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By ontology, we understand a knowledge structure which well reflects the complexity of a real world. Ontologies are built to store and process knowledge about objects and dependencies between them. Thus, ontologies not only structure raw data, but also contain the meaning of those data. So far, ontology developers have been forced to provide the semantics of modeled objects and relations between them manually. The goal of this paper is to address some still unresolved problems related to providing meanings in ontologies. A typical ontology consists of concepts with attributes, relations between them, and instances. In our research, we focus on concepts level where attributes must be interpretable because they are the primary carriers of the meaning of the entire ontology. In other words, we need to assign semantics for each attribute within a concept. For this purpose, we have proposed a semi-automatic method for defining attribute semantics based on WordNet. The attribute semantics designated by human experts and based on WordNet does not affect the integration result. However, the developed method allows reducing the time for preparing an ontology to the integration process. What is more, it is less sensitive to the subjective evaluations done by experts.

Semi-Automatic Definition of Attribute Semantics for the Purpose of Ontology Integration