Ensuring that data is available, accessible, and fit for purpose is fundamental to Europe’s ability to develop AI and data-driven applications and strengthen its digital sovereignty. Therefore, this direction focuses on the capabilities and mechanisms required to generate, discover, access, share, reuse and continuously improve high-quality data across sectors and ecosystems. Key priorities include:
- Expanding data generation capabilities, including sensing, experimentation, simulation and synthetic data generation, to address data gaps and support emerging AI and data-intensive applications.
- Improving data discoverability, access, sharing and reuse across sectors, while ensuring trust in data provenance, quality and conditions of use
- Standardising and automating data capture and collection, improving interoperability, consistency and efficiency across heterogeneous sources and environments.
- Collaborative data quality and trustworthy information, advancing approaches for managing, assessing and continuously improving data quality across distributed data ecosystems, including provenance, lineage and fitness-for-purpose.