Rates and predictors of data and code sharing in the medical and health sciences: Protocol for a systematic review and individual participant data meta-analysis
Author
Hamilton, Daniel GFraser, Hannah
Fidler, Fiona
McDonald, Steve
Rowhani-Farid, Anisa
Hong, Kyungwan
Page, Matthew J
Date
2021-06-22Journal
F1000ResearchPublisher
F1000 Research LtdType
Article
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Numerous studies have demonstrated low but increasing rates of data and code sharing within medical and health research disciplines. However, it remains unclear how commonly data and code are shared across all fields of medical and health research, as well as whether sharing rates are positively associated with implementation of progressive policies by publishers and funders, or growing expectations from the medical and health research community at large. Therefore this systematic review aims to synthesise the findings of medical and health science studies that have empirically investigated the prevalence of data or code sharing, or both. Objectives include the investigation of: (i) the prevalence of public sharing of research data and code alongside published articles (including preprints), (ii) the prevalence of private sharing of research data and code in response to reasonable requests, and (iii) factors associated with the sharing of either research output (e.g., the year published, the publisher's policy on sharing, the presence of a data or code availability statement). It is hoped that the results will provide some insight into how often research data and code are shared publicly and privately, how this has changed over time, and how effective some measures such as the institution of data sharing policies and data availability statements have been in motivating researchers to share their underlying data and code.Rights/Terms
Copyright: © 2021 Hamilton DG et al.Identifier to cite or link to this item
http://hdl.handle.net/10713/16858ae974a485f413a2113503eed53cd6c53
10.12688/f1000research.53874.2
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