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RI-SCALE

financed

Unlocking RI potential with Scalable AI and Data

Data and AI are the fuel of scientific discoveries, and Research Infrastructures (RIs) are at the forefront of this process, generating massive and increasingly more complex datasets. However, the growing size, diversity, and velo... see more

29/02/2028

unknown leader

10M€

Project Budget: 10M€

Project leader unknown leader

PARTICIPATION DEPralty Sin fecha límite de participación.

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Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2024-10-23

HORIZON-INFRA-2024-TECH-01-02: Development of tools, solutions, mo... Expected Outcome:Project results are expected to contribute to several of the following expected out...

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28 Participantes

FONDAZIONE CENTRO EURO-MEDIT...

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Project duration: 40 months Date Start: 2024-10-23
End date: 2028-02-29

Project leader unknown leader

Project Budget 10M€

participation deadline Sin fecha límite de participación.

Project description Data and AI are the fuel of scientific discoveries, and Research Infrastructures (RIs) are at the forefront of this process, generating massive and increasingly more complex datasets. However, the growing size, diversity, and velocity of research data and software demand large-scale infrastructures and technical expertise from those on the user side. RI-SCALE will address this challenge by delivering Data Exploitation Platforms (DEPs). These scalable environments will co-host scientific data with preconfigured AI frameworks and models on powerful compute resources and unlock full data and AI potential for scientific users, RI operators and industry. RI-SCALE will design and develop the DEP technology with four RIs: ENES, EISCAT, BBMRI and Euro-BioImaging. DEP instances will be deployed for environmental and life sciences, validating the technology through 8 scientific and 4 technical use cases. These will run on national e-infrastructures from the EGI Federation and (pre)exascale machines from EuroHPC. RI-SCALE will collaborate with Destination Earth, EUCAIM cancer images data space, Copernicus Data Space Ecosystem, EOSC and Gaia-X to ensure interoperability within the broader landscape. The project will also facilitate industry and university collaborations, provide training and consultancy events to increase the uptake of AI technologies by additional RIs and explore sustainable DEP operation models for RI communities.

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