uCite: The union of nine large-scale public PubMed citation datasets with reliability filtering

There has been a recent push to make public, aggregate, and increase coverage of bibliographic citation data. Here we describe uCite, a citation dataset containing 564 million PubMed citation pairs aggregated from the following nine sources: PubMed Central, iCite, OpenCitations, Dimensions, Microsoft Academic Graph, Aminer, Semantic Scholar, Lens, and OpCitance. Of these, 51 million (9%) were labeled unreliable, as determined by patterns of source discrepancies explained by ambiguous metadata, crosswalk, and typographical errors, citing future publications, and multi-paper documents. Each source contributes to improved coverage and reliability, but varies dramatically in precision and recall, estimates of which are contrasted with the Web of Science and Scopus herein.

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Publication Details

Journal
Data in Brief
Published
2025-04-04
DOI
https://doi.org/10.1016/j.dib.2025.111535
Citations
1
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.81

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article

uCite: The union of nine large-scale public PubMed citation datasets with reliability filtering

Liri Fang, Griffin M. Weber, Malik Oyewale Salami, Vetle I. Torvik
1 citations
Data in Brief
Biomedical Text Mining and Ontologies
0.81
article

uCite: The union of nine large-scale public PubMed citation datasets with reliability filtering

Liri Fang, Griffin M. Weber, Malik Oyewale Salami, Vetle I. Torvik
article en
1 citations

Abstract

There has been a recent push to make public, aggregate, and increase coverage of bibliographic citation data. Here we describe uCite, a citation dataset containing 564 million PubMed citation pairs aggregated from the following nine sources: PubMed Central, iCite, OpenCitations, Dimensions, Microsoft Academic Graph, Aminer, Semantic Scholar, Lens, and OpCitance. Of these, 51 million (9%) were labeled unreliable, as determined by patterns of source discrepancies explained by ambiguous metadata, crosswalk, and typographical errors, citing future publications, and multi-paper documents. Each source contributes to improved coverage and reliability, but varies dramatically in precision and recall, estimates of which are contrasted with the Web of Science and Scopus herein.

Data in BriefVol. 60
Harvard University (US), University of Illinois Urbana-Champaign (US)
National Institutes of Health, National Institute on Aging
Openalex Percentile: Top 29%
Biomedical Text Mining and Ontologies
0.81
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uCite: The union of nine large-scale public PubMed citation datasets with reliability filtering — Liri Fang, Griffin M. Weber, et al. · Data in Brief (2025) | TGRS Research Map | TGRS