D6.2 Data sources and integration report

The objective of document D6.2 describes the work performed in Task 6.2, which focuses on acquiring, preparing, analysing, fusing and integrating the incoming datasets that support the project use cases in a horizontal manner, as well as provide the mechanisms to access and share them. In handling such large and heterogeneous datasets, techniques such as distributed compression and compressed learning can be taken into consideration for effective data management. Data mining methods such as clustering, and feature extraction will be investigated to prepare data conducting effective analysis. Distributed learning techniques such as Federated learning and representative learning approaches can then be taken into consideration for developing collaborative data integration and analysis mechanisms. Additionally, techniques of prediction with guarantees such as causal and conformal learning will be investigated.