Bridging Semantic Gaps Between Stakeholders in the Production Automation Domain with Ontology Areas

Stakeholders from several domains with local terminologies have to work together to develop and operate softwareintensive systems, like production automation systems. Ontologies support the translation between local terminologies via common domain concepts. Unfortunately, the ontology models can become large and complex if they include several aspects on a domain and some parts of the data model are volatile. In this paper, we propose a data modeling approach to support ontology users based on ontology building blocks, so-called “Ontology Areas” (OAs), which allow solving tasks with smaller parts of the overall ontology. We evaluate the proposed approach with use cases from the production automation domain: translation between stakeholder roles to support design-time and run-time decision making. Major result in the study context is that OAs improved the efficiency of data collection for decision making.