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Multidimensional array data, such as remote-sensing imagery and timeseries, climate model simulations, telescope observations, and medical images, contribute massively to virtually all science and engineering domains, and hence play a key role in 'Big Data' challenges. Pure array storage management and analytics is relatively well understood today. However, arrays in practice never come alone, but...
Data-intensive applications in e-Science require scalable solutions for storage as well as interactive tools for analysis of scientific data. It is important to be able to query the data in a storage-independent way, and to be able to obtain the results of the data-analysis incrementally (in contrast to traditional batch solutions). We use the RDF data model extended with multidimensional numeric...
We define an extended version of the Semantic Web query language SPARQL called Scientific SPARQL, SciSPARQL. It is targeted mainly at scientific computing and laboratory data management. SciSPARQL includes expressions, numeric multi-dimensional array operations, user-defined functions, aggregate functions, and function views. A prototype system translates SciSPARQL to a Datalog dialect which is extensible...
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