Deliver the power of data cubes and ML to decision makers and data scientists.
The core mission of FAIRiCUBE is to enable players from beyond classic Earth Observation (EO) domains to provide, access, process and share gridded data an algorithms in a FAIR and TRUSTable manner.
The project’s goal is to leverage power of Machine Learning (ML) operating on multi-thematic datacubes for a broader range of governance and research institutions from diverse fields, who are at present cannot easily access and utilize these potent resources.
The objective is the creation of a FAIRiCUBE Hub, a crosscutting platform and framework for data ingestion, provision, analyses, processing and dissemination, to unleash the potential of environmental, biodiversity and climate data through dedicated European data spaces.
Our Use Cases
FAIRiCUBE use cases address EU green deal action items, focusing on urban and regional scale. The use cases are:
- Spatial and temporal assessment of neighbourhood building stock
- Biodiversity occurrence cubes
- Biodiversity and agriculture nexus
- Urban adaptation to climate change
- Drosophila Genetics