The presentation delivered by Ákos Tényi, PhD revealed that according to estimates, the amount of data created by the public, private and business sectors is expected to increase fivefold between 2018 and 2025. A fundamental problem is, however, that nowadays significant part of usable datasets are created in isolation and stored in data silos, with restricted legislatively restricted access for the purpose of joint utilization of personal data (e.g. GDPR). The workshop introduced the possibilities of federated, privacy-preserving access to separately managed sensitive data through the use of machine learning algorithms and AI models and their validation.