DATA PEER REVIEW GUIDELINES

Abstract:  As part of a pilot project on data and software peer review at the TU Delft Library, we developed this template for peer reviewing datasets. In creating the template, we referred to existing data peer review guidelines at journals that publish data papers, as well as existing practices in research teams. The template distinguishes between ‘technical’ and ‘scientific’ checks. Technical checks are concerned with the completeness and FAIRness of a dataset, for instance whether there is a README file, an adequate description, metadata, license, and so on. The additional scientific checks look at the quality of data and methodology of data collection, and whether supporting experiments are adequately described, research questions addressed. This would require some accompanying documentation to review, such as a short data paper or journal article. Such a review would be best suited, as with other data peer review practices, at a journal where datasets and accompanying data papers (or articles) are published. However, the template is free to use and adapt as best suited to context.