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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.
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 ass...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485098/ https://www.ncbi.nlm.nih.gov/pubmed/34631024 http://dx.doi.org/10.12688/f1000research.53874.2 |
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author | Hamilton, Daniel G. Fraser, Hannah Fidler, Fiona McDonald, Steve Rowhani-Farid, Anisa Hong, Kyungwan Page, Matthew J. |
author_facet | Hamilton, Daniel G. Fraser, Hannah Fidler, Fiona McDonald, Steve Rowhani-Farid, Anisa Hong, Kyungwan Page, Matthew J. |
author_sort | Hamilton, Daniel G. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8485098 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-84850982021-10-08 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. Hamilton, Daniel G. Fraser, Hannah Fidler, Fiona McDonald, Steve Rowhani-Farid, Anisa Hong, Kyungwan Page, Matthew J. F1000Res Study Protocol 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. F1000 Research Limited 2021-09-09 /pmc/articles/PMC8485098/ /pubmed/34631024 http://dx.doi.org/10.12688/f1000research.53874.2 Text en Copyright: © 2021 Hamilton DG et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Study Protocol Hamilton, Daniel G. Fraser, Hannah Fidler, Fiona McDonald, Steve Rowhani-Farid, Anisa Hong, Kyungwan Page, Matthew J. 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. |
title | 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. |
title_full | 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. |
title_fullStr | 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. |
title_full_unstemmed | 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. |
title_short | 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. |
title_sort | 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. |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485098/ https://www.ncbi.nlm.nih.gov/pubmed/34631024 http://dx.doi.org/10.12688/f1000research.53874.2 |
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