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To what extent is researchers' data-sharing motivated by formal mechanisms of recognition and credit?

Author

Listed:
  • Pablo Dorta-González

    (Universidad de Las Palmas de Gran Canaria)

  • Sara M. González-Betancor

    (Universidad de Las Palmas de Gran Canaria)

  • María Isabel Dorta-González

    (Universidad de La Laguna)

Abstract

Data sharing by researchers is a centerpiece of Open Science principles and scientific progress. For a sample of 6019 researchers, we analyze the extent/frequency of their data sharing. Specifically, the relationship with the following four variables: how much they value data citations, the extent to which their data-sharing activities are formally recognized, their perceptions of whether sufficient credit is awarded for data sharing, and the reported extent to which data citations motivate their data sharing. In addition, we analyze the extent to which researchers have reused openly accessible data, as well as how data sharing varies by professional age-cohort, and its relationship to the value they place on data citations. Furthermore, we consider most of the explanatory variables simultaneously by estimating a multiple linear regression that predicts the extent/frequency of their data sharing. We use the dataset of the State of Open Data Survey 2019 by Springer Nature and Digital Science. Results do allow us to conclude that a desire for recognition/credit is a major incentive for data sharing. Thus, the possibility of receiving data citations is highly valued when sharing data, especially among younger researchers, irrespective of the frequency with which it is practiced. Finally, the practice of data sharing was found to be more prevalent at late research career stages, despite this being when citations are less valued and have a lower motivational impact. This could be due to the fact that later-career researchers may benefit less from keeping their data private.

Suggested Citation

  • Pablo Dorta-González & Sara M. González-Betancor & María Isabel Dorta-González, 2021. "To what extent is researchers' data-sharing motivated by formal mechanisms of recognition and credit?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2209-2225, March.
  • Handle: RePEc:spr:scient:v:126:y:2021:i:3:d:10.1007_s11192-021-03869-3
    DOI: 10.1007/s11192-021-03869-3
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    References listed on IDEAS

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    1. Carol Tenopir & Natalie M Rice & Suzie Allard & Lynn Baird & Josh Borycz & Lisa Christian & Bruce Grant & Robert Olendorf & Robert J Sandusky, 2020. "Data sharing, management, use, and reuse: Practices and perceptions of scientists worldwide," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-26, March.
    2. Renata Gonçalves Curty & Kevin Crowston & Alison Specht & Bruce W Grant & Elizabeth D Dalton, 2017. "Attitudes and norms affecting scientists’ data reuse," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-22, December.
    3. Leonardo Candela & Donatella Castelli & Paolo Manghi & Alice Tani, 2015. "Data journals: A survey," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(9), pages 1747-1762, September.
    4. Youngseek Kim & Jeffrey M. Stanton, 2016. "Institutional and individual factors affecting scientists' data-sharing behaviors: A multilevel analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(4), pages 776-799, April.
    5. Gianmaria Silvello, 2018. "Theory and practice of data citation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(1), pages 6-20, January.
    6. Pablo Dorta-González & Yolanda Santana-Jiménez, 2018. "Prevalence and citation advantage of gold open access in the subject areas of the Scopus database," Research Evaluation, Oxford University Press, vol. 27(1), pages 1-15.
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