OntoSTEP: Enriching product model data using ontologies

Authors:
Raphael Barbau;Sylvere Krima;Sudarsan Rachuri;Anantha Narayanan;Xenia Fiorentini;Sebti Foufou;Ram D. Sriram
Affiliations:
Le2i, Université de Bourgogne, BP 47870, 21078 Dijon, France and System Integration Division, Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, U ...;Le2i, Université de Bourgogne, BP 47870, 21078 Dijon, France and System Integration Division, Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, U ...;System Integration Division, Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA;System Integration Division, Engineering Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA;Engisis s.r.l., Rome, Italy;Le2i, Université de Bourgogne, BP 47870, 21078 Dijon, France and CSE Department, CENG, Qatar University, Doha, Qatar;Software and Systems Division, Information Technology Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
Venue:
Computer-Aided Design
Year:
2012

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Abstract

The representation and management of product lifecycle information is critical to any manufacturing organization. Different modeling languages are used at different lifecycle stages, for example STEP's EXPRESS may be used at a detailed design stage, while UML may be used for initial design stages. It is necessary to consolidate product information created using these different languages to build a coherent knowledge base. In this paper, we present an approach to enable the translation of STEP schema and its instances to Ontology Web Language (OWL). This gives a model-which we call OntoSTEP-that can easily be integrated with any OWL ontologies to create a semantically rich model. As an example, we combine geometry information represented in STEP with non-geometry information, such as function and behavior, represented using the NIST's Core Product Model (CPM). A plug-in for Protege is developed to automate the different steps of the translation. As additional benefits, reasoning, inference procedures, and queries can be performed on enriched legacy CAD models. We describe the rules for the translation from EXPRESS to OWL, and illustrate the benefits of OWL translation with an example. We will also describe how these mapping rules can be implemented through meta-model based transformations, which can be used to map other languages to OWL.