The SURF EOSC Node federates the SURF Research Cloud, FAIR data repository, and EFSS services, bridging Dutch national infrastructures with European-level services.
SURF is the ICT cooperative for Dutch research and education institutions, providing compute, storage, data management, AAI, security, publishing, and innovative services such as quantum and AI fabrics. As an innovator, SURF will bring together key national stakeholders to contribute to the development of a Dutch EOSC Node. These activities will bring together resources and capacity with the aim of making them available to the EOSC Federation and will assess how resources from other EOSC Nodes can be made available to the research community in the Netherlands.
Key objective: To support research and education in the Netherlands through computing, data and networking services, consultancy, training and contracting. Through the EOSC Federation, SURF will explore offering these services cross-border to the wider EOSC community.
Science areas: Multidisciplinary – compute, storage, and FAIR data services across natural and engineering sciences, social sciences and humanities, and life and health sciences.
FAIR data
The SURF EOSC Node offers a comprehensive collection of Dutch open research information, covering publications, research data sets, research software items, from Dutch institutional repositories and research information systems (CRIS), linked to research grants (NWO) and research performing organisations (UNL, VH, KNAW, NFU).
Scientific use cases
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 of AI models for prostate-cancer screening (MCVAL) 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.
Other use cases
- Tools to the Data – EESSI software stack across EOSC nodes for uniform workflows and federated analyses.
- Collecting Data – Federating EFSS services (ResearchDrive, OpenCloudMesh API)
