effectively.

Add Keyword Topic Suggestions

When users click ‘Add Keywords’, they can enter free text or use automatically generated topic suggestions. As users start typing the keyword, topic suggestions are provided in real time which can be selected to help compete their search query. This feature can help users save time and refine a search by suggesting relevant topics related to a research field and help users explore various aspects of the topic of interest.

Add ‘Free Text’ keywords

When users click on ‘Add Keywords’, the free text bar allows users to directly enter their own search terms, enabling users to search for specific terms that are important to their research.

Simplified Boolean Logic (Should Include, Must Include & Do Not Include)

When a user selects to add one keyword, this is ‘Should Include’ (OR) by default. However, when users select at least 2 keywords (or multiple keywords), they can select to manage search logic from 3-Dot menu to help complete their query with Boolean logic easily and effectively

AI Enabled Search only works when searching All Databases or Web of Science Core Collection.

All database products within the Web of Science platform includes a spellchecker that checks your search queries against common spellings and their variants to determine if alternative spellings exist that would improve your search results.

If the system determines that an alternative spelling exists, a Did You Mean text box appears offering you an alternative search query. The tool checks full terms and not truncated terms or terms within quotation marks.

For example:

• Did You Mean: Topic=(suggested search terms) [NNN results]
• Did You Mean: (Topic=(suggested search terms) AND Author=(author name)) [NNN results]

When you select the Did You Mean suggestion, a new search opens and takes you to the results page. The original search and the Did You Mean search both display in the Search History .

If no results are found, and there are no Did You Mean suggestions, you will get a list search tips to help return better results.

The product uses an implicit AND operator when you enter two or more adjacent terms in most fields. For example, entering rainbow trout fish farm in the search field is equivalent to entering rainbow AND trout AND fish AND farm ; both queries return the same number of results.

See more about search operators.

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• CORRESPONDENCE
• 21 March 2023

A free online guide to researchers’ best search options

• Michael Gusenbauer   ORCID: http://orcid.org/0000-0001-7768-2351 0

Johannes Kepler University Linz, Linz, Austria.

You can also search for this author in PubMed   Google Scholar

All too often, scientists default to their go-to databases for literature searches without considering whether there might be better alternatives. Search Smart ( Searchsmart.org ) is a free website I created to guide researchers through the overwhelming number of academic search options. It allows them to compare these and informs them of the most productive places to search.

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Nature 615 , 586 (2023)

doi: https://doi.org/10.1038/d41586-023-00845-0

Competing Interests

The author declares no competing interests.

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