In Geo service terminology, coverages represent spatio-temporally varying phenomena, such as sensor, image, simulation, and statistics data; incidentally, these typically are prime Big Data contributors in practice. The OGC unified coverage model encompasses regular and irregular grids, point clouds, and general meshes. As opposed to the (abstract) coverage model of ISO 19123 on which it is based, the (concrete) OGC coverage and service model establishes verifiable nteroperability. The OGC Web Coverage Service (WCS) comprises a modular suite for accessing large coverage assets. WCS Core provides simple data subsetting whereas extensions add optional service facets up to ad-hoc filtering and processing.
By separating coverage data and service model, any service - such as WMS, WFS, SOS and WPS - can provide and consume coverages in addition to WCS. Generally, the WCS suite is appreciated by implementers due to its clear structuring and concise conformance testing, down to pixel/voxel level. Many WCS implementations are available today, such as rasdaman which has proven efficient on 130+ TB datacubes.
In this course, we present the OGC coverage data and service model with an emphasis on practical aspects and illustrate how high-performance, scalable implementations can be built on them. Presentation will make use of online available demo services allowing participants to follow and recapitulate the topics addressed.
The presenter is editor of the OGC coverage standards, the OGC timeseries coordinate systems, and Principal Architect of the rasdaman Big Array Engine proven on 130+ TB datacubes and parallelization across 1,000+ cloud nodes.