Gaps, redundancies, and synergies in researchers’ EHDS-EOSC journeys

Relevance

As Europe advances both the European Open Science Cloud (EOSC) and the European Health Data Space (EHDS), understanding how these two major initiatives interact is critical for researchers, data holders, and policymakers. This work directly supports the strategic goal of unlocking the potential of health data for research and innovation while minimising fragmentation, redundancies, and barriers to cross-border collaboration.

Scope

This deliverable presents a comprehensive gap analysis of the interplay between the EOSC ecosystem and the EHDS regulation, covering data hosting and discoverability, interoperability and quality, and data processing. It targets researchers, research infrastructure operators, policymakers, Health Data Access Bodies, and technical implementers active in either or both ecosystems.

Main highlights

The document maps the EOSC and EHDS landscapes across governance, infrastructure, interoperability, and data processing. A foundational distinction underpins the entire analysis: EHDS is a binding, top-down regulatory framework exclusively governing electronic health data — establishing legal bases, Secure Processing Environments (SPEs), and Health Data Access Bodies (HDABs) — whereas EOSC is a voluntary, federated, community-driven initiative spanning all scientific disciplines. The two are complementary but legally and operationally independent.

Despite this distinction, several concrete synergies emerge. EOSC nodes could provide SPE-compliant infrastructure; metadata standards such as HealthDCAT-AP could be aligned across both ecosystems to improve data discoverability; authentication frameworks (eIDAS, AARC/Life Science Login) are already technically compatible; and EOSC’s projects devoted Trusted Research Environments (TREs) can directly inform EHDS SPE design.

The document equally flags persistent risks. Semantic interoperability of health datasets remains fragmented, and the SPE implementing acts —which will define critical technical requirements— are not due until March 2027. Importantly, since EHDS deliberately refrains from prescribing semantic or technical standards for secondary use data, research communities and EOSC have a concrete voluntary role to fill. The phased timeline for EHDS secondary use provisions (2029–2031) provides a meaningful window to advance this alignment work before full regulatory application.

Key recommendations

While the document is framed as a gap analysis rather than a formal recommendations document, which will be covered in the second Deliverable to be produced by the Health Data Task Force, a number of action points emerge:

1. Align metadata standards: Pursue technical interoperability between EHDS’s HealthDCAT-AP and EOSC cataloguing standards to improve data discoverability without merging their distinct governance structures.
2. Leverage EOSC infrastructure for SPEs: EOSC nodes that will support TRE capabilities (e.g., the ones developed in EOSC-ENTRUST, SIESTA or TITAN projects) should actively pilot EHDS compliance to inform SPE implementing acts and reduce duplication of effort.
3. Harmonise authentication: Build on existing compatibility between eIDAS, AARC, and Life Science Login to ensure seamless access management across EHDS and EOSC services.
4. Promote voluntary adoption of semantic standards: EOSC’s expertise in FAIR principles should be leveraged to support health data holders in adopting domain-relevant standards (e.g., HL7 FHIR, OMOP CDM), filling the intentional gap left by the EHDS regulation.
5. Engage in TEHDAS2 consultations: The EOSC Health Data Task Force should actively contribute to the TEHDAS2 Joint Action to shape the forthcoming implementing acts and ensure EOSC-aligned solutions are considered.
6. Address Data Transfer Agreements for non-EHDS use cases: EOSC may accommodate common DTA templates for health-related data sharing scenarios that fall outside the EHDS framework (e.g., large international cohort repositories).
7. Integrate AI opportunities: Future work should address how EOSC computational resources and AI Factories can complement EHDS’ SPEs for healthcare AI development.