Examples
Worked examples
- Is an instance
The EOSC Federation, which federates existing national and thematic e-infrastructure Nodes via shared AAI, catalogue, and PID-resolution services rather than centrally hosting their data.
Counter-examples
Looks similar, but isn't
- Not an instance
A system that copies every participating organisation's dataset into one central store — a mirrored/centralised architecture, not a federated one, regardless of how the copies are labelled.
Editorial commentary
Federation distinguishes itself from centralisation: data stay where they are produced, governed, and stewarded. The federated infrastructure layer (catalogues, query routers, AAI federation, common schemas) brokers access. The pattern is prevalent in biomedical research (ELIXIR, BBMRI-ERIC, EJP-RD), in the EOSC Federation model, and increasingly in privacy-preserving secondary-use of health data (Federated Learning, Federated Analytics, OHDSI OMOP cohort networks). Federation is well-suited to data that cannot or should not be centralised for legal, ethical, or sovereignty reasons.
Worked example: the EOSC Federation model
The EOSC Federation federates existing national, thematic, and pan-European e-infrastructure “Nodes” — it does not own or centrally host the underlying data or compute. Its core federated services are authentication/authorisation (AAI), a shared service catalogue, monitoring, a helpdesk, and persistent identifier resolution — exactly the “catalogues, query routers, AAI federation, common schemas” pattern this page describes, at continental scale.
Counter-example
A system that replicates a full copy of every participating organisation’s dataset into one central store, even if the copies are labelled by origin, is a mirrored/centralised architecture, not a federated one — the defining property of federation is that governance and stewardship remain distributed, not merely that data has multiple physical copies.
Related pages
See also the EOSC Federation, national data infrastructure, data hub, data commons, data lake, and data safe haven.
References
- Wilkinson M.D. et al., “The FAIR Guiding Principles for scientific data management and stewardship,” Scientific Data 3, 2016.
- EOSC Federation, eosc.eu/building-the-eosc-federation.
Also known as
Federated infrastructure · Federation
Machine-readable encodings
Use in your systems
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