As data publishing technology and data management policies have evolved over the past decade, more academic journals are working with data repositories to disseminate the data associated with published articles. The Dataverse Project at Harvard University’s Institute for Quantitative Social Science (IQSS)recently received a two year grant (2015-2017) from the Sloan Foundation, in partnership with the Odum Institute at the University of North Carolina at Chapel Hill, to collaborate with a variety of publishers, repositories and the international scientific community in order to integrate and automate data publication with more traditional scholarly communication, thus helping make data sharing and preservation an intrinsic and transparent part of the scholarly publication process.
Figure 1. Diagram of an Automated Integrated Article and Data Publishing Workflow
This project is an expansion of a previous Sloan grant (2012-2014), which the Dataverse Project worked on with Stanford University and Simon Fraser University's Public Knowledge Project (PKP) to successfully implement automated data deposit integration (via an API using SWORDv2 protocol) between Dataverse and Open Journal Systems' (OJS) publishing platform (Dataverse plugin) [see this project's website].
This new project will work with a wider group of journals, publishers and publishing systems (beyond OJS), including Sage, PLOS, Elsevier, F1000 Research, several economics journals (e.g., Econometrica, Review of Economics and Statistics), etc. Additionally, the focus will be on engaging more with the wider research community, including FORCE11, RDA, FAIRport, etc to ensure that the data repository API is aligned with a common standard across disciplines, publishing systems and repositories. More specifically, project goals include: extending support for more metadata (beyond Dublin Core); evaluating moving from SWORD to a more generic and suitable data repository API that will allow for sharing data across a wider variety of publishing systems (beyond just journals); supporting more data review workflows; embedding dataset preview widgets into the article; along with automating data citation and bi-directional linking between articles and data. More information will be made available in January 2015 so please stay tuned! If you have any questions or are interested in contributing to this project please get in touch with the project coordinator: Eleni Castro.