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IfcOWL: A case of transforming EXPRESS schemas into ontologies

Published online by Cambridge University Press:  16 December 2008

Jakob Beetz ,
Jos van Leeuwen  and
Bauke de Vries
Jakob Beetz
Affiliation:
Department of Architecture, Building and Planning, Eindhoven University of Technology, Eindhoven, The Netherlands
Jos van Leeuwen
Affiliation:
Department of Architecture, Building and Planning, Eindhoven University of Technology, Eindhoven, The Netherlands
Bauke de Vries
Affiliation:
Department of Architecture, Building and Planning, Eindhoven University of Technology, Eindhoven, The Netherlands
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Abstract

Ontologies have been successfully applied as a semantic enabler of communication between both users and applications in fragmented, heterogeneous multinational business environments. In this paper we discuss the underlying principles, their current implementation status, and most importantly, their applicability to problems in the building information modeling domain. We introduce the development of an ontology for the building and construction sector based on the industry foundation classes. We discuss several approaches of lifting modeling information that is based on the express family of languages for data modeling onto a logically rigid and semantically enhanced ontological level encoded in the W3C Ontology Web Language. We exemplify the added value of such formal notation of building models by providing several examples where generic query and reasoning algorithms can be applied to problems that otherwise have to be manually hard-wired into applications for processing building information. Furthermore, we show how the underlying resource description framework and the set of technologies evolving around it can be tailored to the need of distributed collaborative work in the building and construction industry.

Keywords

Building Information ModelingKnowledge RepresentationModel-Driven ArchitecturesOntologies
Type
Research Article
Information
AI EDAM , Volume 23 , Issue 1: Developing and Using Engineering Ontologies , February 2009 , pp. 89 - 101
Copyright
Copyright © Cambridge University Press 2009

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References

REFERENCES

Adachi, Y. (2003). Overview of partial model query language. Proc. ISPE Conf. Concurrent Engineering 2003, pp. 549–555.Google Scholar
Arenas, M., Perez, J., & Gutierrez, C. (2006). Semantics and complexity of SPARQL. Proc. 5th Int. Semantic Web Conf. (ISWC06), pp. 30–43.Google Scholar
ARQ (2005). ARQ—a SPARQL processor for Jena. Accessed at http://jena.sourceforge.net/ARQ/ on August 2007.Google Scholar
Augenbroe, G. (1994). An overview of the COMBINE project. Proc. 1st European Conf. Product and Process Modeling in the Building Industry ECPPM'94, p. 547.Google Scholar
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., & Patel-Schneider, P. (2003). The Description Logic Handbook: Theory, Implementation, and Applications. New York: Cambridge University Press.Google Scholar
Bechhofer, S., van Harmelen, F., Hendler, J., et al. (2004). OWL Web Ontology Language Reference. W3C Recommendation. Accessed at http://www.w3.org//TR/owl-ref/ on October 7, 2007.Google Scholar
Beetz, J., de Vries, B., & van Leeuwen, J.P. (2007). RDF-based distributed functional part specifications for the facilitation of service-based architectures. Proc. 24th W78 Conf. Maribor 2007, pp. 183–188.Google Scholar
Berners-Lee, T. (1998). Notation 3 (N3): A Readable RDF Syntax. Technical Report World Wide Web Consortium, 1998–2006. Accessed at http://www.w3.org/DesignIssues/Notation3.html on August 2007.Google Scholar
Björk, B. (1994). RATAS Project—developing an infrastructure for computer-integrated construction. Journal of Computing in Civil Engineering 8 ( 4), 401–419.CrossRefGoogle Scholar
Böhms, M., Bonsma, P., Bourdeau, M., Pascual, E., Storer, G., & Sedano, J. (2006). “Semantic Web”-based product modelling: ontologies and configurators. In Exploiting the Knowledge Economy: Issues, Applications and Case Studies (Cunningham, P., & Cunningham, M., Eds.), pp. 1099–1107. Amsterdam: IOS Press.Google Scholar
Borrmann, A., Schraufstetter, S., van Treeck, C., & Rank, E. (2007). An octree-based implementation of directional operators in a 3D spatial query language for building information models. Proc. 24th W78 Conf. Maribor.Google Scholar
Brickley, D., & Guha, R. (2004, February 10). RDF Vocabulary description language 1.0: RDF schema W3C recommendation. Accessed at http://www.w3.org/TR/2004/REC-rdf-schema-20040210/Google Scholar
Broekstra, J., & Kampman, A. (2003). SeRQL: a second generation RDF query language. Proc. SWAD—Europe Workshop on Semantic Web Storage and Retrieval.Google Scholar
Chen, P.P. (1976). The entity-relationship model—toward a unified view of data. ACM Transactions on Database Systems 1 ( 1), 9–36.CrossRefGoogle Scholar
Corcho, O., Fernández-López, M., & Gómez-Pérez, A. (2003). Methodologies, tools and languages for building ontologies. Where is their meeting point? Data & Knowledge Engineering 46 ( 1), 41–64.CrossRefGoogle Scholar
Dolenc, M., Katranuschkov, P., Gehre, A., Kurowski, K., & Turk, Z. (2007). The InteliGrid platform for virtual organisations interoperability. ITcon 12, 459–477.Google Scholar
Drummond, N., Rector, A., Stevens, R., Moulton, G., Horridge, M., Wang, H., & Seidenberg, J. (2006). Putting OWL in order: patterns for sequences in OWL. Proc. 2nd OWL Experiences and Directions Workshop, Athens.Google Scholar
Edmonds, B., & Bryson, J.J. (2004). The insufficiency of formal design methods—the necessity of an experimental approach for the understanding and control of complex MAS. Proc. Third Int. Joint Conf. Autonomous Agents and Multiagent Systems, pp. 938–945.Google Scholar
Gielingh, W. (1988). General AEC reference model (GARM) an aid for the integration of application specific product definition models. Proc. CIB W74 + W78 Workshop, pp. 165–178.Google Scholar
Gruber, T. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition 5 ( 2), 199–220.CrossRefGoogle Scholar
Gutierrez, C., Hurtado, C., & Vaisman, A. (2005). Temporal RDF. Proc. 2nd European Semantic Web Conf. (ESWC ’05), pp. 93–107.CrossRefGoogle Scholar
Hietanen, J. (2006). IFC Model View Definition Format, Technical Report. International Alliance for Interoperability.Google Scholar
Horrocks, I., Patel-Schneider, P.F., & van Harmelen, F. (2003). From SHIQ and RDF to OWL: the making of a Web Ontology Language. Web Semantics: Science, Services and Agents on the World Wide Web 1 ( 1), 7–26.CrossRefGoogle Scholar
Huang, Z., & Stuckenschmidt, H. (2005). Reasoning with multi-version ontologies: a temporal logic approach. Int. Semantic Web Conf., pp. 398–412.Google Scholar
IDEF1x. (1993). Integration Definition for Information Modeling (IDEF1x). FIPS Publication 184, National Institute of Standards and Technology.Google Scholar
ISO. (2007). ISO10303-28:2007. Industrial Automation Systems and Integration—Product Data Representation and Exchange. Part 28: Implementation Methods: XML Representations of EXPRESS Schemas and Data, Using XML Schemas. Geneva: ISO.Google Scholar
Karvounarakis, G., Alexaki, S., Christophides, V., Plexousakis, D., & Scholl, M. (2002). RQL: a declarative query language for RDF. Proc. 11th Int. Conf. World Wide Web, pp. 592–603. New York: ACM Press.Google Scholar
Lassila, O., & McGuinness, D. (2001). The role of frame-based representation on the Semantic Web. Linköping Electronic Articles in Computer and Information Science 6.Google Scholar
Lê, M., Mohus, F., Kvarsvik, O., & Lie, M. (2006). The HITOS project—a full scale IFC test. Proc. ECPPM 2006.Google Scholar
Lee, E.C., & Sacks, R. (2006). Generating IFC VIEWs and conformance classes using GTPPM. Proc. 11th Int. Conf. Computing in Civil and Building Engineering ICCCBE-XI, pp. 1715–1724.Google Scholar
Lima, C., El-Diraby, T., & Stephens, J. (2005). Ontology-based optimisation of knowledge management in e-Construction. ITcon 10, 305–327.Google Scholar
McGuinness, D., Fikes, R., Hendler, J., & Stein, L. (2002). DAML+ OIL: an ontology language for the Semantic Web. Intelligent Systems 17 ( 5), 72–80.CrossRefGoogle Scholar
Minsky, M. (1975). A framework for representing knowledge. In The Psychology of Computer Vision (Winston, P., Ed.), pp. 211–277. New York: McGraw–Hill.Google Scholar
Nijssen, G., & Halpin, T. (1989). Conceptual Schema and Relational Database Design: A Fact Oriented Approach. Upper Saddle River, NJ: Prentice–Hall.Google Scholar
OSExpress. (2001). Project homepage. Accessed at http://osexpress.sourceforge.net/ on August 2007.Google Scholar
Parr, T., & Quong, R. (1995). ANTLR: a predicated-LL(k) parser generator. Software—Practice and Experience 25 ( 7), 789–810.CrossRefGoogle Scholar
Schenck, D., & Wilson, P. (1994). Information Modeling: The EXPRESS Way. New York: Oxford University Press.CrossRefGoogle Scholar
Seidenberg, J., & Rector, A. (2006). Web ontology segmentation: analysis, classification and use. WWW ’06: Proc. 15th Int. Conf. World Wide Web, pp. 13–22. New York: ACM Press.Google Scholar
Sowa, J. (2000). Knowledge Representation: Logical, Philosophical, and Computational Foundations. Pacific Grove, CA: MIT Press.Google Scholar
Spyns, P., Meersman, R., & Jarrar, M. (2002). Data modeling versus ontology engineering. ACM SIGMOD Record 31, 12–17.CrossRefGoogle Scholar
Uschold, M., & King, M. (1995). Towards a methodology for building ontologies. Proc. Workshop on Basic Ontological Issues in Knowledge Sharing in Conjunction With IJCAI95, Artificial Intelligence Applications Institute, University of Edinburgh.Google Scholar
van Leeuwen, J.P., & Fridqvist, S. (2003). Object version control for collaborative design—characteristics of the concept-modelling framework. E-Activities in Building Design and Construction—9th EuropIA Int. Conf. (Tunçer, B., Özsariyildiz, S.S., & Sariyildiz, S., Eds.), pp. 129–139. Paris: EuropIA Productions.Google Scholar
Weise, M., Katranuschkov, P., & Scherer, R.J. (2003). Generalised model subset definition schema. Proc. CIB-W78 Conf. 2003—Information Technology for Construction. Accessed at https://www.cs.auckland.ac.nz/w78/papers/Google Scholar
Wix, J., Christensen, L., Mohus, F., Stangeland, B., & Espedokken, K. (2005). A framework of information for construction—creating an industry-wide enterprise architecture for building information modeling use. Proc. 6th European Conf. Product and Process Modelling, pp. 665–671, Valencia, Spain, September 13–15.Google Scholar
Woods, W.A. (1975). What's in a link: foundations for semantic networks. In Representation and Understanding: Studies in Cognitive Science (Bobrow, D., & Collins, A., Eds.), pp. 35–82. New York: Academic Press.CrossRefGoogle Scholar