Enterprise Knowledge Modeling, UML vs Ontology: Formal Evaluation Everyday activities in enterprises rely heavily on the expertsxe2x80x99 knowhow. Due to experts departure, the loss of expertise and knowledge is a reoccurring problem in these enterprises. Recently, in order to capture experts knowledge into intelligent systems, formal knowledge representation methods, such as ontologies, are being studied and have caught up with nonformal or semiformal representation, such as UML. The similarities and differences between UML class diagram and computational ontology have for long raised questions about the possibility of synthesizing them in a common representation (usually an ontology). Indeed, the problem of migrating knowledge encoded in UML into an ontology is an active research domain. This paper outlines our approach, which is based on semantic matching between existing ontologies and a UML class diagram, to support UML driven ontology refactoring and engineering.

Combining UML and ontology: An exploratory survey Abstract   UML models and ontologies are two knowledge representations with different strengths and weaknesses. Until recently, they were considered unrelated research domains. However, studies investigating their underlying paradigms and the approaches combining these two are increasingly emerging. Nevertheless, the state of the art research covering the relationship between the two is still under exploration. In this paper, we aim to provide a comprehensive overview of both domains by conducting a literature review of the relevant research work. In this survey, the relationship between UML and ontology is investigated from both the theoretical and practical perspectives. We present a detailed classification of the existing work based on the considered issues and their practical use cases. Finally, we provide an evaluation of the existing work according to the criteria we identified.