Abstract

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.

Keywords

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