FORTH is already collaborating with Oracle Labs Switzerland for enabling data partitioning mechanisms for query answering and is a key partner in a COST action proposal focusing among others on data management for PGs.

TALE will focus on schema-based data partitioning for big data, exploring summary-based partitioning and hierarchical schemas for improving query answering efficiency. Further, summaries will be exploited as materialized views for further speeding-up query answering. The findings will be integrated within an online, community-driven resource (e.g., GitHub repository of data science notebooks and tutorials). This will also result in the identification of important unmet needs, which will be translated in a unified view of promising research directions towards a system architecture and techniques that could overcome them.