2nd Workshop on DaMaLOS (Data and research objects management for Linked Open Science)
Automating Evaluation of Machine-Actionable Data Management Plans with Semantic Web Technologies
Machine-actionable data management plans (maDMPs) have, by their very nature, potential to bring advantages over data management plans that are written in text form. By employing maDMPs, not only researchers should be able to benefit from their merits, but also research funders receiving and assessing the DMPs. Science Europe, which is an association of major European research funders, have published an evaluation rubric that provides a common basis to support evaluation of DMPs. By stating a set of criteria, it helps to ensure submitted DMPs cover required aspects and support FAIR data management.
In this paper, we present a semi-automatic approach to leverage the benefits of maDMPs by providing SPARQL queries that represent requirements of Science Europe. The goal is to support reviewers in the assessment of DMPs expressed as maDMPs. The results shows that semantic web technologies can help in providing customised views to reviewers, but human inspection and interpretation is still needed.
Tomasz Miksa is senior researcher at SBA Research.