The vision for EOSC, recognised as the Common European Data Space for Research and Innovation, is to put in place a ‘system of systems’ to find and access data and services for research and innovation in Europe. This is to help researchers store, share, process, analyse and reuse FAIR research outputs within and across disciplines and borders.
The deployment of a network between data repositories and services is instrumental for Open Science to progress in Europe. For this, the EOSC Federation of Nodes has been created and will continue to grow.
In March 2025 the build-up phase of the EOSC Federation kicked off in Brussels. The Federation was launched in November 2025 and entered operations with 14 production-grade nodes on 08 October 2026.
Recognised by the EU as the Common European Data Space for Research and Innovation, the EOSC Federation will grow to accommodate dozens of EOSC Nodes that are interconnected and can collaborate to share and manage scientific data, knowledge, and resources within and across thematic and geographical research communities.
The European research organisations behind the EOSC Nodes have been working together with the EOSC Tripartite to shape the Federation since March 2025 as part of the Build-up Group.
The EOSC Nodes are entry points for users to the EOSC Federation, with each node offering its own and possibly third-party services, including data reposing and accessing services.
To enable the establishment and sustainability of such a distributed system, many questions are in the process of being answered:
- What are the requirements for an entity to become an EOSC Node?
- How will the EOSC Federation be governed?
- What are the financial mechanisms that will support the resource transactions within the EOSC Federation?
The EOSC Tripartite Governance has recognised that answering those questions is of paramount importance for all parties to come to an agreement on realistic scenarios for EOSC’s post-2027 governance and funding models.
EOSC Nodes
The entry points for users of the EOSC Federation. Browse all 28 Nodes or narrow the list by using the filters and search field.
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EOSC EU Node 1 Node
National EOSC Nodes 14 Nodes
Thematic EOSC Nodes 9 Nodes
Infrastructure EOSC Nodes 4 Nodes
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The Tripartite Group
As the decision-making body for EOSC, the EOSC Tripartite Governance should oversee the structure, governance and operations of the EOSC Federation.
The EOSC Tripartite Governance has emphasised that a coordinated effort by the three parties is necessary to build the EOSC Federation, and this is why the “Tripartite Group” to advance the creation of EOSC was established in April 2024.
The main scope of the Tripartite Group is to prepare commonly agreed positions and support the strategic steering of the EOSC Tripartite Governance in what concerns the establishment and operation of EOSC, including the EOSC Federation.
The Tripartite Group supports the coordination and steering of the processes to establish the requirements for the EOSC Federation and the minimum set of rules and policies applicable throughout the Federation. All other relevant processes for the creation of EOSC as an operational infrastructure are to be discussed and prepared for decision making by the Tripartite Group as well.
To fulfill its role, the Tripartite Group meets monthly and may also seek expert advice and set up inclusive community consultations as needed for the execution of its tasks. The Tripartite Group will ensure that all the views of the different stakeholders are considered, and that the processes to build EOSC are inclusive, open, and transparent.
The Tripartite Group is chaired by Michael Arentoft, Head of Unit for Open Science and Research Infrastructures at the European Commission’s Directorate-General for Research and Innovation (DG RTD).
The Tripartite Group’s main responsibilities include:
- To refine the minimum requirements of an EOSC Node.
- To identify and enroll EOSC Nodes into the EOSC Federation.
- To discuss and endorse the EOSC-A-led developments on the EOSC Federation Handbook.
Enrollment of EOSC Nodes
The Tripartite Group works to identify and enroll candidate EOSC Nodes into the EOSC Federation. The Tripartite Governance agrees that this effort needs to be steered to ensure the coherent, sustainable and steady growth of the EOSC Federation.
Second wave (2025-2027)
The Federation entered a new stage of strategic growth with the EOSC Tripartite Governance’s call for second-wave EOSC Nodes, opened on 03 November 2025.
In April 2026, 14 second-wave candidate EOSC Nodes were invited by the Tripartite Governance to enrol in the Federation, enhancing its geographical reach and thematic diversity to further advance the development of a trusted, interoperable, and federated European ecosystem for research data and services. These will establish:
- National EOSC Nodes in Czechia, Croatia, Latvia, North Macedonia, Sweden, Slovenia, Switzerland, and Türkiye;
- pan-European e-Infrastructure EOSC Nodes through GÉANT, EGI, and Scholarly Commons;
- and thematic EOSC Nodes by METROFOOD-RI, EBRAINS RI, and ENVRI.
First wave (2024-2025)
Following a two-stage dialogue process in winter 2024-2025 to establish a sequence for enrolling the first-wave candidate EOSC Nodes, a group of organisations was invited by the Tripartite Governance to join the EOSC EU Node for the kick-off workshop for the EOSC Federation in March 2025. At this meeting, the EOSC Federation Build-up Group was constituted to implement the technical and structural aspects of the Federation.
The EOSC Federation was launched in November 2025.
EOSC Nodes, with the exception of the EOSC EU Node, are developed in-kind by their coordinating and contributing organisations.
the Tripartite Group includes representatives from
- The European Commission’s Directorate-General Research and Innovation (DG RTD)
- Directorate-General Communications Network, Content and Technology (DG CNECT)
- The EOSC Steering Board
- The EOSC-A Board of Directors
- Technical experts mobilised by request and community consultations
For Nodes
For resource providers
Quick links
- EOSC Federation Handbook page
- EOSC Federation news
- Candidate EOSC Nodes
- Scientific use cases
- Build-up Group
- Second wave of EOSC Nodes enrolment call (guidelines for applicants)
- EOSC-A Board position paper on the EOSC Federation and the role of nodes (draft version 12 November 2023)
- Results of the European Commission’s procurement of the EOSC EU Node [“Managed Services for the European Open Science Cloud Platform (EOSC)” (Ref. CNECT/LUX/2022/CD/0023]
Selected scientific use cases of the EOSC Federation
The cross-Node scientific use cases detailed below demonstrate how the EOSC Federation is enabling cross-disciplinary collaboration, empowering researchers, and supporting the creative reuse of FAIR data to accelerate discovery and innovation in Europe. This selection represents only a small number of the use cases undertaken by the Nodes.
- Mapping of Earth’s marine microbiome to inform global climate models and potential carbon sequestration strategies
- Training AI models for improved prostate cancer screening
- Monitoring pathogenic outbreaks and antimicrobial resistance by establishing models for timely cross-border health data sharing in Europe
- Using AI to provide researchers with access to the vast store of scientific data generated at large, public European research infrastructures
- A networked European solution to bring researchers together with the computational resources, large data sets, and scientific workflows essential to basic research and innovation
- A European-based social network of data that brings together high-performance computing with common, scalable approaches to the analysis of the massive imaging data sets collected by astrophysicists, oceanographers, climate scientists, biologists and other researchers
Use case descriptions and videos
Biological sequestration of carbon in the ocean
The scientific use case addresses the ocean’s critical role in mitigating climate change through biological carbon sequestration, a process by which marine microorganisms capture atmospheric carbon dioxide and store it in the deep ocean for centuries.
Despite its global importance for climate modelling, this mechanism remains poorly represented in current models, which still rely on simplified representations of marine ecosystems. The use case seeks to fill this knowledge gap by integrating genomic, environmental, and modelling data within a unified, open, and interoperable framework provided by the EOSC Federation.
Federated analysis of pathogen genomes
The federated analysis of pathogen genomes science case outlines a federated, cross‑border capability for timely analysis of pathogen genomes that brings computation to the data instead of copying sensitive datasets across institutions.
The objective is to shorten time‑to‑insight for outbreak detection, source attribution, and antimicrobial‑resistance (AMR) surveillance while preserving data sovereignty and meeting European legal and ethical requirements. Experience from COVID‑19 showed that sequencing at scale can transform public‑health decision‑making. Operationally, the effort starts with two neighbouring nodes of the EOSC Federation—the Slovakian national node providing workflows, datasets, computational infrastructure and domain expertise, and the Polish national node (via Poland’s National Science Centre (NCN) and a scientific repository service) supplying key technical support and their own datasets. Their geographical proximity make the two EOSC Nodes an ideal pair for a cross-border pilot. The approach demonstrates how to establish a federation of trusted sites, run harmonized workflows locally, and share only the minimum results needed for action.
Federating CERN’s REANA pipelines
The REANA science case focuses on enabling near-data computation—sending computational workflows to where large scientific datasets are stored, rather than transferring massive volumes of data to the researcher.
The use case demonstrates this concept through particle physics—a field that generates enormous data volumes—but it is applicable to many other domains, including astronomy and life sciences. The project aims to show how researchers can execute their analyses directly at the data source, using REANA—CERN’s Reproducible research data analysis platform—to manage containerized workflows across federated computing resources.
Imaging data workflows on Galaxy
This science case on imaging data workflows on Galaxy demonstrates how a federated, open-access computational platform can transform the way imaging data are processed, shared, and reused across diverse scientific domains.
The use case leverages the Galaxy platform to integrate data from a wide range of imaging-based research fields—such as life sciences (microscopy), astrophysics (telescope data), climate science (satellite data), and marine science (underwater imagery)—into a unified analysis environment. The goal is to demonstrate that Galaxy can be integrated into the EOSC Federation’s common infrastructure to serve many disciplines simultaneously, allowing researchers to share workflows, reuse methods, and access powerful computational tools without needing specialised technical expertise.
Multi-centric validation of AI models for prostate cancer screening
Advances in digital pathology are transforming cancer diagnosis by enabling high-resolution imaging of tissue samples and the application of artificial intelligence (AI) for clinical decision support.
Prostate cancer, one of the most prevalent malignancies among men worldwide, represents a critical case for early and accurate diagnosis, as survival rates are strongly tied to timely detection and treatment. The objective of the multi-centric validation (MCVAL) of AI models for prostate-cancer screening use case, coordinated by the BBMRI-ERIC EOSC Node, is to create a secure environment in which AI models for prostate cancer screening can be validated using data from different hospitals. Rather than building new diagnostic systems from scratch, the project focuses on testing an existing model trained on whole-slide images and assessing how well it performs when applied to data processed elsewhere.
PaN-Finder
The PaN-Finder science case presents an artificial intelligence–driven data discovery platform designed to enhance Open Science within Europe’s research communities by making data from photon and neutron facilities easier to find.
The initiative builds upon previous work undertaken through the PaNOSC (Photon and Neutron Open Science Cloud) project, which aimed to interconnect data catalogues from large-scale research facilities. While the initial federated portal provided a single access point to open data, it was limited by inconsistencies in metadata, domain-specific terminology, and the need for users to possess detailed technical knowledge to perform effective searches. PaN-Finder aims to lower these barriers, making the discovery of open research data more intuitive and inclusive.
