Semantic correction, enrichment and enhancement of social and transport infrastructure BIM models
File(s)
Published version
Author(s)
Nisbet, Nicholas
Zhang, Zijing
Ma, Ling
Chen, Weiwei
Çıdık, Mustafa Selçuk
Type
Journal Article
Abstract
The use of Building Information Modelling (BIM) models in the design, construction and operation of buildings and infrastructure is leading to a stronger focus on the quality of the models. Models may need correction, enrichment or enhancement to meet the expectations for quality and completeness, especially if models are to be taken as legal documents, for example for regulatory approval. Past work on semantic development has looked at specific scenarios such as scanned geometry or missing classification. This paper describes an innovative unified approach to the documentation of semantic expectations by actors in the AECO (Architectural, Engineering, Construction and Operations) domain and the means to put them into effect. RASE (Requirements, Applications, Selections and Exceptions) semantic mark-up is used to make both the requirements and any supporting resources both human-readable and machine-operable. Two example models from industry, a motorway bridge and a healthcare space, are used to demonstrate applying geometric, schema and classification knowledge. This knowledge is represented in a number of different styles. This extends our understanding of the nature of the knowledge found in dictionaries, classifications and development specifications, demonstrating how this knowledge can be made operable. This bridges the gap between the application of static compliance knowledge and the accurate and efficient application of correction, enrichment and enhancement knowledge.
Date Issued
2024-01-01
Date Acceptance
2023-11-24
Citation
Advanced Engineering Informatics, 2024, 59
ISSN
1474-0346
Publisher
Elsevier BV
Journal / Book Title
Advanced Engineering Informatics
Volume
59
Copyright Statement
© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
10.1016/j.aei.2023.102290
Publication Status
Published
Article Number
102290
Date Publish Online
2023-12-04