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OSTrails/DMP-Evaluation-Service

DMP-Evaluation-Service

Repository with specifications and rulesets developed to support the semi-automated evaluation of Data Management Plans (DMPs). It is designed to support evaluation of both machine-actionable DMPs (maDMPs), i.e. in JSON format and compliant with the DMP Common Standard (DCS), as well as traditional, narrative-style DMPs. It is a key component of the OSTrails project (https://ostrails.eu/) and reflects input from research funders, institutional policy frameworks, and research support needs.

Authors: Tomasz Miksa, Elli Papadopoulou, Lukas Arnhold, Andres Mauricio, Maria Kontopidi, Diamantis Tziotzios, Georgios Kakaletris

Evaluation Dimensions

Evaluation is organised across five core dimensions, each addressing a critical aspect of a high-quality Data Management Plan:

  • Content Completeness: Verifies whether all required sections of the DMP have been addressed. It checks for presence, adequacy, and consistency of information, ensuring that no essential element is missing.
  • Research Data Management Coverage: Assesses how thoroughly the DMP addresses key areas of research data management, such as data collection, documentation, storage, access, sharing, and preservation.
  • Openness: Examines the extent to which the DMP supports open access to data, metadata, and other outputs, including considerations of licensing, embargo periods, and justifications for any access restrictions.
  • FAIRness: Evaluates the extent to which the DMP aligns with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), including aspects such as metadata richness, licensing, and use of persistent identifiers.
  • Policy alignment: Measures the degree to which the DMP reflects and adheres to relevant institutional, funder, and legal policies (e.g., GDPR compliance, data sharing mandates).
  • Standards compliance: Evaluates whether the DMP adheres to recognized structural and content standards (e.g., the DMP Common Standard), supporting interoperability, machine-readability, and alignment with community expectations.

Exemplar metadata

Compatible with: https://github.com/OSTrails/FAIR_assessment_output_specification

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Tool for automated assessment of maDMPs

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