IASSIST, Research Journals and Data Linkages

The future of data publication was a big topic at this year’s IASSIST (International Association for Social Science Information Services and Technology) conference. The conference (the 39th to date) entitled Data Innovation: Increasing Accessibility, Visibility and Sustainability was hosted by GESIS – Leibniz Institute for the Social Sciences and held in Cologne (Köln), Germany.

One of the key areas for discussion was around how journals and data can link to each other. Angus Whyte and I presented in a session entitled Expanding Scholarship: Research Journals and Data Linkages. I began the session by outlining recent developments in my talk The Rise of the Data Journal. To explain, a data journal comprises of data articles. A data article is a paper that describes a data set, the data set is usually stored in an accredited repository. The paper gives details of the data collection (when, why, how) and the processing of the data, software, file formats etc. It has a cover sheet, which contains familiar elements such at title, date, authors, abstract, persistent identifiers (DOI, ARK), and set of links to archived artefacts. A data article is unlike a traditional paper in that there is no novel analyses or ground breaking conclusions. However one advantage is that the author list could include those involved in data management and processing. Data journals have been widely discussed as part of the Preparde project and they have been using the Geoscience data journal published by Wiley-Blackwell as a test-bed data journal.

After my talk there followed a presentation by Sven Vlaeminck 
 from Leibniz Information Centre for Economics on Research Data Management in Economics Journals: Data Policies and Data Description as Prerequisites of Reproducible Research. Vlaeminck explained that after a piece of work that had encouraged economists to replicate studies in articles by tracing related data had failed due to unavailable data the EDaWax project had begun to look at data policies. They had found that of 141 journals only 40 had data availability policies, and of these only 4 had 50% or more of their articles accompanied by data. There was acknowledgement among the economists in the room of the poor sharing culture in their discipline, primarily due to legal issues. However it was agreed that there still could be links to the data, even if it isn’t accessible.

Angus Whyte concluded the session with a talk on 'Perspectives on the Role of Trustworthy Repository Standards' in Data Journal Publication' (available on slideshare). This focused on the PREPARDE project's work to draft guidelines for journal editors. In the data journal model it is crucial to maintain the link between a data paper and the dataset it describes. This begs certain questions, such as how data journal editors can know a repository is trustworthy, how repositories can prove their trustworthiness, and what 'trustworthy' means for a model that includes pre-publication peer review of the data as well as the data paper.  Angus summarised how a workshop at IDCC had considered these questions and related issues, such as the relevance of  trusted repository standards including the Data Seal of Approval and ISO 16363. A workshop report is also available.

This led into discussion of social science use cases for data journals. Some IASSISTers were enthusiastic about the possibilties. For example survey protocols, coding details and the practicalities of dealing with particular data types were talked of as possible themes for an IASSIST a Special Interest Group. There was also some enthusiasm for the creation of a data journal to sit alongside IASSIST Quarterly. Some felt that a data journal could be used as a place for data sets that had real value for the community but would not fit within a traditional journal article. Others felt that senior academic support would depend on high impact journals being available, and without these data journals would not take off. In that respect the forthcoming Nature publication Scientific Data looks like it may make a real difference.