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.
36 Months da 01/03/2025 a 29/02/2028
General aims
1. Co-design and develop an RI ‘Data Exploitation Platform’ (DEP) technology prototype.
2. Increase the AI-based data exploitation and data mining capacity of RIs with AI frameworks and AI models integrated into the DEP framework.
3. Demonstrate and validate the practical application of the AI-powered DEPs through RIs, Data Spaces and use cases that contribute to the EU policy objectives in environmental and health sciences.
4. Increase the industry and university collaborations of data-intensive RIs in the area of scalable AI applications.
5. Facilitate the uptake and use of AI technologies for scalable RI data analysis through competence centres, consultancy events and training.
6. Explore sustainable operation models for large-scale DEP offerings through joint partnerships among RIs, e-infrastructures and commercial entities.
CMCC role
In RI-SCALE CMCC is involved in:
T1.1: Project Coordination and Technical Management
T2.3: Data Discovery and Data popularity services integration (LEAD):
T2.4: Data holdings integration
T3.3: AI for environmental science (LEAD)
T5.1: Requirement consolidation and technical coordination
T5.2: Scientific validations
T6.4: Capacity building through a dedicated Competence Centre
Moreover, within task 3.3 CMCC is leading a case titled “Smart detection of anomalies in climate data usage (ENES)”
Expected results
1. DEP technology prototype with operation guidelines
2. AI frameworks and trained AI models for scalable analytics in DEPs
3. DEP deployments for environmental and health sciences with interoperability to Data Spaces, EOSC EU Nods.
4. Engagement Framework targeting SMEs and universities in the area of scalable AI analytics
5. Competence Centre on scalable AI for RI and e-Infrastructure communities
Partners
BIOBANKS AND BIOMOLECULAR RESOURCES RESEARCH INFRASTRUCTURE CONSORTIUM (BBMRI-ERIC) (BBMRI-ERIC).
Comprimato Systems s.r.o. (COM)
EISCAT SCIENTIFIC ASSOCIATION (EISCAT)
EURO-BIOIMAGING ERIC (Euro-BioImaging),
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS (ECMWF)
EUROPEAN MOLECULAR BIOLOGY LABORATORY (EMBL)
ORGANISATION EUROPEENNE POUR LA RECHERCHE NUCLEAIRE (CERN),
FORSCHUNGSZENTRUM JULICH GMBH (Juelich),
FRAGMENTIX STORAGE SOLUTIONS GMBH (FRA),
DEUTSCHES KLIMARECHENZENTRUM GMBH (DKRZ),
HYPERMETEO SRL (HYP),
ISTITUTO NAZIONALE DI FISICA NUCLEARE (INFN),
JNP STRATIGIKI KAI EPICHIRISIAKI SYMVOULEFTIKI IKE (JNP),
KUNGLIGA TEKNISKA HOEGSKOLAN (KTH),
LULEA TEKNISKA UNIVERSITET (LTU),
Masarykova univerzita (MU),
MASARYKUV ONKOLOGICKY USTAV (MMCI),
MEDIZINISCHE UNIVERSITAT GRAZ (MUG),
NATIONAL INFRASTRUCTURES FOR RESEARCH AND TECHNOLOGY (GRNET),
NEURASPACE SA (NEU),
T-SYSTEMS INTERNATIONAL GMBH (T-Systems),
TECHNISCHE UNIVERSITAET WIEN (TUWien),
TURKIYE BILIMSEL VE TEKNOLOJIK ARASTIRMA KURUMU (TUBITAK),
UNITED KINGDOM RESEARCH AND INNOVATION (UKRI),
UNIVERSITAT POLITECNICA DE VALENCIA (UPV),
UNIVERSITA DEGLI STUDI DI TRENTO (UNITN)