Abstract
In order to support the processing of qualitative spatial queries, spatial knowledge must be represented in a way that machines can make use of it. Ontologies typically represent thematic knowledge. Enhancing them with spatial knowledge is still a challenge. In this article, an implementation of the Region Connection Calculus (RCC) in the Web Ontology Language (OWL), augmented by DL-safe SWRL rules, is used to represent spatio-thematic knowledge. This involves partially ordered partitions, which are implemented by nominals and functional roles. Accordingly, a spatial division into administrative regions, rather than, for instance, a metric system, is used as a frame of reference for evaluating closeness. Hence, closeness is evaluated purely according to qualitative criteria. Colloquial descriptions typically involve qualitative concepts. The approach presented here is thus expected to align better with the way human beings deal with closeness than does a quantitative approach. To illustrate the approach, it is applied to the retrieval of documents from the database of the Datacenter Nature and Landscape (DNL).
Highlights
Fueled by a joint initiative of research institutes and industrial organizations towards the Semantic Web, knowledge representation has regained considerable attention through the last decade [1]
In this paper an implementation of the Region Connection Calculus (RCC) in the Web Ontology Language (OWL) augmented by Description Logics (DLs)-safe rules is used in order to represent spatio-thematic knowledge
Since colloquial descriptions typically involve qualitative concepts, the presented approach is expected to align better with the way human beings deal with closeness than a quantitative approach
Summary
Fueled by a joint initiative of research institutes and industrial organizations towards the Semantic Web, knowledge representation has regained considerable attention through the last decade [1]. The initiative was committed to advance Description Logics (DLs), f.k.a. terminological systems, as a means for capturing the terminological and assertional knowledge of a domain and for inferring new knowledge from existing. This kind of knowledge has been (and continues to be) made available by so-called ontologies [2]. The paper is organized as follows: Section 2 provides an overview of recent work on vague spatial concepts. Insights gained from this overview are used later in the paper when describing and implementing the notion of spatial closeness.
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