001047384 001__ 1047384
001047384 005__ 20251027202212.0
001047384 0247_ $$2CORDIS$$aG:(EU-Grant)101131841$$d101131841
001047384 0247_ $$2CORDIS$$aG:(EU-Call)HORIZON-EUSPA-2022-SPACE$$dHORIZON-EUSPA-2022-SPACE
001047384 0247_ $$2originalID$$acorda_____he::101131841
001047384 0247_ $$2doi$$a10.3030/101131841
001047384 035__ $$aG:(EU-Grant)101131841
001047384 150__ $$aEarth Observation & Weather Data Federation with AI Embeddings$$bAI compressing for Earth observation and weather data exchange$$y2024-01-01 - 2026-12-31
001047384 371__ $$0P:(DE-Juel1)185654$$aKesselheim, Stefan$$s20240101$$t20261231
001047384 450__ $$aEmbed2Scale$$wd$$y2024-01-01 - 2026-12-31
001047384 5101_ $$0I:(DE-588b)5098525-5$$aEuropean Union$$bCORDIS
001047384 680__ $$aThe Copernicus programme, weather models, and Global Navigation Satellite Systems (GNSS) provide extensive geospatial data applicable to various scientific sectors. However, the volume of this data makes it impractical for a single platform to host. As a result, service providers face challenges in accessing data from different archives due to cost constraints. The EU-funded Embed2Scale project will address this issue by leveraging AI-based data compression techniques to facilitate efficient data exchange. The project will investigate deep neural network training methods and introduce innovations in data management and portability. The outcome will be groundbreaking research in AI-driven data compression, leading to more accessible and efficient access to earth observation and weather data.
001047384 8564_ $$uhttps://cordis.europa.eu/project/id/101131841$$yHomepage
001047384 909CO $$ooai:juser.fz-juelich.de:1047384$$pauthority:GRANT$$pauthority
001047384 980__ $$aG
001047384 980__ $$aAUTHORITY
001047384 980__ $$aCORDIS