Landscape overview for the EOSC Federation Semantic Interoperability in 2025

Implementation challenges arrow_forward EOSC interoperability
Landscape, Monitoring and Engagement arrow_forward Landscape Monitoring

Relevance

This deliverable is essential for realizing the European Open Science Cloud (EOSC) vision by ensuring digital objects are consistently understood by humans and machines. It reports on the practical status of semantic interoperability across EOSC projects and nodes, which is fundamental for successfully implementing the FAIR Principles. The work is critical for enhancing data integration, enabling better data reuse, and preparing scientific data for Machine Learning/Artificial Intelligence (ML/AI) applications.

Scope

The deliverable reviews the practical implementation status of semantic interoperability across the EOSC ecosystem by synthesizing information and gathering requirements through a targeted survey of European scientists in EOSC projects, national, and thematic nodes. Its audience includes the EOSC Association, participants in the build-up phase of the EOSC Federation, and anyone interested in the state of semantic interoperability in EOSC.

Main highlights

This deliverable assesses the practical status of Semantic Interoperability within the European EOSC ecosystem, confirming its fundamental role in achieving the FAIR Principles and enabling advanced Machine Learning/Artificial Intelligence (ML/AI) applications. Based on a targeted survey of EOSC projects and nodes, the report highlights a high level of engagement with largely positive outcomes, primarily in improved data discovery. Current efforts, however, are fragmented and driven bottom-up at the project level, leading to limited implementations. The most frequently adopted standards include DCAT, Dublin Core, Schema.org, and PROV-O, supported by Semantic Artefact Catalogues (SACs) like OntoPortal and LOV. A clear consensus among experts calls for moving towards coordinated, standards-based, and operationally embedded semantics, stressing the need for normative guidance and harmonisation to avoid silos and ensure systematic use of Uniform Resource Identifiers (URIs). The report also details emerging challenges at the intersection of semantic interoperability and the needs arising from the secure, federated ecosystems known as Data Spaces, specifically addressing the complexities of governance interoperability (data sovereignty) and semantic alignment at both the metadata and data layers. This analysis sets the foundation for concrete, coordinated recommendations in subsequent deliverable.

Key recommendations

This work highlights the need for Semantic Interoperability (SI) in the EOSC Federation around three pillars, emphasizing a shift from fragmented, bottom-up implementations to a coordinated, standard-based infrastructure. It identifies following areas for action:

  1. Systematic Planning and Governance: SI implementation must be treated as a challenge addressing both technical and organizational aspects. This requires strengthening governance, promoting community collaboration, and moving beyond isolated actions toward systematic planning and harmonization.
  2. Core Infrastructure: There is a clear need to introduce Semantic Artefacts (SA) and Semantic Artefact Catalogues (SAC) into the EOSC core infrastructure. This would address the current issue where efforts are fragmented and lack normative support, leading to shallow data descriptions. Solutions reside in building a centralized infrastructure for SAs and ensuring sustained governance.
  3. Data Spaces Alignment: Interoperability issues arising from the Data Spaces ecosystem must be addressed at three levels: governance (e.g., binding digital/legal entities and data access policies); metadata (solving problems with mapping various domain-specific metadata profiles); and data (managing the significantly larger number of classes and properties for data representation). The critical solution is to register domain-specific SAs in SACs and ensure that mappings and crosswalks are stored in a FAIR, discoverable, and reusable way.

These points provide the basis for the concrete recommendations which are getting described in the upcoming second deliverable.