SOWL: A Framework for Handling Spatio-temporal Information in OWL 2.0

Abstract

The Semantic Web extends existing World Wide Web (WWW) with formal machine readable semantics that enable better understanding of Web content by both, people and machines. The OWL ontology language forms the basis of Semantic Web technologies by providing the means for defining formal semantics of concepts and their properties. Semantic Web standards also provide with the formalism and mechanisms for supporting reasoning and querying of information in OWL.Qualitative spatial and temporal information is supported using sets of SWRL rules and OWL axioms offering a sound, complete and tractable reasoning procedure based on path consistency applying on the supported sets of relations. Polynomial time complexity of spatio-temporal reasoning is achieved by restricting the supported sets of relations to "tractable" sets. Furthermore, rules enforcing cardinality constrains on dynamic properties are defined. Reasoning support for qualitative information and restriction checking is also introduced in this work for increasing expressive power of existing approaches. Building-upon existing Semantic Web standards and on the idea of integrating reasoning support into the proposed representation are important advantages of the proposed approach.Query support in SOWL is realized with two languages referred to as TOQL and SOWL Query Language. Both, are high-level query languages, independent from the underlying SOWL representation so that, the user need not be familiar with the peculiarities of the ontological spatio-temporal representation in SOWL (i.e., the 4D-fluents or the N-ary approach). TOQL handles ontologies almost like relational databases and relies on the idea of extending SQL with spatiotemporal operators. Respectively, SOWL builds-upon SPARQL, the current standard of the Semantic Web, which is also extended with a set of spatio-temporal operators similar to those introduced in TOQL.

Imposing Restrictions over Temporal Properties in OWL: A Rule-Based Approach

“…Properties having a temporal dimension are called f luent properties and connect instances of class TimeSlice (as in Fig.1(b)). In [1], the 4D-fluents 1 http://www.w3.org/TR/owl-time 2 http://www.w3.org/TR/swbp-n-aryRelations representation was enhanced with qualitative temporal relations (i.e., relations holding between time intervals whose starting and ending points are not specified). A temporal relation can be one of the 13 pairwise disjoint Allen's relations.…”

“…In our previous work [1], we extended this approach with qualitative (in addition to quantitative) temporal expressions, allowing for the representation of temporal intervals with unknown endpoints by means of their relation (e.g., "before", "after") to other time intervals, or alternatively, by translating relations between temporal intervals into equivalent relations between time instants [2]. Property semantics such as cardinality restrictions or property constraints are not handled.…”

Temporal and Spatial Expansion of Urban LOD for Solving Illegally Parked Bicycles in Tokyo

“…SOWL [13] is a spatio-temporal data model for Web Ontology Language. In SOWL, temporal information is modeled based on the 4D-fluents approach [14] and spatial information is modeled based on region connection calculus and cone-shaped directional relations.…”

MRQUTER : A Parallel Qualitative Temporal Reasoner Using MapReduce Framework

“…반면에, 표준 질의 언어인 SPARQL을 확장한 시간 질의 표현 연구들로는 T-SPARQL [6], stSPARQL [4] 한편, 기존의 시간 순서 관계 표현법들은 주로 Kautz [7] 의 점 대수(point algebra) 이론이나 Allen [8] 본 논문에서는 그동안 GQR [9], SOWL [10], CHRONOS [11,12] Relationships between Two Events …”