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

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.

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References

  1. Buneman, P., Christie, G., Davies, J. A., Dimitrellou, R., Harding, S. D., Pawson, A. J., Sharman, J. L., & Wu, Y. (2020) Why data citation isn't working, and what to do about it. Database, 2020, baaa022.

  2. Candela, L., Castelli, D., Manghi, P., & Tani, A. (2015). Data journals: a survey. Journal of the Association for Information Science and Technology, 66(9), 1747–1762.

    Article  Google Scholar 

  3. Colavizza, G., Hrynaszkiewicz, I., Staden, I., Whitaker, K., & McGillivray, B. (2020). The citation advantage of linking publications to research data. PLoS ONE, 15(4), e0230416.

    Article  Google Scholar 

  4. Cousijn, H., Feeney, P., Lowenberg, D., Presani, E., & Simons, N. (2019). Bringing citations and usage metrics together to make data count. Data Science Journal, 18(9), 1–7.

    Google Scholar 

  5. Critchlow, T., & Van Dam, K. K. (2016). Data-intensive science. Boca Raton: CRC Press.

    Google Scholar 

  6. Curty, R. G., Crowston, K., Specht, A., Grant, B. W., & Dalton, E. D. (2017). Attitudes and norms affecting scientists’ data reuse. PLoS ONE, 12(12), e0189288.

    Article  Google Scholar 

  7. Dorta-González, P., & Santana-Jiménez, Y. (2018). Prevalence and citation advantage of gold open access in the subject areas of the Scopus database. Research Evaluation, 27(1), 1–15.

    Article  Google Scholar 

  8. Downey, A. S., & Olson, S. (2013). Sharing clinical research data: workshop summary. Washington: National Academies Press.

    Google Scholar 

  9. Fane, B., Ayris, P., Hahnel, M., Hrynaszkiewicz, I., Baynes, G., et al. (2019). The state of open data report 2019. Digital Science: Report. https://doi.org/10.6084/m9.figshare.9980783.v2.

    Google Scholar 

  10. González-Betancor, S. M., & Dorta-González, P. (2019). Publication modalities ‘article in press’ and ‘open access’ in relation to journal average citation. Scientometrics, 120(3), 1209–1223.

    Article  Google Scholar 

  11. Gorgolewski, K., Margulies, D. S., & Milham, M. P. (2013). Making data sharing count: a publication-based solution. Frontiers in Neuroscience, 7, 9.

    Article  Google Scholar 

  12. Kim, Y., & Stanton, J. M. (2012). Institutional and individual influences on scientists’ data sharing practices. Journal of Computational Science Education, 3(1), 47–56.

    Article  Google Scholar 

  13. Kim, Y., & Stanton, J. M. (2016). Institutional and individual factors affecting scientists’ data-sharing behaviors: a multilevel analysis. Journal of the Association for Information Science and Technology, 67(4), 776–799.

    Article  Google Scholar 

  14. Lowndes, J. S. S., Best, B. D., Scarborough, C., Afflerbach, J. C., Frazier, M. R., O’Hara, C. C., et al. (2017). Our path to better science in less time using open data science tools. Nature Ecology and Evolution, 1(6), 1–7.

    Article  Google Scholar 

  15. Martone, M. (2014) Data citation synthesis group: joint declaration of data citation principles. FORCE11. doi:https://doi.org/10.25490/a97f-egyk

  16. Nature Research, Penny, D., Fane, B., Goodey, G., & Baynes, G. (2019) Raw data and questionnaire from the Springer Nature-Digital Science collaboration of an annual survey of research authors on their attitudes and behaviour around research data. https://figshare.com/articles/State_of_Open_Data_2019/10011788

  17. Sayogo, D. S., & Pardo, T. A. (2013). Exploring the determinants of scientific data sharing: Understanding the motivation to publish research data. Government Information Quarterly, 30, S19–S31.

    Article  Google Scholar 

  18. Schmidt, B., Gemeinholzer, B., & Treloar, A. (2016). Open data in global environmental research: The Belmont Forum’s open data survey. PLoS ONE, 11(1), e0146695.

    Article  Google Scholar 

  19. Silvello, G. (2018). Theory and practice of data citation. Journal of the Association for Information Science and Technology, 69(1), 6–20.

    Article  Google Scholar 

  20. Tenopir, C., Allard, S., Douglass, K., Aydinoglu, A. U., Wu, L., Read, E., et al. (2011). Data sharing by scientists: practices and perceptions. PLoS ONE, 6(6), e21101.

    Article  Google Scholar 

  21. Tenopir, C., Rice, N. M., Allard, S., Baird, L., Borycz, J., Christian, L., et al. (2020). Data sharing, management, use, and reuse: practices and perceptions of scientists worldwide. PLoS ONE, 15(3), e0229003.

    Article  Google Scholar 

  22. Vicente-Sáez, R., & Martínez-Fuentes, C. (2018). Open science now: a systematic literature review for an integrated definition. Journal of Business Research, 88, 428–436.

    Article  Google Scholar 

  23. Volk, C. J., Lucero, Y., & Barnas, K. (2014). Why is data sharing in collaborative natural resource efforts so hard and what can we do to improve it? Environmental Management, 53(5), 883–893.

    Article  Google Scholar 

  24. Walters, W. H. (2020). Data journals: incentivizing data access and documentation within the scholarly communication system. Insights, 33(1), 18.

    Article  Google Scholar 

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Correspondence to Pablo Dorta-González.

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Dorta-González, P., González-Betancor, S.M. & Dorta-González, M.I. To what extent is researchers' data-sharing motivated by formal mechanisms of recognition and credit?. Scientometrics (2021). https://doi.org/10.1007/s11192-021-03869-3

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Keywords

  • Data sharing
  • Data reuse
  • Data citation
  • Professional age-cohort differences
  • Open data
  • Open science