arXiv:2512.16455v4 Announce Type: replace-cross Abstract: The rapid growth of Artificial Intelligence and Machine Learning in scientific research has highlighted a gap between industry-standard MLOps tools and platforms, and the unique requirements of modern and Open Science, particularly regarding the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This paper presents AI4EOSC, a federated, open-source platform designed to operationalize the full AI/ML lifecycle within the European Open Science Cloud (EOSC) ecosystem. Our methodology tackles the fragmentation of distribute
The proliferation of AI/ML in scientific research necessitates dedicated infrastructure, and the European Open Science Cloud (EOSC) convergence provides a timely opportunity for a federated platform.
This initiative addresses the critical gap between industry MLOps and Open Science principles, potentially standardizing and accelerating AI adoption in European scientific endeavors while upholding data sovereignty.
Scientific institutions will gain access to a dedicated, federated, and FAIR-compliant platform for AI/ML lifecycle management, reducing fragmentation and dependency on commercial, non-specialized tools.
- · European scientific research institutions
- · Open Science initiatives
- · European AI developers
- · Data privacy advocates
- · Fragmented, localized AI development efforts
- · Non-FAIR compliant data practices
- · Third-party commercial MLOps providers without open-source integration
AI4EOSC will streamline the development and deployment of AI/ML models across the European scientific community.
This standardization could foster greater collaboration and efficiency in AI-driven research, leading to accelerated scientific discoveries in Europe.
Increased European computational and AI sovereignty could emerge as a result of a robust, localized, and federated AI infrastructure within the EOSC.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI