Improving Conceptual Domain Characterization in Ontology Networks.

The community of Conceptual Modeling (CM) perception that Semantic Interoperability cannot be achieved without the support of an ontology-driven approach has become increasingly consensual. Moreover, the more complex and extensive the domain of the application of conceptual models, the harder it is to achieve semantic consensus. Therefore, it has emerged the perception that ontologies built to describe complex domains should not be overly large or be used in isolation. Ontology Networks arose to cover this issue. The community had to deal with issues such as different ontologies of the network using the same concept with different meanings or the same term used to designate distinct concepts. We developed a framework for classifying ontologies that provides a stable and homogeneous environment to facilitate the ontological analysis process by dealing simultaneously with ontological and domain perspectives. This article presents our proposal where conceptualization is used to identify the relationships among the evaluated ontologies. Our goal is to facilitate semantic consensus, providing guidelines and best practices supported by a stable, homogeneous, and repeatable environment.