Professor of Machine Learning,
During this session, we will explore potential and existing models of collaboration/federation in cross-border initiatives that can be applied in a practical / realistic way to foster data driven innovation at European level, and make this innovation available and accessible to all actors in the European data landscape, in particular SMEs and Start-ups, as it is aimed in the project EUHubs4Data. Starting from a general view on needs, benefits and models of a federation, we will focus on specific and concrete aspects such as governance and structure, a federated catalogue / offer (including data sources, data governance, delivery of joint services and a common training programme), potential legal or organisational barriers, etc. We will also count with the experience of actors involved in existing and different types of federation and networks.
The expected outcome from this workshop aims to be a set of recommendations about the best options for each of the aspects considered, that could contribute, in the scope of EUHubs4Data project, to the establishment of federated network of data-driven experimentation facilities in Europe (with special focus on AI and Data service innovation development and experimentation), find synergies, share knowledge and assets, and let small and medium size actors on each region to benefit from latest European advances on those fields.