  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.
