In scientific research, data and Research Infrastructures (RIs) play a key role by generating massive and increasingly complex datasets. However, the growing size, limited multidisciplinary accessibility, and need for specialised technical expertise hinder the optimal reuse and analysis of these valuable resources.

The “RI-SCALE: Unlocking RI potential with Scalable AI and Data” Project addresses this challenge with the aim of creating a Data Exploitation Platform" (DEP) standard.

These cloud/HPC prototypes provide a scalable environment for hosting and analysing RI data through preconfigured AI frameworks. By unlocking the potential of RI data, DEPs can act as a powerful and reproducible tool for data valorisation, maximising the value and impact of RIs and their research communities.

Four Research Infrastructures (ENES, EISCAT_3D, BBMRI, Euro-Bioimaging), two digital infrastructures (EGI and SLICES), technology providers and SMEs will participate in the design of this prototype.

The project will contribute to the full exploitation of the Research Infrastructures datasets, promoting transformational research, innovation as well as discovery in various fields.

More specifically, the benefits of achieving the project's objectives are multiple:

• The co-design and development of a prototype technology centre " Data Exploitation Platform " DEP, its software and associated operational implementation manual, will enable the RIs to expand their portfolio with better scalable services for the combined provision of computing services in electronic infrastructures.
• The integration of AI frameworks into DEP technology will provide AI models trained on big data RIs, both for Research Infrastructure operators (aiming at increasing data quality) and for Research Infrastructure users (aiming at data analysis).
• Demonstration and validation of the practical application of the DEP through RIs, Space Data Sites and use cases contributing to EU policy objectives, environmental and health sciences.
• With the increased use of data from AI applications, an increase in industrial and academic collaborations in the field of research infrastructures will be achieved.
• It will facilitate the adoption and use of AI technologies that aim to enhance the data analysis of RIs through competence centres, advisory events and Training.
• Investigation of sustainable operating models for large-scale DEP offers through joint partnerships between RIs, e-Infrastructures and commercial entities.

The main role of GRNET for the needs of the project concerns Access management technologies, which are described as follows:

• Implementation of a secure and conventional data access control system: Establish a framework for managing user access to various scientific data using advanced policy-based licensing with user roles, data sensitivity and dynamic adapters.
• Compatibility committee with external initiatives: Integration with Space Data Spaces and utilization of decentralized discovery solutions for secure and privacy-preserving access to data across platforms.
• Privacy and user control: Integration of privacy principles into the system, including user-friendly consent management, comprehensive data access control and federated token revocation mechanisms.
• Promoting sustainability of resources: Development of a credit management system that allows monitoring of resource use and cost-effective research collaboration.

GRNET will be additionally involved in the individual work packages:

• Project, ethics and data compliance management
• Co-design and integrated validation
• Maximising the impact

The project is implemented within the framework of the EU's Horizon Europe programme.