Big Spatio-Temporal Datacubes on Steroids ...and Standards
With the advent of the massive deluge in Earth data, serving them to diverse communities is increasingly promising and challenging alike. A useful abstraction for spatio-temporal raster data (and beyond) is the coverage data model, as standardized by ISO, OGC, and INSPIRE. Rather than zillions of individual image files it provides spatio-temporal "datacubes" for simple, efficient handling through the corresponding service model, the Web Coverage Service (WCS) with its Web Coverage Processing Service (WCPS) geo analytics language - "one cube tells more than a million images".
Open-source rasdaman ("raster data manager") is the official reference implementation of both OGC and INSPIRE WCS. It supports easy incremental construction and maintenance of spatio-temporal datacubes, based on the OGC WCS-T standard. Retrieval may use WMS for visual navigation, WCS for data extraction and download, and WCPS for massive server-side processing. On server side, adaptive data partitioning and "tile streaming" processing enables fast query responses. In July 2016, US magazine CIO Review has included rasdaman in its top 100 Big Data technologies list.
In this talk we present coverages in terms of concepts, implementation, and large-scale application. Live demos underpin the talk, using publicly accessible sites where the audience can replay and modify the examples. Being editor of the OGC and ISO coverage standard the presenter can give first-hands insights and answers, such as about the new generalized grid model for coverages (CIS 1.1) which OGC has adopted in Fall 2016 as well as the newly adopted INSPIRE-WCS. This is an excellent opportunity to learn about the state of the art and standards in an open, free-of-cost setup.