SIM‐NET: A View‐Based Semantic Similarity Model for Ad Hoc Networks of Geospatial Databases

Abstract

AbstractSemantic similarity is a fundamental notion in GIScience for achieving semantic interoperability among geospatial data. Until now, several semantic similarity models have been proposed; however, few of these models address the issues related to the assessment of semantic similarity in ad hoc networks. Also, several models are based on a definition of concepts where features are independent, an assumption that reduces the richness of the geospatial concept representation. This article presents the conceptual basis for Sim‐Net, a novel semantic similarity model for ad hoc networks based on Description Logics (DL). Sim‐Net is based on the multi‐view paradigm. This paradigm is used to include inferential knowledge in semantic similarity, that is, the knowledge about implicit dependencies between features of concepts. In Sim‐Net, assessing semantic similarity relies on the notions of Semantic Reference Systems and Formal Concept Analysis (FCA), which are combined to establish a common semantic reference frame for ontologies of the ad hoc network called the view lattice. The Sim‐Net semantic similarity measure distinguishes concepts that belong to different or similar domains and takes into account the neighbours of a concept in the network. An application example is used to show the positive impact of the properties of Sim‐Net.