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Geo data classically are categorized into vector, raster, and meta data. The latter category receives plentiful attention by the Web research community; vector data are considered to some extent, but raster data, contributing the largest data volumes, are neglected hitherto. Hence, today only on metadata level service offerings can only be consumed in a semantically adequate manner, while requests addressing the contents of raster sets cannot be done at all or only through APIs. In the end, they lack automatic contents discovery, service chaining, as well as flexible retrieval and analysis. The Open GeoSpatial Consortium (OGC) Web Coverage Processing Service (WCPS) standard defines a raster retrieval language suitable for ad-hoc navigation, extraction, and analysis of large, multi-dimensional data sets. Due to its formalized semantics definition it is suitable for reasoning and automatic service chaining. Based on real-life use cases drawn from remote sensing, oceanography, geophysics, and climate modeling we discuss the language concept, design rationales, and features like discoverability, declarativeness, safe evaluation, and optimizability. Further, the reference implementation stack, which will be released in open source, is detailed.
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