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DCSO: towards an ontology for machine-actionable data management plans.

João Cardoso1,2, Leyla J Castro3, Fajar J Ekaputra4

  • 1INESC-ID, R. Alves Redol, 9, Lisboa, 1000-029, Portugal. joao.m.f.cardoso@tecnico.ulisboa.pt.

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Summary

A new DMP Common Standard Ontology (DCSO) was developed to improve machine-actionable Data Management Plans (maDMP). This ontology provides a standardized way to represent DMP concepts, enhancing data management practices for researchers.

Keywords:
Data management planMachine-actionable data management planOntologySemantic web technologies

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Area of Science:

  • Data Science
  • Information Science

Background:

  • Data Management Plans (DMPs) are crucial for systematic data handling in research.
  • The Research Data Alliance DMP Common Standard (DCS) aimed to create machine-actionable DMPs (maDMP).
  • Current maDMP specifications lack explicit links to data models/ontologies and standardized vocabulary descriptions.

Purpose of the Study:

  • To develop the DMP Common Standard Ontology (DCSO) as a machine-readable serialization of DCS core concepts.
  • To address limitations in the current maDMP specification regarding data model linkage, vocabulary description, and extensibility.
  • To provide a detailed description of the DCSO components.

Main Methods:

  • Community-driven development of the DMP Common Standard Ontology (DCSO).
  • Focus on serializing the core concepts of the DMP Common Standard (DCS).
  • Detailed component analysis and description of the ontology structure.

Main Results:

  • The proposed DCSO effectively serializes the DCS core concepts.
  • The DCSO offers a structured approach to representing DMP information.
  • Initial results indicate DCSO's suitability as a reference serialization for the DMP Common Standard.

Conclusions:

  • The DMP Common Standard Ontology (DCSO) is a promising solution for creating standardized, machine-actionable Data Management Plans.
  • DCSO addresses key limitations of previous maDMP specifications.
  • This ontology facilitates better data management and interoperability in research.