A linked data system framework for sharing construction defect information using ontologies and BIM environments

Do Yeop Lee, Hung-lin Chi, Jun Wang, Xiangyu Wang, Chan Sik Park

Research output: Journal article publicationJournal articleAcademic researchpeer-review

44 Citations (Scopus)

Abstract

Defect data contains knowledge about specific work conditions. In order to prevent reoccurrence of defects, a data feedback mechanism is required. However, most defect data are stored in unstructured ways, resulting in the fundamental problem of data utilization. This paper proposes a novel framework by using BIM and linked data technologies for sharing defect data between heterogeneous data sources in a new way. To demonstrate, a defect ontology is developed, work context information is extracted from BIM models, extracted BIM data is converted to RDF format, and SPARQL queries are implemented. The proposed approach could help BIM software applications to take into account information stemming from the defect management domain. Also, it can reduce data search time and improve the accuracy of search results as well. Therefore, this framework may enable reductions of defect occurrence and improvements in current defect management practices.
Original languageEnglish
Pages (from-to)102-113
Number of pages12
JournalAutomation in Construction
Volume68
DOIs
Publication statusPublished - 1 Aug 2016
Externally publishedYes

Keywords

  • Building information modeling
  • Defect management
  • Linked data
  • Ontology
  • SPARQL query

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Civil and Structural Engineering
  • Building and Construction

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