Semantic web based rule checking of real-world scale BIM models: a pragmatic method

Tracking #: 1621-2833

This paper is currently under review
Authors: 
Hehua Zhang
Wenqi Zhao
Jianqiao Gu
Han Liu
Ming Gu

Responsible editor: 
Guest Editors ST Built Environment 2017

Submission type: 
Full Paper
Abstract: 
Rule checking is important to assure the integrity, correctness and usability of Building Information Models (BIMs) in Architecture, Engineering and Construction (AEC) projects. Semantic web based rule checking of BIM models are widely accepted and studied recent years. This technology has noteworthy advantages on interoperability, extensibility and logical basics. However, there are still some gaps to make it practical. One challenge is the efficiency problem on processing large-scale BIM models. The other is how to effectively input checking rules which can be understood by both human beings and machines. In this paper, we propose a pragmatic method to check real-world scale BIM models. In our framework, BIM models are transformed into a well-defined OWL model. Rules are formalized by a structured natural language (SNL) designed intentionally to describe building regulations. The checking engine is based on SPARQL queries on OWL models. We propose a rule-based model extraction method and optimization strategies on SPARQL statements, which can effectively improve the time efficiency and deal with large-scale applications. A prototype has been implemented and applied to BIM models of a real-world building project. We found out non-trivial problems in a totally automatic way, which helped to improve the quality of BIM models and verified the usability of our method.
Full PDF Version: 
Tags: 
Under Review

Comments