Developing a model for a Data Lab for Science linking with EOSC and RAISE (RAISE pilot) (CSA)

O čem je ta razpis?

The call funds one coordination and support action to design a sustainable operating model and blueprint for a Data Lab for Science linked to EOSC and RAISE. It targets better researcher access to AI-ready research data and related data services.

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Background

Data labs, introduced in the Data Union Strategy, link AI factories with common European data spaces by offering services that turn data into resources for training AI and developing AI applications, such as aggregation, curation, pseudonymisation and synthetic data generation. This coordination and support action aims to anchor the data lab model in the development of the European Open Science Cloud (EOSC) and the Resource for AI Science in Europe (RAISE). The Data Lab for Science is to be a key output and element of the RAISE data work strand.

Expected outcomes

• A sustainable operating model and reference blueprint for a Data Lab for Science connected to EOSC and RAISE, helping researchers speed up the uptake of AI in science.
• Easier access for researchers to large volumes of AI-ready research data and related high-quality data services for developing and training AI models for science.
• Better coordination, interoperability and spread across countries and disciplines of AI workflows and related services, such as data aggregation, anonymisation, curation or synthetic data generation.

Activities proposals must include

• Identifying, consolidating and organising existing data, services and other results of Horizon Europe EOSC-related projects and other promising community-supported solutions, including mapping them to ease navigation, access and use.
• Identifying the elements needed to integrate the Data Lab for Science into existing European data and high-performance computing infrastructures.
• Identifying technical, operational, legal, organisational or other bottlenecks that hinder the sharing, reuse or combination of data for AI in science.
• Developing a blueprint that addresses these bottlenecks and demonstrating use cases with the EOSC Association and relevant work in the EuroHPC Joint Undertaking.
• Developing governance and funding models for a sustainable path after the project ends.
• Identifying researchers' needs and data service gaps across disciplines, with recommendations for future policy and funding measures.
• Connecting projects that offer data and data services for AI in science and fostering cooperation between them.

Links with other work

The action should build on relevant Horizon Europe results contributing to EOSC and RAISE and on EU-funded projects developing AI solutions for science, such as foundation models, datasets or AI research assistants. It should coordinate closely with projects funded under HORIZON-INFRA-2025-01-EOSC-03, HORIZON-CL4-INDUSTRY-2025-01-DIGITAL-62 and HORIZON-CL4-INDUSTRY-2025-01-DIGITAL-61, and with relevant EuroHPC and AI factory projects.

Form of funding

Eligible costs take the form of a lump sum.

Kdaj je rok za oddajo?

2. februarja 2027 (89 dni)

2 February 2027