EGU21-15148
https://doi.org/10.5194/egusphere-egu21-15148
EGU General Assembly 2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Teams Win: The European Datacube Federation

Peter Baumann
Peter Baumann
  • Jacobs University, Bremen, Germany (p.baumann@jacobs-university.de)

Collaboration requires some minimum of common understanding, in the case of Earth data in particular common principles making data interchangeable, comparable, and combinable. Open standards help here; in case of Big Earth Data specifically the OGC/ISO Coverages standard. This unifying framework establishes a common framework in particular for regular and irregular spatio-temporal datacubes. Services grounding on such common understanding have proven more uniform to access and handle, implementing a principle of "minimal surprise" for users visiting different portals while using their favourite clients. Data combination and fusion benefits from canonical metadata allowing automatic alignment, e.g, between 2D DEMs, 3D satellite image time series, 4D atmospheric data, etc.

The EarthServer datacube federation s showing the way towards unleashing in full the potential of pixels for supporting the UN Sustainable Development Goals, local governance, and also businesses. EarthServer is an open, free, transparent, and democratic network of data centers offering dozens of Petabytes of a critical variety, such as radar and optical Copernicus data, atmospheric data, elevation data, and thematic cubes like global sea ice. Data centers like DIASs and CODE-DE, research organizations, companies, and agencies have teamed up in EarthServer. Strictly based on the open OGC standards, an ecosystem of data has been established that is available to users as a single pool, without the need for any coding skills (such as python). A specific unique capability is location-transparency: clients can fire their query against any of the mebers, and the federation nodes will figure out the optimal work distribution irrespective of data location.

The underlying datacube engine, rasdaman, enables all datacube access, analytics, and federation. Query evaluation is optimized automatically applying highly efficient intelligent, rule-based methods in homogeneous and heterogeneous mashups, up to satellite on-board deployments as done in the ORBiDANSe project. Users perceive one single, common information space accessible through a wide spectrum of open-source and proprietary clients.

In our talk we present technology, services, and governance of this unique line-up of data centers. A demo will show distributed datacube fusion live.

 

How to cite: Baumann, P.: Teams Win: The European Datacube Federation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15148, https://doi.org/10.5194/egusphere-egu21-15148, 2021.