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Cited by 175

The DOI matches its Crossref record.

Crossref: The sustainable source of community-owned scholarly metadata

Hendricks, Ginny, Tkaczyk, Dominika, Lin, Jennifer, Feeney, Patricia·2020·Quantitative Science Studies
DOI 10.1162/qss_a_00022
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Abstract

This paper describes the scholarly metadata collected and made available by Crossref, as well as its importance in the scholarly research ecosystem. Containing over 106 million records and expanding at an average rate of 11% a year, Crossref’s metadata has become one of the major sources of scholarly data for publishers, authors, librarians, funders, and researchers. The metadata set consists of 13 content types, including not only traditional types, such as journals and conference papers, but also data sets, reports, preprints, peer reviews, and grants. The metadata is not limited to basic publication metadata, but can also include abstracts and links to full text, funding and license information, citation links, and the information about corrections, updates, retractions, etc. This scale and breadth make Crossref a valuable source for research in scientometrics, including measuring the growth and impact of science and understanding new trends in scholarly communications. The metadata is available through a number of APIs, including REST API and OAI-PMH. In this paper, we describe the kind of metadata that Crossref provides and how it is collected and curated. We also look at Crossref’s role in the research ecosystem and trends in metadata curation over the years, including the evolution of its citation data provision. We summarize the research used in Crossref’s metadata and describe plans that will improve metadata quality and retrieval in the future.

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Crossref · 10.1162/qss_a_00022

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Figures

Figure 1 The current distribution of crossref metadata records by major content type. For the purpose of this visualization, we merged some fine-grained types into major content types. For example, ' book ' type in the figure contains all related fine-grained types, such as book chapters, books, and book series.
Figure 1 The current distribution of crossref metadata records by major content type. For the purpose of this visualization, we merged some fine-grained types into major content types. For example, ' book ' type in the figure contains all related fine-grained types, such as book chapters, books, and book series.CC-BY · From the PDF
Figure 2 The distribution of metadata records in Crossref published over time by content type. (Data are smoothed using the locally estimated scatterplot smoothing method 6 .)
Figure 2 The distribution of metadata records in Crossref published over time by content type. (Data are smoothed using the locally estimated scatterplot smoothing method 6 .)CC-BY · From the PDF
Figure 3 Percentage of records containing given metadata type vs. their publication time. (The blue lines show the trend and were generated by smoothing data locally.)
Figure 3 Percentage of records containing given metadata type vs. their publication time. (The blue lines show the trend and were generated by smoothing data locally.)CC-BY · From the PDF
Figure 4 Crossref metadata workflow.
Figure 4 Crossref metadata workflow.CC-BY · From the PDF
Figure 5 Percentage of Crossref metadata updated at least once after registration. (The blue line shows the trend and was generated by smoothing data locally.)
Figure 5 Percentage of Crossref metadata updated at least once after registration. (The blue line shows the trend and was generated by smoothing data locally.)CC-BY · From the PDF

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Cites

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Research works printed but not linked: 15

  1. Akbaritabar A., 2019, SocArXiv
  2. Cho H., 2018, Social Network Analysis and Mining, 8, 211
  3. Dion M. L., 2018, Political Analysis, 26, 312, 10.1017/pan.2018.12 · DOI
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  6. Hicks D. J., 2019, Scientific Communication and Education
  7. Khoo S. Y-S., 2019, LIBER Quarterly, 29, 1, 10.18352/lq.10280 · DOI
  8. Klein M., 2016, Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries—JCDL ’16, 153, 10.1145/2910896.2910909 · DOI
  9. Martín-Martín A., 2018, Journal of Informetrics, 12, 819, 10.1016/j.joi.2018.06.012 · DOI
  10. Matthias L., 2019, Publications, 7, 23, 10.3390/publications7020023 · DOI
  11. Ortega J. L., 2018, FEMS Microbiology Letters, 365, 10.1093/femsle/fny049 · DOI
  12. Ortega J. L., 2018, Scientometrics, 116, 2123, 10.1007/s11192-018-2838-z · DOI
  13. Peroni S., 2019, CoRR
  14. Schenkel R., 2018, BIR 2018 Workshop on Bibliometric-enhanced Information Retrieval
  15. Zahedi Z., 2018, PLoS One, 13, e0197326, 10.1371/journal.pone.0197326 · DOI

Cited by

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Metadata

Authors
Hendricks, G., Tkaczyk, D., Lin, J., & Feeney, P.
Affiliations
Crossref
ORCID
Venue
Quantitative Science Studies
Publisher
MIT Press
Published
2020-02
Volume
1
Issue
1
Pages
414-427
ISSN
2641-3337
DOI
10.1162/qss_a_00022
Cited by
175
References
0
Language
en

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CoChat. (2026). Citation check: Crossref: The sustainable source of community-owned scholarly metadata. https://app.cochat.ai/papers/10.1162/qss_a_00022
The paper
Hendricks, G., Tkaczyk, D., Lin, J., & Feeney, P. (2020). Crossref: The sustainable source of community-owned scholarly metadata. Quantitative Science Studies. https://doi.org/10.1162/qss_a_00022

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.