Spatio-Temporal Datacubes at Your Fingertips

EarthServer was one of the most influential project series delivering next-generation Big Earth Data services. It has pinted new directions for flexible, scalable EO services based on innovative NoSQL technology. Researchers from Europe, the US, and Australia have teamed up to rigorously materialize the concept of the datacube. Such a datacube may have spatial and temporal dimensions (such as an x/y/t satellite image time series) and may unite an unlimited number of scenes. Independently from whatever efficient data structuring a server net¬work may perform internally, users will always see just a few datacubes they can slice and dice.

EarthServer has established client and server technology for such spatio-temporal datacubes. The underlying scalable array engine, rasdaman, en¬ables direct interaction, including 3-D visualization, what-if scenarios, common Earth Observation data processing, and general analytics. Services exclusively rely on the open OGC "Big Geo Data" standards suite, the Web Coverage Service (WCS). Phase 1 of EarthServer has advanced scalable array database technology into 100+ TB services; in Phase 2, more than 2.5 Petabyte datacubes have been built for ad-hoc extraction, processing, and fusion. In addition, Jacobs University's PlanetServer service is one of the key European portals offering datacubes on Planetary bodies like Mars, Moon, and Vesta.

Today, the EarthServer datacube federation unites a 2-digit number of large-scale Earth data providers with about 100 PB of seamlessly coupled offerings, based on the unique location-transparent federation technology of rasdaman.

However, EarthServer has not only used, but also shaped several Big Data standards. This includes OGC coverage data and service standards, INSPIRE WCS, and the ISO SQL/MDA (Multi-Dimensional Arrays) standard.

Both European Commission and reviewers observed "proven evidence" that rasdaman does "significantly transform [how to] access and use data" and "with no doubt has been shaping the Big Earth Data landscape".

Planetary-scale federation of datacubes


River discharge timeseries with rasdaman


Climate indicators with rasdaman


Landsat-8 satellite imagery with rasdaman


Glasgow subsurface modeling with rasdaman


Planetary sciene services on Mars, Moon, and Vesta with rasdaman

Demonstration of planetary-scale rasdaman federation: determining global heavy rain risk areas from ERA climate data at ECMWF/UK and Landsat8 data at NCI / Australia