A process model discovery approach for enabling model interoperability in signal engineering
Proceedings of the First International Workshop on Model-Driven Interoperability
Ontology-Driven Software Engineering
RDF containers: a framework for the integration of distributed and heterogeneous applications
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems
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The engineering of complex production automation systems involves experts from several backgrounds, such as mechanical, electrical, and software engineering. The production automation expert knowledge is embedded in their tools and data models, which are, unfortunately, insufficiently integrated across the expert disciplines, due to semantically heterogeneous data structures and terminologies. Traditional integration approaches to data integration using a common repository are limited as they require an agreement on a common data schema by all project stakeholders. In this paper we introduce the Engineering Knowledge Base (EKB), a semantic-web-based framework, which supports the efficient integration of information originating from different expert domains without a complete common data schema. We evaluate the proposed approach with data from real-world use cases from the production automation domain on data exchange between tools and model checking across tools. Major results are that the EKB framework supports stronger semantic mapping mechanisms than a common repository and is more efficient if data definitions evolve frequently.