Semantic Building Information Modeling: an empirical evaluation of existing tools
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
Semantic Building Information Modeling (BIM) consists in translating data expressed using BIM formats (namely IFC) into Semantic Web files using RDF serializations (e.g., Turtle). This enables the inference of new knowledge and constraint checking, among other advantages. While several software tools for translating BIM models into Semantic Web languages have been proposed in the literature, they differ in the features exposed.
This paper analyzes and empirically compares some of these tools (namely, IFC converters translating an input IFC model into an RDF graph), identifying their strengths and main limitations. Our methodology includes measuring computation times of common tasks (file conversion, query and inference over output files), assessing the retention of knowledge (particularly, geometric information) and examining reasoning capabilities (complexity and completeness of the resulting models). Our results show that IFCtoLBD is the best option in many cases. IFCtoRDF and IFC2LD are slower but better preserve geometric information, while KGG is faster at the expense of losing information in the translation.
This paper analyzes and empirically compares some of these tools (namely, IFC converters translating an input IFC model into an RDF graph), identifying their strengths and main limitations. Our methodology includes measuring computation times of common tasks (file conversion, query and inference over output files), assessing the retention of knowledge (particularly, geometric information) and examining reasoning capabilities (complexity and completeness of the resulting models). Our results show that IFCtoLBD is the best option in many cases. IFCtoRDF and IFC2LD are slower but better preserve geometric information, while KGG is faster at the expense of losing information in the translation.
Date Issued
2024-11-01
Date Acceptance
2024-11-03
Citation
Journal of Industrial Information Integration, 2024, 42
ISSN
2452-414X
Publisher
Elsevier
Journal / Book Title
Journal of Industrial Information Integration
Volume
42
Copyright Statement
Copyright © 2024 Elsevier Inc. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Subjects
Building Information Modeling
Computer Science
Computer Science, Interdisciplinary Applications
Engineering
Engineering, Industrial
EXPRESS
IFCOWL
INDUSTRY
Ontologies
ONTOLOGY
OWL
RDF graphs
REPRESENTATION
Science & Technology
Semantic BIM software
Technology
Publication Status
Published
Article Number
100731
Date Publish Online
2024-11-12