A Reference Ontology Based Approach for Service Oriented Semantic Interoperability

A Reference Ontology Based Approach for Service Oriented Semantic Interoperability

Shuying Wang (University of Western Ontario, Canada), Kevin P. Brown (University of Western Ontario, Canada), Jinghui Lu (University of Western Ontario, Canada) and Miriam Capretz (University of Western Ontario, Canada)
Copyright: © 2011 |Pages: 16
DOI: 10.4018/jwp.2011010101
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Abstract

To establish effective information exchange among applications in a distributed environment, participants not only share their functions and service interfaces, but often exchange data models. This paper proposes the use of ontologies to represent data models thus allowing applications to locate and integrate these models. A reference ontology based approach for service oriented ontology management is introduced. Specifically, a domain-specific reference ontology for use in the evaluation of a practical case is developed. To validate and evaluate the approach, a prototype system is developed to provide ontology deploying, browsing and mapping operations based on a service-oriented system. Experiments provide promising results that are consistent with the original ideas of managing ontologies and optimizing ontology mappings to facilitate data interoperability in a distributed environment.
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Our work aims to extend the principles of the ontology mapping approach as well as the emerging Web services standards in order to support the manageability and interoperability of heterogeneous data sources. A fundamental problem with ontology mapping involves the integration of heterogeneous data sources, which has been researched extensively in the last two decades (Rahm & Bernstein, 2001).

Background Knowledge Used in Mapping

Some research approaches (Sabou, d’Aquin, & Motta, 2006; Aleksovski, Klein, ten Kate, & Harmelen, 2006; Ehrig & Staab, 2004) have considered the use of external background knowledge as a way of obtaining semantic mappings between syntactically dissimilar ontologies. WordNet is one of the most frequently used sources of background knowledge. The literature (Li, Szpakowicz, & Matwin, 1995) shows that WordNet has been used successfully for word sense disambiguation algorithms in other contexts, particularly in text. WordNet is an extremely large and readily available in an online database, which is divided into various parts of speech such as nouns, verbs, adjectives, and adverbs. The nouns are organized as a hierarchy of nodes where each node is a word meaning or, as it is termed in WordNet, a synset, which is simply a set of English words that express the same meaning in at least one context.

SUMO was initially created by Ian Niles and Adam Pease (2001). As one of three starter documents under consideration by the IEEE, SUMO was developed to facilitate data interoperability, information search and retrieval, automated inference, and natural language processing.

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