The CERN EOSC Node will strengthen the EOSC Federation by providing high-TRL services and technology essential for high-energy physics (HEP) and interdisciplinary research. Services and technology include Zenodo, REANA, Indico, INSPIRE-HEP, HEPData, and the CERN Open Data portal, along with the ESCAPE Virtual Research Environment (VRE).
These will support FAIR, reproducible, and scalable workflows, enabling broader scientific impact. The Node will be deployed in two phases: first by onboarding CERN technology into the EOSC EU Node and testing the virtual credit model, and second by establishing the CERN EOSC Node with quotas and controlled resource allocation.
Key objective: To integrate CERN’s high-TRL services and technology into the EOSC Federation, as well as to support the exploitation of FAIR CERN Open Data, through reproducible workflows, analysis facilities, and cross-disciplinary collaboration.
Science area: Particle physics
FAIR data
CERN provides curated FAIR Open Data from particle physics and literature via the CERN Open Data portal, HEPData, and INSPIRE-HEP. Zenodo ensures long-term preservation, discoverability, and interoperability of multi-domain research outputs.
Scientific use cases
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.
Other use cases
- ESCAPE VRE: Modular, scalable platform integrating Rucio (data lake), REANA (workflows), and Jupyter (interactive analysis).
- Federated workflows across nodes (multi-node distributed analysis).
- Hosting curated Open Particle Physics datasets and providing access for cross-disciplinary communities.
