000362542 001__ 362542
000362542 005__ 20251029173127.0
000362542 0247_ $$2CORDIS$$aG:(EU-Grant)101131841$$d101131841
000362542 0247_ $$2CORDIS$$aG:(EU-Call)HORIZON-EUSPA-2022-SPACE$$dHORIZON-EUSPA-2022-SPACE
000362542 0247_ $$2originalID$$acorda_____he::101131841
000362542 0247_ $$2doi$$a10.3030/101131841
000362542 035__ $$aG:(EU-Grant)101131841
000362542 150__ $$aEarth Observation & Weather Data Federation with AI Embeddings$$bAI compressing for Earth observation and weather data exchange$$y2024-01-01 - 2026-12-31
000362542 371__ $$0P:(DE-Juel1)185654$$aKesselheim, Stefan$$s20240101$$t20261231
000362542 450__ $$aEmbed2Scale$$wd$$y2024-01-01 - 2026-12-31
000362542 5101_ $$0I:(DE-588b)5098525-5$$aEuropean Union$$bCORDIS
000362542 680__ $$aThe Copernicus programme, weather models, and Global Navigation Satellite Systems (GNSS) provide extensive geospatial data applicable to various scientific sectors. However, the volume of this data makes it impractical for a single platform to host. As a result, service providers face challenges in accessing data from different archives due to cost constraints. The EU-funded Embed2Scale project will address this issue by leveraging AI-based data compression techniques to facilitate efficient data exchange. The project will investigate deep neural network training methods and introduce innovations in data management and portability. The outcome will be groundbreaking research in AI-driven data compression, leading to more accessible and efficient access to earth observation and weather data.
000362542 8564_ $$uhttps://cordis.europa.eu/project/id/101131841$$yHomepage
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000362542 980__ $$aCORDIS