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<div class="csl-entry">Cardoso, J., Castro, L. J., Ekaputra, F. J., Jacquemot-Perbal, M.-C., Suchánek, M., Miksa, T., & Borbinha, J. (2022). DCSO: towards an ontology for machine-actionable data management plans. <i>Journal of Biomedical Semantics</i>, <i>13</i>, Article 21. https://doi.org/10.1186/s13326-022-00274-4</div>
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dc.identifier.issn
2041-1480
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/192677
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dc.description.abstract
The concept of Data Management Plan (DMP) has emerged as a fundamental tool to help researchers through the systematical management of data. The Research Data Alliance DMP Common Standard (DCS) working group developed a set of universal concepts characterising a DMP so it can be represented as a machine-actionable artefact, i.e., machine-actionable Data Management Plan (maDMP). The technology-agnostic approach of the current maDMP specification: (i) does not explicitly link to related data models or ontologies, (ii) has no standardised way to describe controlled vocabularies, and (iii) is extensible but has no clear mechanism to distinguish between the core specification and its extensions.This paper reports on a community effort to create the DMP Common Standard Ontology (DCSO) as a serialisation of the DCS core concepts, with a particular focus on a detailed description of the components of the ontology. Our initial result shows that the proposed DCSO can become a suitable candidate for a reference serialisation of the DMP Common Standard.
en
dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.description.sponsorship
SBA Research gemeinnützige GmbH
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dc.language.iso
en
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dc.publisher
BMC
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dc.relation.ispartof
Journal of Biomedical Semantics
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Vocabulary, Controlled
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dc.subject
Data management plan
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dc.subject
Machine-actionable data management plan
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dc.subject
Ontology
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dc.subject
Semantic web technologies
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dc.subject
Biological Ontologies
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dc.subject
Data Management
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dc.title
DCSO: towards an ontology for machine-actionable data management plans