A shared ontology suite for digital construction workflow

Yuan Zheng*, Seppo Törmä, Olli Seppänen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

41 Citations (Scopus)
256 Downloads (Pure)


With ongoing advancements in information and communication technologies (ICTs) in all stages of the construction lifecycle, information from entities related to construction workflow (CW) can now be automatically collected. These implementations are point solutions, which require systematic integration to combine their information to enable a holistic picture of CW. The major barrier to such integration is information heterogeneity, where the information is collected from different systems under multiple contexts. Scholars in the construction domain have explored the use of ontology to solve the information-integration problem, although an ontology that both adequately represents the CW and integrates the digitalized information of CW via various systems and multiple contexts is currently missing from the existing literature. This research thus presents an ontology set for formalizing and integrating CW information within the digital construction context. The proposed digital construction ontologies (DiCon) are shared representations of construction domain knowledge that specify the terms and relations of CWs and their related information. We developed the DiCon based on a hybrid ontology development approach. The DiCon includes six modules: Entities, Processes, Information, Agents, Variables, and Contexts. The developed DiCon was further evaluated by approaches including automatic consistency checking, criteria-based evaluation, expert workshops, and task-based evaluation and involved two use cases by answering relevant competency questions via SPARQL queries. The results of the evaluation demonstrate that the DiCon ontologies are sufficient to represent domain knowledge and can formalize and integrate CW information within the digital construction context.

Original languageEnglish
Article number103930
Number of pages23
JournalAutomation in Construction
Publication statusPublished - Dec 2021
MoE publication typeA1 Journal article-refereed


  • Construction workflow
  • Digital construction
  • Information management
  • Ontology


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