|Funding Organization:||European Commission|
|Funding Programme:||Horizon Europe|
|Funding Instrument:||Innovation Action|
November 1, 2022
|Total Budget:||6,953,400.00 EUR|
|ITI Budget:||600,000.00 EUR|
LAGO (LESSEN DATA ACCESS AND GOVERNANCE OBSTACLES) will deliver the foundation for a trusted EU FTC Research Data Ecosystem (RDE) to address the so-called “Data Issue” in the FCT research landscape, i.e., the lack of domain-specific data in sufficient quality and quantity to enable appropriate training and testing of the developed methods, platforms and tools. LAGO will be instrumental in identifying common barriers and subsequently providing the structural, governance and technical foundations to foster and innovate data-oriented research collaboration among LEAs, security practitioners, relevant EU agencies, academic and industry researchers, policy makers and regulators. For this purpose, LAGO will develop an evidence-based and validated multi-actor Reference Architecture for the FCT RDE for these actors to deposit, share and co-create data and tools for FCT research purposes based on common rules, protocols, standards and instruments in a trusted and secured environment. The envisaged Reference Architecture and accompanying governance framework will be based on the design principles of decentralisation, data sovereignty, data quality, openness, transparency and trust and comply with EU values and principles on data protection, privacy and ethics. The Reference Architecture will be accompanied by a TRL-7 Reference Implementation of added-value technological tools to ensure practical realisation of the Reference Architecture as multiple data spaces and across the full range of concrete usage scenarios. A Roadmap will finally provide the consolidated rules, conditions and considerations for the actual deployment of the EU FCT RDE. The ultimate ambition of LAGO is to go beyond the creation of a common repository in order to innovate the FCT data-oriented research sphere by creation the crucial foundations for the sustainable, safe and trusted creation, co-creation, sharing and maintenance of training and testing datasets for the FCT research domain.