Ontologies are widely used as a means for solving the information heterogeneity problems on the web because of their capability to provide explicit meaning to the information. In recent years, the growing need to resolve the ambiguities and integrate vocabularies between heterogeneous systems within a domain of interest led to the rapid development of ontologies by different organizations. These ontologies designed for a particular task could be a unique representation of their project needs. Hence, there arises a need to align heterogeneous ontologies to facilitate meaningful knowledge interchange between various sources. Thus, ontology mapping has become the key point to enable semantic interoperability between different representations within a domain. This paper proposes a new instance-based algorithm to automate ontology mapping in ocean sensor networks, whose data are highly heterogeneous in syntax, structure and semantics.
['Shruthi Bheemireddy', 'Surya S. Durbha', 'Roger L. King', 'Santhosh K. Amanchi', 'Nicolas H. Younan']
An ontology merging tool to facilitate interoperability between coastalsensor networks