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An examination of research data sharing and re-use: implications for data citation practice

Author

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  • Hyoungjoo Park

    (University of Wisconsin – Milwaukee)

  • Dietmar Wolfram

    (University of Wisconsin – Milwaukee)

Abstract

This study examines characteristics of data sharing and data re-use in Genetics and Heredity, where data citation is most common. This study applies an exploratory method because data citation is a relatively new area. The Data Citation Index (DCI) on the Web of Science was selected because DCI provides a single access point to over 500 data repositories worldwide and to over two million data studies and datasets across multiple disciplines and monitors quality research data through a peer review process. We explore data citations for Genetics and Heredity, as a case study by examining formal citations recorded in the DCI and informally by sampling a selection of papers for implicit data citations within publications. Citer-based analysis is conducted in order to remedy self-citation in the data citation phenomena. We explore 148 sampled citing articles in order to identify factors that influence data sharing and data re-use, including references, main text, supplementary data/information, acknowledgments, funding information, author information, and web/author resources. This study is unique in that it relies on a citer-based analysis approach and by analyzing peer-reviewed and published data, data repositories, and citing articles of highly productive authors where data sharing is most prevalent. This research is intended to provide a methodological and practical contribution to the study of data citation.

Suggested Citation

  • Hyoungjoo Park & Dietmar Wolfram, 2017. "An examination of research data sharing and re-use: implications for data citation practice," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 443-461, April.
    • Handle: RePEc:spr:scient:v:111:y:2017:i:1:d:10.1007_s11192-017-2240-2
    DOI: 10.1007/s11192-017-2240-2
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    References listed on IDEAS

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    1. Benjamin F. Jones, 2009. "The Burden of Knowledge and the "Death of the Renaissance Man": Is Innovation Getting Harder?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(1), pages 283-317.
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    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. Isola Ajiferuke & Kun Lu & Dietmar Wolfram, 2010. "A comparison of citer and citation-based measure outcomes for multiple disciplines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(10), pages 2086-2096, October.
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    6. Isola Ajiferuke & Kun Lu & Dietmar Wolfram, 2010. "A comparison of citer and citation‐based measure outcomes for multiple disciplines," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(10), pages 2086-2096, October.
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    8. Kun Lu & Isola Ajiferuke & Dietmar Wolfram, 2014. "Extending citer analysis to journal impact evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 245-260, July.
    9. Carol Tenopir & Elizabeth D Dalton & Suzie Allard & Mike Frame & Ivanka Pjesivac & Ben Birch & Danielle Pollock & Kristina Dorsett, 2015. "Changes in Data Sharing and Data Reuse Practices and Perceptions among Scientists Worldwide," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-24, August.
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    Cited by:

    1. Nushrat Khan & Mike Thelwall & Kayvan Kousha, 2021. "Measuring the impact of biodiversity datasets: data reuse, citations and altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3621-3639, April.
    2. Yongmei Bai & Jian Du, 2022. "Measuring the impact of health research data in terms of data citations by scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6881-6893, December.

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