The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
IfcOWL: A case of transforming EXPRESS schemas into ontologies
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The entity-relationship model—toward a unified view of data
Chen, P. P.-S. (1976) · ACM Transactions on Database Systems · doi:10.1145/320434.320440 · Cited by 4,708
Cited by
Big Data in the construction industry: A review of present status, opportunities, and future trends
Bilal, M., Oyedele, L. O., Qadir, J., Munir, K., Ajayi, S. O., Akinade, O. O., Owolabi, H. A., Alaka, H. A., & Pasha, M. (2016) · Advanced Engineering Informatics · doi:10.1016/j.aei.2016.07.001 · Cited by 734
A semantic rule checking environment for building performance checking
Pauwels, P., Van Deursen, D., Verstraeten, R., De Roo, J., De Meyer, R., Van de Walle, R., & Van Campenhout, J. (2011) · Automation in Construction · doi:10.1016/j.autcon.2010.11.017 · Cited by 277
Dynamic prompt-based virtual assistant framework for BIM information search
Zheng, J., & Fischer, M. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.105067 · Cited by 154
Management of Collaborative BIM Data by Federating Distributed BIM Models
Beach, T., Petri, I., Rezgui, Y., & Rana, O. (2017) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0000657 · Cited by 67
Metadata
- Authors
- Beetz, J., van Leeuwen, J., & de Vries, B.
- Venue
- Artificial Intelligence for Engineering Design, Analysis and Manufacturing
- Publisher
- Cambridge University Press (CUP)
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: IfcOWL: A case of transforming EXPRESS schemas into ontologies. https://app.cochat.ai/papers/10.1017/s0890060409000122
- The paper
- 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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.