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Unlocking RI potential with Scalable AI and Data

Project description

Boosting data and AI for science

Scientific discoveries increasingly rely on data and AI. Research infrastructures (RIs) generate huge amounts of complex data, but managing, analysing and using this information is becoming a major challenge. Scientists often lack the large-scale tools and expertise needed to process data quickly and effectively. With this in mind, the EU-funded RI-SCALE project is tackling this issue by creating scalable Data Exploitation Platforms. These platforms will combine scientific data with preconfigured AI tools and powerful computing resources, unlocking their full potential. Working with four RIs (ENES, EISCAT, BBMRI and Euro-BioImaging), RI-SCALE will test the technology in environmental and life sciences. It will also foster collaborations to help more RIs adopt these innovations.

Objective

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.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-INFRA-2024-TECH-01

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Coordinator

STICHTING EGI
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 930 625,00
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 930 625,00

Participants (27)

Partners (1)

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