Suchergebnisse

Funding Information: This research was partly supported by the DiCtion (Digitalizing Construction Workflows) project, which was funded by Business Finland and a consortium of six industrial partners (until 2020). It was also partly funded by the BIM4EEB project that has received funding from European Union's H2020 research and innovation programme under grant agreement N. 820660 (from 2019-). Financial support was also provided by the Building 2030 consortium of 21 Finnish companies (from 2020-). The content of this publication reflects the authors' view only, and Business Finland, the European Commission or the Building 2030 consortium are not responsible for any use that may be made of the information it contains. The authors are grateful for the study's financial and technical support. Publisher Copyright: © 2021 The Authors ; 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. ; Peer reviewed