Enabling and Connecting Interoperable FAIR digital objects

Despite significant progress in open data, code sharing, and implementation of FAIR principles, there is no automated, universal mechanism capable to "FAIR-ify" DOs across large cross-domain repositories and data spaces. RAISE-CONNECT addresses this challenge by providing AI-powered, domain-agnostic connectors that can "FAIR-ify" DOs (i.e data, code, experiments, experimental results and FDOs) and make them interoperable both within and across repositories. 
Leveraging existing EOSC-RAISE tools, it offers researchers and other stakeholders and entry point to access, share and process FDOs with no effort. RAISE-CONNECT establishes an architectural framework for seamless creation, transformation and integration of FDOs. At its core, it introduces an automated "FAIR-ification" service to continously enhace DOs by searching across repositories for missing FAIR elements. This ensures that every DO can be transformed into an FDO that is discoverable, interoperable and reusable. To maximise usability and uptake, RAISE-CONNECT let users interact with DOs through natural language prompts, leveraging LLMs: users can "ask" for datasets, scripts, compare results, all without technical overhead. A model of Common Repository Connector acts as "template" abstraction layer to bridge heterogeneous repositories, while different specific implementatitons of the it will be developed for well-known Data Spaces and DO repositories. The FAIR-ification Engine provides continous and on-demand FAIR-ness assessment and transformation. Complex workflows can be initiated by natural language  queries or graphical tools. By removing technical barriers nd enforcing compliance, provenance, and reproducibility by design, it turns open science from a policy into an everyday practice for researchers, innovators, and data providers. RAISE-CONNECT will be validated on more than 12 real-life data, code, and experiment repositories, ensuring its applicability across diverse domains.