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About DaFab

DaFab's vision is to break silos between different types of data and metadata handling and enable better Earth Observation (EO) data exploitation and easier value extraction. Towards that goal, DaFab is pushing the boundaries of various state-of-the-art components. Firstly, DaFab is seeking a cost-effective AI solution to process the Copernicus data set for metadata generation using a more recent non-Von Neuman hardware architecture for AI (IPU, neuromorphic) Computing approach. Secondly, DaFab seeks interoperability among multiple data silos by structuring generated metadata similar to the semantic web. Thirdly, the project seeks to provide a unified searchable catalog that fuses multiple existing datasets. Finally, DaFab provides mechanisms to abstract the decision between moving computation to a data site and moving data to a compute site. DaFab's flood prevention/prediction and crop prediction use cases are aligned with the foreseen market evolution. Participating partners in the DaFab project: - Datadirect Networks France - GCORE - Foundation for Research and Technology - Hellas - LuxProvide - European Center for Medium-Range Weather forecasts - Jozef Stefan Institute - Ljubljana - CERN - Thales Alenia Space Funded by the European Union.

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