Abstract
Large volumes of spatial data and multidimensional data are being published on the Semantic Web, which has led to new opportunities for advanced analysis, such as Spatial Online Analytical Processing (SOLAP). The RDF Data Cube (QB) and QB4OLAP vocabularies have been widely used for annotating and publishing statistical and multidimensional RDF data. Although such statistical data sets might have spatial information, such as coordinates, the lack of spatial semantics and spatial multidimensional concepts in QB4OLAP and QB prevents users from employing SOLAP queries over spatial data using SPARQL. The QB4SOLAP vocabulary, on the other hand, fully supports annotating spatial and multidimensional data on the Semantic Web and enables users to query endpoints with SOLAP operators in SPARQL. To bridge the gap between QB/QB4OLAP and QB4SOLAP, we propose an RDF2SOLAP enrichment model that automatically annotates spatial multidimensional concepts with QB4SOLAP and in doing so enables SOLAP on existing QB and QB4OLAP data on the Semantic Web. Furthermore, we present and evaluate a wide range of enrichment algorithms and apply them on a non-trivial real-world use case involving governmental open data with complex geometry types.
Highlights
E Data warehouses (DWs) and Online Analytical ProR cessing (OLAP) tools and queries are widely used for interactive data analysis
Data examples, which are depicted as graphs, and annotated both with QB4OLAP and QB4SOLAP vocabularies, identifying the required spatial MD metadata and concepts for Spatial Online Analytical Processing (SOLAP) analysis based on the given comparison. * Hierarchical enrichment algorithms for (1) detecting topological relations at hierarchy steps with direct links between the level members; and
The alternative would be to export the spatial RDF data to relational format, do the enrichment spatial analysis, which is called Turfjs6. This way, we with relational/geographical information systems (GIS) tools and perform the SOLAP on can ensure that RDF2SOLAP can be used on top of the resulting relational data, loosing all the advanany triple store since the Javascript library provides us tages of having the data in RDF in the first place
Summary
E Data warehouses (DWs) and Online Analytical ProR cessing (OLAP) tools and queries are widely used for interactive data analysis. Spatial data cubes can contain spatial a nominal reference to places and areas, e.g., parish measures, which can be aggregated with spatial funcname This does not allow for applying spatial opertions. In To emerge this need the QB4SOLAP vocabulary was addition, by using geometric attributes of level mem- proposed [13], which allows modeling the data cubes bers, topological relations between the levels, and lev- fully with both multidimensional and spatial concepts els and facts can be specified implicitly. P and data warehouses have emerged [50], there is still a lack of common standards to model and publish (geo)semantic cubes on the SW [15]
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