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Research article - Peer-reviewed, 2022

Why don't we share data and code? Perceived barriers and benefits to public archiving practices

Gomes, Dylan G. E.; Pottier, Patrice; Crystal-Ornelas, Robert; Hudgins, Emma J.; Foroughirad, Vivienne; Sánchez-Reyes, Luna L.; Turba, Rachel; Martinez, Paula Andrea; Moreau, David; Bertram, Michael; Smout, Cooper A.; Gaynor, Kaitlyn M.


The biological sciences community is increasingly recognizing the value ofopen, reproducible and transparent research practices for science and societyat large. Despite this recognition, many researchers fail to share their dataand code publicly. This pattern may arise from knowledge barriers abouthow to archive data and code, concerns about its reuse, and misalignedcareer incentives. Here, we define, categorize and discuss barriers to dataand code sharing that are relevant to many research fields. We explorehow real and perceived barriers might be overcome or reframed in thelight of the benefits relative to costs. By elucidating these barriers and thecontexts in which they arise, we can take steps to mitigate them and alignour actions with the goals of open science, both as individual scientistsand as a scientific community.


open science; data science; reproducibility,transparency; data reuse; code reuse

Published in

Proceedings of the Royal Society B: Biological Sciences
2022, volume: 289, number: 1987, article number: 20221113

Authors' information

Gomes, Dylan G. E.
Oregon State University
Pottier, Patrice
University of New South Wales
Crystal-Ornelas, Robert
Lawrence Berkeley National Laboratory (Berkeley Lab)
Hudgins, Emma J.
Carleton University
Foroughirad, Vivienne
Georgetown University
Sánchez-Reyes, Luna L.
University of California Merced
Turba, Rachel
University of California Los Angeles (UCLA)
Martinez, Paula Andrea
University of Queensland
Moreau, David
University of Auckland
Swedish University of Agricultural Sciences, Department of Wildlife, Fish and Environmental Studies
Smout, Cooper A.
Institute for Globally Distributed Open Research and Education
Gaynor, Kaitlyn M.
University of British Columbia

UKÄ Subject classification

Information Studies
Information Science

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