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DataCite as a novel bibliometric source: Coverage, strengths and limitations

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  • Robinson-Garcia, Nicolas
  • Mongeon, Philippe
  • Jeng, Wei
  • Costas, Rodrigo

Abstract

This paper explores the characteristics of DataCite to determine its possibilities and potential as a new bibliometric data source to analyze the scholarly production of open data. Open science and the increasing data sharing requirements from governments, funding bodies, institutions and scientific journals has led to a pressing demand for the development of data metrics. As a very first step towards reliable data metrics, we need to better comprehend the limitations and caveats of the information provided by sources of open data. In this paper, we critically examine records downloaded from the DataCite’s OAI API and elaborate a series of recommendations regarding the use of this source for bibliometric analyses of open data. We highlight issues related to metadata incompleteness, lack of standardization, and ambiguous definitions of several fields. Despite these limitations, we emphasize DataCite’s value and potential to become one of the main sources for data metrics development.

Suggested Citation

  • Robinson-Garcia, Nicolas & Mongeon, Philippe & Jeng, Wei & Costas, Rodrigo, 2017. "DataCite as a novel bibliometric source: Coverage, strengths and limitations," Journal of Informetrics, Elsevier, vol. 11(3), pages 841-854.
    • Handle: RePEc:eee:infome:v:11:y:2017:i:3:p:841-854
    DOI: 10.1016/j.joi.2017.07.003
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    References listed on IDEAS

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    1. Christine L. Borgman, 2012. "The conundrum of sharing research data," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(6), pages 1059-1078, June.
    2. Christine L. Borgman, 2012. "The conundrum of sharing research data," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(6), pages 1059-1078, June.
    3. Isabella Peters & Peter Kraker & Elisabeth Lex & Christian Gumpenberger & Juan Gorraiz, 2016. "Research data explored: an extended analysis of citations and altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 723-744, May.
    4. Heather A Piwowar & Roger S Day & Douglas B Fridsma, 2007. "Sharing Detailed Research Data Is Associated with Increased Citation Rate," PLOS ONE, Public Library of Science, vol. 2(3), pages 1-5, March.
    5. Heather A Piwowar & Michael J Becich & Howard Bilofsky & Rebecca S Crowley & on behalf of the caBIG Data Sharing and Intellectual Capital Workspace, 2008. "Towards a Data Sharing Culture: Recommendations for Leadership from Academic Health Centers," PLOS Medicine, Public Library of Science, vol. 5(9), pages 1-5, September.
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    Cited by:

    1. Zeng, Tong & Wu, Longfeng & Bratt, Sarah & Acuna, Daniel E., 2020. "Assigning credit to scientific datasets using article citation networks," Journal of Informetrics, Elsevier, vol. 14(2).
    2. Wei‐Min Fan & Wei Jeng & Muh‐Chyun Tang, 2023. "Using data citation to define a knowledge domain: A case study of the Add‐Health dataset," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(1), pages 81-98, January.
    3. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
    4. B. Preedip Balaji & M. Dhanamjaya, 2019. "Preprints in Scholarly Communication: Re-Imagining Metrics and Infrastructures," Publications, MDPI, vol. 7(1), pages 1-23, January.
    5. Irina Gerasimov & Binita KC & Armin Mehrabian & James Acker & Michael P. McGuire, 2024. "Comparison of datasets citation coverage in Google Scholar, Web of Science, Scopus, Crossref, and DataCite," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 3681-3704, July.
    6. Sixto-Costoya Andrea & Robinson-Garcia Nicolas & Leeuwen Thed & Costas Rodrigo, 2021. "Exploring the relevance of ORCID as a source of study of data sharing activities at the individual-level: a methodological discussion," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7149-7165, August.
    7. Anne E Thessen & Paul Bogdan & David J Patterson & Theresa M Casey & César Hinojo-Hinojo & Orlando de Lange & Melissa A Haendel, 2021. "From Reductionism to Reintegration: Solving society’s most pressing problems requires building bridges between data types across the life sciences," PLOS Biology, Public Library of Science, vol. 19(3), pages 1-12, March.

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