Qualitative Spatial Reasoning Using Topological and Directional Information in OWL

We investigate on potential improvements to reasoning approaches designed for spatial information in OWL. First, we introduce CHOROS, a qualitative spatial reasoning engine for ontologies in OWL. Building upon Pellet Spatial, CHOROS supports consistency checking and query answering for spatial information using Region-Connection Calculus (RCC), but also using the Cone-Shaped Directional (CSD) logic formalism. It works with all RCC and CSD relations in combination with standard RDF/OWL semantic relations in an OWL ontology and can answer SPARQL queries with spatial and non-spatial relations. We also present SOWL, a spatial reasoner for both relation calculi implemented in SWRL and runs under Pellet. We discuss and evaluate possible optimizations of CHOROS and compare its performance with that of SOWL. The experimental results demonstrate that CHOROS runs significantly faster than its respective SWRL implementation in most cases.