Abstract
AbstractThis 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.
Funder
University of Innsbruck and Medical University of Innsbruck
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Computer Science Applications,General Social Sciences
Reference118 articles.
1. Aksnes, D. W., & Sivertsen, G. (2019). A criteria-based assessment of the coverage of Scopus and Web of Science. Journal of Data and Information Science, 4, 1–21. https://doi.org/10.2478/jdis-2019-0001
2. Allen Institute for Artificial Intelligence. (2022). Why Semantic Scholar?: Multidisciplinary scope. Retrieved January 17, 2022, from https://www.semanticscholar.org/about/librarians.
3. American Chemical Society. (2022). CONTENT OF SCIFINDERn. Retrieved January 17, 2022, from https://www.cas.org/solutions/cas-scifinder-discovery-platform/cas-scifinder/content.
4. arXiv. (2021). arXiv.org. Retrieved July 18, 2021, from https://arxiv.org/.
5. Association for Computing Machinery. (2022). The ACM guide to computing literature. Retrieved January 17, 2022, from https://libraries.acm.org/digital-library/acm-guide-to-computing-literature.
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