Baumann P., Hirschorn E., Maso J., Merticariu V., Misev D. (2018) All in One: Encoding spatio-temporal big data in XML, JSON, and RDF without information loss. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017. 2018-January: 1-10.LinkDoi: 10.1109/BigData.2017.8258326
With the unprecedented availability of continuously observed and generated data there is a likewise unprecedented potential for new and timely insights; yet, benefits are not fully leveraged as of today. The plethora of formats in combination with heterogeneous services remains is an obstacle-e.g., image services prefer binary formats, SPARQL endpoints like to think in RDF triples, and browsers integrate JSON data smoothly. We propose a model-based multi-encoding approach for overcoming the limitations of individual formats while still supporting their use. Concretely, this approach is being followed by the OGC Coverage Implementation Schema (CIS) standard which establishes a concrete, interoperable data model unifying n-D spatiotemporal regular and irregular grids, point clouds, and meshes. We describe how independence from data formats is achieved, in particular for three practically relevant formats-XML, JSON, and RDF-, thereby fostering integration of hitherto rather separate application domains. © 2017 IEEE.
Masó J., Zabala A., Serral I., Pons X. (2018) Remote sensing analytical geospatial operations directly in the web browser. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 42: 475-482.LinkDoi: 10.5194/isprs-archives-XLII-4-403-2018
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