Literature DB >> 35571007

Search where you will find most: Comparing the disciplinary coverage of 56 bibliographic databases.

Michael Gusenbauer1.   

Abstract

This paper introduces a novel scientometrics method and applies it to estimate the subject coverages of many of the popular English-focused bibliographic databases in academia. The method uses query results as a common denominator to compare a wide variety of search engines, repositories, digital libraries, and other bibliographic databases. The method extends existing sampling-based approaches that analyze smaller sets of database coverages. The findings show the relative and absolute subject coverages of 56 databases-information that has often not been available before. Knowing the databases' absolute subject coverage allows the selection of the most comprehensive databases for searches requiring high recall/sensitivity, particularly relevant in lookup or exploratory searches. Knowing the databases' relative subject coverage allows the selection of specialized databases for searches requiring high precision/specificity, particularly relevant in systematic searches. The findings illustrate not only differences in the disciplinary coverage of Google Scholar, Scopus, or Web of Science, but also of less frequently analyzed databases. For example, researchers might be surprised how Meta (discontinued), Embase, or Europe PMC are found to cover more records than PubMed in Medicine and other health subjects. These findings should encourage researchers to re-evaluate their go-to databases, also against newly introduced options. Searching with more comprehensive databases can improve finding, particularly when selecting the most fitting databases needs particular thought, such as in systematic reviews and meta-analyses. This comparison can also help librarians and other information experts re-evaluate expensive database procurement strategies. Researchers without institutional access learn which open databases are likely most comprehensive in their disciplines.
© The Author(s) 2022.

Entities:  

Keywords:  Basket of keywords; Bibliographic database; Comparison; Query hit counts; Search system; Subject coverage

Year:  2022        PMID: 35571007      PMCID: PMC9075928          DOI: 10.1007/s11192-022-04289-7

Source DB:  PubMed          Journal:  Scientometrics        ISSN: 0138-9130            Impact factor:   3.801


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