Published May 15, 2026
| Version 1.0.0
Project deliverable
Open
Towards Fitness-for-purpose assessment in HealthData@EU
Authors/Creators
-
1.
Universitat Politècnica de València
- 2. Polytechnic University of Valencia
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3.
Sciensano (Belgium)
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4.
Instituto Aragonés de Ciencias de la Salud
- 5. Instituto Aragonés de Ciencias de la Salud (IACS)
Description
Proposal Design of a Fitness‑for‑Purpose (F4P) Mechanism for HealthData@EU
Executive Summary
This report proposes an initial design for a Fitness‑for‑Purpose (F4P) mechanism within HealthData@EU, aimed at complementing the existing QUANTUM Data Quality, Utility, and Maturity Label. The F4P mechanism introduces a structured way to capture and share Data Users’ assessments of how well datasets meet specific secondary‑use purposes under the European Health Data Space (EHDS). These assessments are intended to enhance transparency, usability, and trust by making real‑world dataset performance visible through Health Data Access Bodies (HDAB) catalogues.
At its core, the mechanism enables purpose‑specific scoring of datasets, aligned with EHDS Article 53(1) use cases, including scientific research (e.g., AI training/testing), public health surveillance, policymaking and Health Technology Assessment (HTA), statistics, and education. Evaluations are anchored in QUANTUM’s established data quality dimensions, such as completeness, consistency, and accuracy; while also incorporating qualitative feedback through user comments and optional supporting materials (e.g., reports, code, persistent identifiers).
The design defines a post‑use reporting model, requiring feedback submission within EHDS Article 61(4) timelines, while allowing optional early feedback to Data Holders (DHs). Governance is ensured through HDAB‑led validation and moderation, combined with DH rights to review and respond before publication. The solution emphasises open‑source, reusable tooling to support consistent implementation across Member States.
To maximise usability, F4P results are integrated into HDAB portals with intuitive visualisation features, such as filtering by purpose or score thresholds, and dynamic displays including sunburst charts and trend analyses. The mechanism also supports semantic interoperability, using RDF and the Data Quality Vocabulary (DQV) to link feedback with datasets, QUANTUM labels, and access permits in a machine‑readable format.
The proposed model is grounded in stakeholder input, including 14 expert interviews, a 20‑participant workshop, and validation through an external forum of up to 18 experts. However, it intentionally focuses on operational and structural aspects, leaving the detailed scoring methodology out of its scope. This methodology will be developed through a community‑driven, data‑type‑agnostic process, aligned with QUANTUM principles.
The report concludes with 11 recommendations and highlights key open issues, including the degree of obligatoriness, the granularity of purpose definitions, and the resources required for validation. These will need to be addressed during future implementation and alignment with HealthData@EU, ensuring the mechanism evolves into a robust and scalable component of the EHDS ecosystem.
Files
QUANTUM F4P Report_v1.pdf
Files
(3.5 MB)
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Additional details
Related works
- References
- Project deliverable: 10.5281/zenodo.14944767 (DOI)
- Project deliverable: 10.5281/zenodo.14937423 (DOI)
Funding
Software
- Repository URL
- https://github.com/quantum-label/quantum_labelling_tool
- Programming language
- Python , JavaScript
- Development Status
- Active