Ontology-Based Model Abstraction

• Published in: 2019 13th International Conference on Research Challenges in Information Science (RCIS) pp. 1 - 13
• Main Authors: Guizzardi, Giancarlo, Figueiredo, Guylerme, Hedblom, Maria M., Poels, Geert
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2019
• Subjects: Clustering methods; Complexity Management in Conceptual Modeling; Complexity theory; Context modeling; Model Abstraction; Object oriented modeling; Ontologies; Ontology-Based Conceptual Modeling; Semantics; Unified modeling language
• ISSN: 2151-1357
• DOI: 10.1109/RCIS.2019.8876971

In recent years, there has been a growth in the use of reference conceptual models to capture information about complex and critical domains. However, as the complexity of domain increases, so does the size and complexity of the models that represent them. Over the years, different techniques for complexity management in large conceptual models have been developed. In particular, several authors have proposed different techniques for model abstraction. In this paper, we leverage on the ontologically well-founded semantics of the modeling language OntoUML to propose a novel approach for model abstraction in conceptual models. We provide a precise definition for a set of Graph-Rewriting rules that can automatically produce much-reduced versions of OntoUML models that concentrate the models' information content around the ontologically essential types in that domain, i.e., the so-called Kinds. The approach has been implemented using a model-based editor and tested over a repository of OntoUML models.