Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.

Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals. We...

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Autores principales:	Victoria Stodden, Peixuan Guo, Zhaokun Ma
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/aa45b865765a4d02a36c97dcad449b80
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spelling	oai:doaj.org-article:aa45b865765a4d02a36c97dcad449b802021-11-18T07:40:34ZToward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.1932-620310.1371/journal.pone.0067111https://doaj.org/article/aa45b865765a4d02a36c97dcad449b802013-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0067111https://doaj.org/toc/1932-6203Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals. We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012. We build a predictive model of open data and code policy adoption as a function of impact factor and publisher and find higher impact journals more likely to have open data and code policies and scientific societies more likely to have open data and code policies than commercial publishers. We also find open data policies tend to lead open code policies, and we find no relationship between open data and code policies and either supplemental material policies or open access journal status. Of the journals in this study, 38% had a data policy, 22% had a code policy, and 66% had a supplemental materials policy as of June 2012. This reflects a striking one year increase of 16% in the number of data policies, a 30% increase in code policies, and a 7% increase in the number of supplemental materials policies. We introduce a new dataset to the community that categorizes data and code sharing, supplemental materials, and open access policies in 2011 and 2012 for these 170 journals.Victoria StoddenPeixuan GuoZhaokun MaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 6, p e67111 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Victoria Stodden Peixuan Guo Zhaokun Ma Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.
description	Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals. We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012. We build a predictive model of open data and code policy adoption as a function of impact factor and publisher and find higher impact journals more likely to have open data and code policies and scientific societies more likely to have open data and code policies than commercial publishers. We also find open data policies tend to lead open code policies, and we find no relationship between open data and code policies and either supplemental material policies or open access journal status. Of the journals in this study, 38% had a data policy, 22% had a code policy, and 66% had a supplemental materials policy as of June 2012. This reflects a striking one year increase of 16% in the number of data policies, a 30% increase in code policies, and a 7% increase in the number of supplemental materials policies. We introduce a new dataset to the community that categorizes data and code sharing, supplemental materials, and open access policies in 2011 and 2012 for these 170 journals.
format	article
author	Victoria Stodden Peixuan Guo Zhaokun Ma
author_facet	Victoria Stodden Peixuan Guo Zhaokun Ma
author_sort	Victoria Stodden
title	Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.
title_short	Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.
title_full	Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.
title_fullStr	Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.
title_full_unstemmed	Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.
title_sort	toward reproducible computational research: an empirical analysis of data and code policy adoption by journals.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/aa45b865765a4d02a36c97dcad449b80
work_keys_str_mv	AT victoriastodden towardreproduciblecomputationalresearchanempiricalanalysisofdataandcodepolicyadoptionbyjournals AT peixuanguo towardreproduciblecomputationalresearchanempiricalanalysisofdataandcodepolicyadoptionbyjournals AT zhaokunma towardreproduciblecomputationalresearchanempiricalanalysisofdataandcodepolicyadoptionbyjournals
_version_	1718423118744125440

Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals.

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