rasdaman newsletter 03/2026
Satellites Deliver Answers Instead of Raw Data – rasdaman Invited Keynote in USA
The renowned Summit on Big Data, Data Science & Machine Learning is held again, this year in Orlando in the US. Every year, key innovations get presented by academicians, researchers and industry professionals. This year, Prof. Dr. Peter Baumann, Principal Architect of rasdaman, has been invited as a keynote speaker to share his insights on AI on Big Data.
In his talk, “Herding Cats: How to Federate EO Satellites and Big Data Archives”, he is going to address one of today’s greatest data challenges: the massive daily streams generated by an armada of satellites, which cannot be analysed as intended. All the satellites commissioned by the European Space Agency, NASA, the Japan Aerospace Agency, etc., plus all the commercial Earth observation providers, like Planet, Maxar, etc., together make EO analysis like "drinking from a fire hose". Downloading and analyzing these volumes on the ground is increasingly impractical, while data complexity limits accessibility for non-experts.
In the SkyFed project, satellites are made intelligent so as to answer questions, rather than firing down raw data. For doing so, satellites build and maintain space/time datacubes on board.
Such concise answering is not only better Quality of Service, but reduces the data flood transmission by orders of magnitude, thus allowing more questions to be answered at the same time. Queries ultimately can be asked in natural language through AI, or using interoperable open standard like the OGC WCPS geo datacube query language. Additionally, these in-orbit datacubes get federated with large-scale ground services providing weather datacubes, historical satellite image time series, and further resources.
The underlying rasdaman federated Big Datacube Analytics platform integrates AI, distributed data fusion, and cloud/edge computing based on open standards, paving the way towards a globally integrated, query-driven data ecosystem.
This research is part of the FAIRgeo and SkyFed projectis co-funded by EU EFRE and the State of Bremen.
More information: Summit on Big Data, Data Science and Machine Learning, FAIRgeo, SkyFed