Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 0

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

A federated policy-governed architecture for sovereign European data spaces

Lamo, Paula, Valdeolmillos, Diego, Plaza Hernández, Marta, Dimitrakis, Panagiotis, Alonso, Ricardo S.·2026·Open Research Europe

Abstract

European data spaces aim to enable trusted, sovereign and interoperable data sharing across organisational boundaries. Existing reference frameworks address parts of the problem in isolation: GAIA-X concentrates on federated trust and self-descriptions, the International Data Spaces Reference Architecture Model (IDS-RAM) emphasises usage control and the connector pattern, the Data Spaces Support Centre (DSSC) Blueprint consolidates governance vocabulary and Simpl-Open provides a vendor-neutral middleware substrate. The integration of semantic interoperability, policy-driven sovereignty, federated computation across the cloud–edge–high-performance computing (HPC) continuum and decentralised governance within a single deployable architecture remains an open design problem. This article proposes and analyses a conceptual, policy-governed federated architecture derived from the architectural work of the Horizon Europe NOUS project (Grant Agreement No. 101135927). The architecture is organised in five functional layers — data, services, compute, federation and governance — and revolves around five interacting roles: the Data Space Participant (DSP), the Data Space Infrastructure Participant (DSIP), the Data Space Common Services (DSCS) and the companion NOUS Data and Infrastructure Agents (NDA, NIA). A clear separation between Control Plane and Data Plane mediates policy negotiation, contract enforcement, federated learning and infrastructure provisioning across cloud, edge, HPC and quantum back-ends. We illustrate the model through two representative scenarios derived from NOUS use cases — crisis management with heterogeneous geospatial and field data, and cross-organisational federated analytics over heterogeneous compute resources — and we map architectural functions onto major European reference initiatives. The contribution is conceptual: the article does not claim empirical validation, performance benchmarks or formal certification of standards compliance. Limitations and a research agenda — prototyping, federated interoperability testing and formal verification of policy enforcement — are stated explicitly.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.12688/openreseurope.24687.1

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 4 references

Research works printed but not linked: 11

  1. 5. European Parliament and Council: Regulation (EU) 2016/679 on the protection of natural persons with regard to the processing of personal data (General Data Protection Regulation). Official Journal of the European Union. 2016; L 119: 1–88.
  2. 20. Rose S, Borchert O, Mitchell S, et al.: Zero Trust Architecture. NIST Special Publication 800-207. 2020. · DOI · Paper page
  3. 10.1007/978-3-030-93975-5 · DOI
  4. 10.1007/978-3-030-98636-0 · doi:10.1007/978-3-030-98636-0
  5. 10.1145/3512341 · DOI
  6. 26. Solmaz G, Cirillo F, Fürst F, et al.: Enabling data spaces: existing developments and challenges. Commun. ACM. 2022; 65(11): 66–75.
  7. 10.1007/978-3-030-93975-5_8 · doi:10.1007/978-3-030-93975-5_8
  8. 30. Li T, Sahu AK, Talwalkar A, et al.: Federated Learning: Challenges, Methods, and Future Directions. IEEE Signal Process. Mag. 2020; 37(3): 50–60. · DOI · Paper page
  9. 31. Bonawitz K, Eichner H, Grieskamp W, et al.: Towards Federated Learning at Scale: System Design. Proc. Conference on Machine Learning and Systems (MLSys). 2019.
  10. 10.1109/MC.2020.3007297 · doi:10.1109/mc.2020.3007297
  11. 33. Beckman P, Dongarra J, Ferrier N, et al.: Harnessing the Computing Continuum for Programming Our World. Fog Computing: Theory and Practice. Zomaya M, Abawajy J, Buyya A, editors. Wiley;2020; pp. 215–230. · doi:10.1002/9781119551713.ch7

Metadata

Authors
Lamo, P., Valdeolmillos, D., Plaza Hernández, M., Dimitrakis, P., & Alonso, R. S.
Venue
Open Research Europe
Publisher
CERN
Published
2026-08-13
ISSN
2732-5121
Cited by
0
References
4
Funders
European Commission (101135927)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A federated policy-governed architecture for sovereign European data spaces. https://app.cochat.ai/papers/10.12688/openreseurope.24687.1
The paper
Lamo, P., Valdeolmillos, D., Plaza Hernández, M., Dimitrakis, P., & Alonso, R. S. (2026). A federated policy-governed architecture for sovereign European data spaces. Open Research Europe. https://doi.org/10.12688/openreseurope.24687.1

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.