A foundation for spatial data warehouses on the Semantic Web

Article type: Research Article

Authors: Gür, Nurefşan^{a; b; *} | Pedersen, Torben Bach^a | Zimányi, Esteban^b | Hose, Katja^a

Affiliations: [a] Center for Data Intensive Systems, Aalborg University, Selma Lagerlöfsvej 300, DK-9220 Aalborg Ø, Denmark. E-mails: [email protected], [email protected], [email protected] | [b] Department of Computer and Decision Engineering, Université Libre de Bruxelles, Avenue F. D. Roosevelt 50, B-1050 Brussels, Belgium. E-mails: [email protected], [email protected]

Correspondence: [*] Corresponding author. E-mail: [email protected].

Abstract: Large volumes of geospatial data are being published on the Semantic Web (SW), yielding a need for advanced analysis of such data. However, existing SW technologies only support advanced analytical concepts such as multidimensional (MD) data warehouses and Online Analytical Processing (OLAP) over non-spatial SW data. To remedy this need, this paper presents the QB4SOLAP vocabulary, which supports spatially enhanced MD data cubes over RDF data. The paper also defines a number of Spatial OLAP (SOLAP) operators over QB4SOLAP cubes and provides algorithms for generating spatially extended SPARQL queries from the SOLAP operators. The proposals are validated by applying them to a realistic use case.

Keywords: Spatial OLAP, spatial data, multidimensional data, data modelling, RDF, SPARQL

DOI: 10.3233/SW-170281

Journal: Semantic Web, vol. 9, no. 5, pp. 557-587, 2018