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Unlocking RI potential with Scalable AI and Data

Sector: Education • Location: Netherlands, Austria, Czechia, Sweden, Finland, United Kingdom, Germany, Switzerland, Italy, Greece, Portugal, Türkiye, Spain

Source: EU Funding & Tenders Portal

Project
Ongoing

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 delive

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The project “Unlocking RI potential with Scalable AI and Data” is an infrastructure initiative in the Education sector, located in Netherlands, Austria, Czechia, Sweden, Finland, United Kingdom, Germany, Switzerland, Italy, Greece, Portugal, Türkiye, Spain. Taiyo aggregates data on it from EU Funding & Tenders Portal.

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ongoing

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Description

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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100%

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