Representing Time and Space for the Semantic Web

TLDR

Representation of temporal and spatial information for the Semantic Web often relies on qualitative terms because precise dates or coordinates are not always available, and this study is the first to combine qualitative and quantitative information in such representations. The authors propose several temporal and spatial representations using OWL properties and SWRL rules. All representations are fully compliant with Semantic Web standards, are applied to RCC5 and RCC8 topological relations, and are evaluated with multiple reasoners and SPARQL queries. Experimental results reveal large differences in reasoning performance across representations and reasoners, and demonstrate that extracting qualitative relations from quantitative ones improves query performance.

Abstract

Representation of temporal and spatial information for the Semantic Web often involves qualitative defined information (i.e., information described using natural language terms such as “before” or “overlaps”) since precise dates or coordinates are not always available. This work proposes several temporal representations for time points and intervals and spatial topological representations in ontologies by means of OWL properties and reasoning rules in SWRL. All representations are fully compliant with existing Semantic Web standards and W3C recommendations. Although qualitative representations for temporal interval and point relations and spatial topological relations exist, this is the first work proposing representations combining qualitative and quantitative information for the Semantic Web. In addition to this, several existing and proposed approaches are compared using different reasoners and experimental results are presented in detail. The proposed approach is applied to topological relations (RCC5 and RCC8) supporting both qualitative and quantitative (i.e., using coordinates) spatial relations. Experimental results illustrate that reasoning performance differs greatly between different representations and reasoners. To the best of our knowledge, this is the first such experimental evaluation of both qualitative and quantitative Semantic Web temporal and spatial representations. In addition to the above, querying performance using SPARQL is evaluated. Evaluation results demonstrate that extracting qualitative relations from quantitative representations using reasoning rules and querying qualitative relations instead of directly querying quantitative representations increases performance at query time.