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IfcOWL: A case of transforming EXPRESS schemas into ontologies

Beetz, Jakob, van Leeuwen, Jos, de Vries, Bauke·2009·Artificial Intelligence for Engineering Design, Analysis and Manufacturing

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.

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Metadata

Authors
Beetz, J., van Leeuwen, J., & de Vries, B.
Venue
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Published
2008-12-16
Volume
23
Issue
1
Pages
89-101
ISSN
  • 0890-0604 (ISSN-L)
  • 1469-1760
OpenAlex
W2094504514
Cited by
304
References
1
FWCI
6.36
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: IfcOWL: A case of transforming EXPRESS schemas into ontologies. https://app.cochat.ai/papers/10.1017/s0890060409000122
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Beetz, J., van Leeuwen, J., & de Vries, B. (2009). IfcOWL: A case of transforming EXPRESS schemas into ontologies. Artificial Intelligence for Engineering Design, Analysis and Manufacturing. https://doi.org/10.1017/s0890060409000122

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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