Volume XLI-B4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 691-699, 2016
https://doi.org/10.5194/isprs-archives-XLI-B4-691-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B4, 691-699, 2016
https://doi.org/10.5194/isprs-archives-XLI-B4-691-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  14 Jun 2016

14 Jun 2016

STANDARDS-BASED SERVICES FOR BIG SPATIO-TEMPORAL DATA

P. Baumann1, V. Merticariu2, A. Dumitru2, and D. Misev2 P. Baumann et al.
  • 1Jacobs University, Bremen, Germany
  • 2rasdaman GmbH, Bremen, Germany

Keywords: Big Data, datacubes, coverages, WCS, WCPS, standards, OGC, rasdaman

Abstract. With the unprecedented availability of continuously updated measured and generated data there is an immense potential for getting new and timely insights – yet, the value is not fully leveraged as of today. The quest is up for high-level service interfaces for dissecting datasets and rejoining them with other datasets – ultimately, to allow users to ask "any question, anytime, on any size" enabling them to "build their own product on the go".

With OGC Coverages, a concrete, interoperable data model has been established which unifies n-D spatio-temporal regular and irregular grids, point clouds, and meshes. The Web Coverage Service (WCS) suite provides versatile streamlined coverage functionality ranging from simple access to flexible spatio-temporal analytics. Flexibility and scalability of the WCS suite has been demonstrated in practice through massive services run by large-scale data centers. We present the current status in OGC Coverage data and service models, contrast them to related work, and describe a scalable implementation based on the rasdaman array engine.