Toward Reproducible Computational Research

An Empirical Analysis of Data and Code Policy Adoption by Journals

Victoria Stodden, Peixuan Guo, Zhaokun Ma

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Article numbere67111
JournalPloS one
Volume8
Issue number6
DOIs
StatePublished - Jun 21 2013

Fingerprint

Empirical Research
data analysis
Availability
Information Dissemination

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Toward Reproducible Computational Research : An Empirical Analysis of Data and Code Policy Adoption by Journals. / Stodden, Victoria; Guo, Peixuan; Ma, Zhaokun.

In: PloS one, Vol. 8, No. 6, e67111, 21.06.2013.

Research output: Contribution to journalArticle

@article{cdbc855cbf20407fac5ae02b42f6fbfc,
title = "Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals",
abstract = "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.",
author = "Victoria Stodden and Peixuan Guo and Zhaokun Ma",
year = "2013",
month = "6",
day = "21",
doi = "10.1371/journal.pone.0067111",
language = "English (US)",
volume = "8",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "6",

}

TY - JOUR

T1 - Toward Reproducible Computational Research

T2 - An Empirical Analysis of Data and Code Policy Adoption by Journals

AU - Stodden, Victoria

AU - Guo, Peixuan

AU - Ma, Zhaokun

PY - 2013/6/21

Y1 - 2013/6/21

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84879254020&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84879254020&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0067111

DO - 10.1371/journal.pone.0067111

M3 - Article

VL - 8

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 6

M1 - e67111

ER -