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Water, Water, Everywhere: Defining and Assessing Data Sharing in Academia

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  • Steven Van Tuyl
  • Amanda L Whitmire

Abstract

Sharing of research data has begun to gain traction in many areas of the sciences in the past few years because of changing expectations from the scientific community, funding agencies, and academic journals. National Science Foundation (NSF) requirements for a data management plan (DMP) went into effect in 2011, with the intent of facilitating the dissemination and sharing of research results. Many projects that were funded during 2011 and 2012 should now have implemented the elements of the data management plans required for their grant proposals. In this paper we define ‘data sharing’ and present a protocol for assessing whether data have been shared and how effective the sharing was. We then evaluate the data sharing practices of researchers funded by the NSF at Oregon State University in two ways: by attempting to discover project-level research data using the associated DMP as a starting point, and by examining data sharing associated with journal articles that acknowledge NSF support. Sharing at both the project level and the journal article level was not carried out in the majority of cases, and when sharing was accomplished, the shared data were often of questionable usability due to access, documentation, and formatting issues. We close the article by offering recommendations for how data producers, journal publishers, data repositories, and funding agencies can facilitate the process of sharing data in a meaningful way.

Suggested Citation

  • Steven Van Tuyl & Amanda L Whitmire, 2016. "Water, Water, Everywhere: Defining and Assessing Data Sharing in Academia," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-16, February.
  • Handle: RePEc:plo:pone00:0147942
    DOI: 10.1371/journal.pone.0147942
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    References listed on IDEAS

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    1. Paul Sturges & Marianne Bamkin & Jane H.S. Anders & Bill Hubbard & Azhar Hussain & Melanie Heeley, 2015. "Research data sharing: Developing a stakeholder-driven model for journal policies," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(12), pages 2445-2455, December.
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