Ontology-based approach for heterogeneity analysis of EA models

Abstract

The different needs and domains of enterprises and how they employ EA modelling languages and tools can give rise to heterogeneity at the syntactical, structural and semantical levels. In particular, models dealing with the process perspective are becoming increasingly complex and hetereogeneous. This raises difficulties in managing and reusing EA models. To address the heterogeneity of EA models, we propose an approach that relies on encoding the models as OWL ontologies, then applying ontology matching techniques to map them. By using ontology-based techniques applied to the heterogeneity analysis of EA models. We have applied our approach to a well known benchmarking data set (EMISA-PMMC) encoded in BPMN. This involved the creation of a novel ontology matching algorithm specifically designed for business processes and their integration in a state of the art ontology matching system, AgreementMakerLight.