Abstract
Funding bodies and other policy-makers are increasingly more concerned with Research Data Management (RDM). The Data Management Plan (DMP) is one of the tools available to perform RDM tasks, however it is not a perfect concept. The Machine-Actionable Data Management Plan (maDMP) is a concept that aims to make the DMP interoperable, automated and increasingly standardised. In this paper we showcase that through the usage of semantic technologies, it is possible to both express and exploit the features of the maDMP. In particular, we focus on showing how a maDMP formalised as an ontology can be used automate the assessment of a funder’s requirements for a given organisation.
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CITATION STYLE
Cardoso, J., Proença, D., & Borbinha, J. (2020). Machine-actionable data management plans: A knowledge retrieval approach to automate the assessment of funders’ requirements. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12036 LNCS, pp. 118–125). Springer. https://doi.org/10.1007/978-3-030-45442-5_15
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