This information is over 2 years old. Information was current at time of publication.{"id":12588,"date":"2020-02-19T14:29:32","date_gmt":"2020-02-19T18:29:32","guid":{"rendered":"https:\/\/info.hsls.pitt.edu\/updatereport\/?p=12588"},"modified":"2020-03-03T15:44:20","modified_gmt":"2020-03-03T19:44:20","slug":"data-journals-standalone-publication-for-replication-negative-intermediate-or-simply-noteworthy-data","status":"publish","type":"post","link":"https:\/\/info.hsls.pitt.edu\/updatereport\/data-journals-standalone-publication-for-replication-negative-intermediate-or-simply-noteworthy-data\/","title":{"rendered":"Data Journals: Standalone Publication for Replication, Negative, Intermediate, or Simply Noteworthy Data"},"content":{"rendered":"

As the scholarly community continues to recognize the importance of open data sharing for increasing the reproducibility of research, researchers are faced with a growing menu of options through which to make their data available. For example, is it better to deposit data in a digital repository, which often grants depositors a Digital Object Identifier (DOI), or to formally describe a dataset in a data journal article, or to share it through a metadata registry like the Pitt Data Catalog<\/a>? A recent video call for papers<\/a> from the journal Data in Brief <\/em>argues that data journals offer a unique opportunity for standalone publication of genres that are often critically underserved by the scholarly publishing ecosystem: datasets containing replication data, negative results, and intermediate data for research in progress.<\/p>\n

The distinctions between data papers, data deposits, and traditional research articles can be blurry in terms of how they describe datasets and their creation, as a recent article <\/a>in the Journal of the Association for Information Science and Technology<\/em> suggests. But at their core, most data journals aim to make data permanent, by way of being preserved in the journal\u2019s archives; peer-reviewed through the journal\u2019s normal workflows; and citable, thanks to well-established norms for citing published research (whereas citation standards for data in repositories, for example, are frequently negotiable or in flux.)<\/p>\n

A 2015 survey<\/a> counted over 100 data journals publishing across all disciplines, a number that has fluctuated since then as new data journals open and established ones close (including the merger of Genomics Data <\/em>with Data in Brief<\/em>, two health sciences data journals mentioned in an HSLS Update<\/em> 2014 article<\/a> on this topic). As with digital-only journals, however, this occasional instability should not be a cause of undue concern: trustworthy journals (data or otherwise) generally continue to make their archives available according to best practices.<\/p>\n

Interested in getting started using or submitting to data journals? This short list includes some of the biggest data journals, as well as smaller journals with a health sciences focus:<\/p>\n