Detection, Simulation and Elimination of Semantic Anti-patterns in Ontology-Driven Conceptual Models

Abstract

The construction of large-scale reference conceptual models is a complex engineering activity. To develop high-quality models, a modeler must have the support of expressive engineering tools such as theoretically well-founded modeling languages and methodologies, patterns and anti-patterns and automated support environments. This paper proposes Semantic Anti-Patterns for ontology-driven conceptual modeling. These anti-patterns capture error prone modeling decisions that can result in the creation of models that allow for unintended model instances (representing undesired state of affairs). The anti-patterns presented here have been empirically elicited through an approach of conceptual models validation via visual simulation. The paper also presents a tool that is able to: automatically identify these anti-patterns in user’s models, provide visualization for its consequences, and generate corrections to these models by the automatic inclusion of OCL constraints.