IFC-graph for facilitating building information access and query

This study attempts to address a challenge regarding the extraction of building information, which is one of the fundamental tasks that needs to be addressed in the construction domain. Current technologies, such as relational databases, have difficulty in efficiently and effectively managing and qu...

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Main Authors: Zhu, Junxiang, Wu, Peng, Lei, Xiang
Format: Journal Article
Published: Elsevier 2023
Online Access:http://purl.org/au-research/grants/arc/DP180104026
http://hdl.handle.net/20.500.11937/90621
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author Zhu, Junxiang
Wu, Peng
Lei, Xiang
author_facet Zhu, Junxiang
Wu, Peng
Lei, Xiang
author_sort Zhu, Junxiang
building Curtin Institutional Repository
collection Online Access
description This study attempts to address a challenge regarding the extraction of building information, which is one of the fundamental tasks that needs to be addressed in the construction domain. Current technologies, such as relational databases, have difficulty in efficiently and effectively managing and querying the interconnected building information with full of hidden relationships. To address this problem, this study adopted the graph-theory-based graph database technology to reveal hidden relationships within building information. A model-driven approach was developed to enable a full conversion of Industry Foundation Classes data into labeled property graph, which is referred to as IFC-Graph. The result shows that IFC-Graph can represent interconnected building information and reveal hidden relationships, supporting effective and efficient building information access and query. This study can benefit a vast number of future studies in the area of building information query by improving its accessibility and queryability.
first_indexed 2025-11-14T11:34:43Z
format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T11:34:43Z
publishDate 2023
publisher Elsevier
recordtype eprints
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spelling curtin-20.500.11937-906212023-03-27T05:30:25Z IFC-graph for facilitating building information access and query Zhu, Junxiang Wu, Peng Lei, Xiang This study attempts to address a challenge regarding the extraction of building information, which is one of the fundamental tasks that needs to be addressed in the construction domain. Current technologies, such as relational databases, have difficulty in efficiently and effectively managing and querying the interconnected building information with full of hidden relationships. To address this problem, this study adopted the graph-theory-based graph database technology to reveal hidden relationships within building information. A model-driven approach was developed to enable a full conversion of Industry Foundation Classes data into labeled property graph, which is referred to as IFC-Graph. The result shows that IFC-Graph can represent interconnected building information and reveal hidden relationships, supporting effective and efficient building information access and query. This study can benefit a vast number of future studies in the area of building information query by improving its accessibility and queryability. 2023 Journal Article http://hdl.handle.net/20.500.11937/90621 10.1016/j.autcon.2023.104778 http://purl.org/au-research/grants/arc/DP180104026 http://creativecommons.org/licenses/by/4.0/ Elsevier fulltext
spellingShingle Zhu, Junxiang
Wu, Peng
Lei, Xiang
IFC-graph for facilitating building information access and query
title IFC-graph for facilitating building information access and query
title_full IFC-graph for facilitating building information access and query
title_fullStr IFC-graph for facilitating building information access and query
title_full_unstemmed IFC-graph for facilitating building information access and query
title_short IFC-graph for facilitating building information access and query
title_sort ifc-graph for facilitating building information access and query
url http://purl.org/au-research/grants/arc/DP180104026
http://hdl.handle.net/20.500.11937/90621