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How to Share Data for Collaboration

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  • Shannon E. Ellis
  • Jeffrey T. Leek

Abstract

Within the statistics community, a number of guiding principles for sharing data have emerged; however, these principles are not always made clear to collaborators generating the data. To bridge this divide, we have established a set of guidelines for sharing data. In these, we highlight the need to provide raw data to the statistician, the importance of consistent formatting, and the necessity of including all essential experimental information and pre-processing steps carried out to the statistician. With these guidelines we hope to avoid errors and delays in data analysis.

Suggested Citation

  • Shannon E. Ellis & Jeffrey T. Leek, 2018. "How to Share Data for Collaboration," The American Statistician, Taylor & Francis Journals, vol. 72(1), pages 53-57, January.
    • Handle: RePEc:taf:amstat:v:72:y:2018:i:1:p:53-57
    DOI: 10.1080/00031305.2017.1375987
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    References listed on IDEAS

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    1. Keith Baggerly, 2010. "Disclose all data in publications," Nature, Nature, vol. 467(7314), pages 401-401, September.
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    Cited by:

    1. Wesley Mendes-Da-Silva, 2018. "The Promotion of Transparency and the Impact of Research on Business," RAC - Revista de Administração Contemporânea (Journal of Contemporary Administration), ANPAD - Associação Nacional de Pós-Graduação e Pesquisa em Administração, vol. 22(4), pages 639-649.
    2. Nicholas Tierney & Dianne Cook, 2018. "Expanding tidy data principles to facilitate missing data exploration, visualization and assessment of imputations," Monash Econometrics and Business Statistics Working Papers 14/18, Monash University, Department of Econometrics and Business Statistics.

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