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Showing posts with the label scopus

Tip #70: Building a (Database) Creature with the Best Features: An Unscientific Report

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It’s alive! Or we wish it were. On June 16th, 2026, the Medical Library Association User Experience Caucus hosted the networking event, “Building a (Database) Creature with the Best Features”, at the Library Evidence Synthesis Services Symposium ( LESSS) .  During this event, more than sixty evidence synthesis librarians across disciplines assembled in an unscientific effort to cobble together their dream database platform based on the ones they search every day.

Tip #68 Searches Gone Wild! Popular Database Platforms and Their Wildcards

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Written by Hilary Kraus and Zahra Premji  Take a walk on the wild side! Join us for a deep dive into the world of wildcards. This post provides an introduction to how wildcards work, some potential  pitfalls  of using them, and detailed information about how to use them in many popular database platforms. Wildcards 101 Complex searching often involves looking for various forms and spellings of a word. One common approach to this is the use of wildcards. There are two varieties of wildcard. A mandatory wildcard replaces one letter; an optional wildcard replaces either zero or one letter. How these wildcards function and what syntax is used to operationalize them depends on where you're searching. In this post, we look at the ways commonly used databases (or database platforms) use wildcards. Going forward, we will use root to refer to a collection of Latin alphabet letters to which a wildcard may be applied. Since wildcards are typically executed using a punctuation mar...

Tip #67 Subject Areas in Scopus May Amplify the Noise in Your Search

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The crux:  In Scopus, pay attention to Subject area  on the search results page to see if your search retrieves an unexpected number of records from non-relevant areas.  This is especially important when you include acronyms in a search.  The multidisciplinary nature of Scopus presents opportunities and challenges. This post focuses on one of the challenges - records that contain your terms but are wildly irrelevant. This is referred to as noise in a search. Scopus's subject area feature can alert you to noise in your search and provide clues to which terms are causing it.  On the left side of the Scopus results page are options for refining the search. This is where you find the feature called Subject area . But it may not work how you think.   Journal titles are classified in Scopus using its ASJC (All Science Journal Classification) scheme, a list of 361 numerical classification codes that correspond to subject areas. Classification is perform...

Tip #59: Getting Up Close and Personal with Database Proximity Syntax

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Written by Hilary Kraus and Zahra Premji Why is proximity searching valuable? In systematic searching, there is an inherent tension between sensitivity and precision. According to the Cochrane Handbook, "Searches for systematic reviews aim to be as extensive as possible in order to ensure that as many of the relevant studies as possible are included in the review. It is, however, necessary to strike a balance between striving for comprehensiveness and maintaining relevance when developing a search strategy." ( Chapter 4, Section 4.4.3: Sensitivity versus precision ) One strategy for achieving this balance is the use of proximity operators. As explained in the Cochrane Handbook's Technical Supplement to Chapter 4, "Use of proximity operators helps to ensure that searches are more sensitive than would be the case with direct adjacency or phrase searching, and can also facilitate ease of searching where there are multiple possible variations of a phrase which would othe...

Tip #52: Searching for PMIDs in Other Databases

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What is a PMID? A PMID, also known as the PubMed Identifier, is a unique number assigned by the National Library of Medicine to all records included in PubMed. It appears under the citation information on each record. PMIDs do not change over time or during processing and are never reused. Searching for articles using their PMIDs can be a very efficient way to find known items or test searches (e.g., Testing for Article Inclusion in Ovid and Testing for Articles in PubMed ). To search for a set of known records in PubMed, enter a string of PMIDs in the search box without the Boolean "OR" and without the [pmid] field tag. If you use [pmid], you will need to use the Boolean "OR" to combine them. These three searches return the same results: 26104772 11038025 35106283 26104772 OR 11038025 OR 35106283 26104772[pmid] OR 11038025[pmid] OR 35106283[pmid] Below we will highlight some search tips for finding PMIDs across various databases Too long didn't read (tldr) c...

Tip #50: "Indexed Keywords" in Scopus: what they are, where they come from, and how (and whether) to exclude them

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Scopus is a very large multidisciplinary database with a wide range of sources. According to Elsevier, almost 99% of journals indexed in Embase and MEDLINE are included in Scopus. Unlike Embase, which uses the Emtree thesaurus for indexing (the full Emtree thesaurus is only available in Embase), or MEDLINE, which uses MeSH (accessible publicly via the MeSH Browser or MeSH Database ), Scopus does not have its own controlled vocabulary or thesaurus searching capabilities. So what are the "indexed keywords" in Scopus? And are they beneficial or harmful to your searches? The origins of "indexed keywords" Journal article records in Scopus are supplied directly from publishers, and thus arrive with no indexing. Scopus then enriches these references whenever possible, using thesauri Elsevier either owns or licenses. The “indexed keywords” that display in references are added when Scopus finds an exact item match with a reference from Embase or MEDLINE. For example, an ar...