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

IF 1 Q3 MULTIDISCIPLINARY SCIENCES

Data in Brief Pub Date : 2025-04-02 DOI:10.1016/j.dib.2025.111535

Liri Fang , Malik Oyewale Salami , Griffin M. Weber , Vetle I. Torvik

引用次数: 0

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.

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uCite：对9个大型公共PubMed引文数据集进行可靠性过滤的联合

最近一直在推动书目引文数据的公开、汇总和增加覆盖范围。uCite是一个包含5.64亿PubMed引文对的引文数据集，汇集了以下九个来源：PubMed Central、iCite、OpenCitations、Dimensions、Microsoft Academic Graph、Aminer、Semantic Scholar、Lens和OpCitance。其中，5100万篇（9%）被标记为不可靠，这是由模棱两可的元数据、人行横道和印刷错误解释的来源差异模式所决定的，引用了未来的出版物和多篇论文。每个来源都有助于提高覆盖范围和可靠性，但在准确性和召回率方面差异很大，这与本文的Web of Science和Scopus进行了对比。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.