Completeness degree of publication metadata in eight free-access scholarly databases

Bibliographic Data

ID21255750
AuthorsLorena Delgado-Quirós (0000-0001-8738-7276, Instituto de Estudios Sociales Avanzados), José-Luis Ortega (0000-0001-9857-1511, Instituto de Estudios Sociales Avanzados)
Year2024
Volume5
Issue1
Pages31-49
Publication date2024-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueQuantitative Science Studies (JOURNAL)
Journal identifiersISSN: 2641-3337 • E-ISSN: 2641-3337
PublisherMIT Press (PUBLISHER • US)
DOI10.1162/qss_a_00286
OpenAlexW4391658149
LanguageEN
Citations received14
References cited24

The main objective of this study is to compare the amount of metadata and the completeness degree of research publications in new academic databases. Using a quantitative approach, we selected a random Crossref sample of more than 115,000 records, which was then searched in seven databases (Dimensions, Google Scholar, Microsoft Academic, OpenAlex, Scilit, Semantic Scholar, and The Lens). Seven characteristics were analyzed (abstract, access, bibliographic info, document type, publication date, language, and identifiers), to observe fields that describe this information, the completeness rate of these fields, and the agreement among databases. The results show that academic search engines (Google Scholar, Microsoft Academic, and Semantic Scholar) gather less information and have a low degree of completeness. Conversely, third-party databases (Dimensions, OpenAlex, Scilit, and The Lens) have more metadata quality and a higher completeness rate. We conclude that academic search engines lack the ability to retrieve reliable descriptive data by crawling the web, and the main problem of third-party databases is the loss of information derived from integrating different sources

Database · Information retrieval · Metadata · World Wide Web · Academic Publishing and Open Access · Computer Science · Mathematics · Research Data Management Practices

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