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.
Highlights
The journal publication process is a key lever shaping the nature of scholarly communication and promoting the integrity of the scholarly record
In June of 2012, 62% of the journals in this study make no mention of a data policy and 79% make no mention of a software policy
We hypothesized that open data and code policies are in the process of being adopted more widely, that data policies would lead code policies, and that open access journals would be more likely to have policies making data and code open as well
Summary
The journal publication process is a key lever shaping the nature of scholarly communication and promoting the integrity of the scholarly record. The ability to replicate published computational results relies on the availability of the data and code used to generate the findings, and lack of access to such materials is engendering a credibility crisis in the computational sciences [1,2,3]. Recent attention has focused on changes needed in scientific publishing and the role of journal open data requirements in fostering scientific reliability [4,5,6,7] but little research has focused on availability of the code needed to replicate computational findings, this has been associated with high impact publications [8]. In this study we document data sharing policies for 170 journals in June 2011 and again in June 2012. We seek to understand the nature of these policies, their rate of implementation, and how different journal characteristics may be related to adoption rates
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