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CCPO overview with marked CQs; prefix–ontology mapping: iof—IOF Core; obo—BFO; pato—phenotype and trait ontology [96]; ccpo—proposed concrete composition and properties ontology.
Source publication
Advanced construction techniques, such as additive manufacturing (AM) and modular construction, offer promising solutions to address labor shortages, reduce CO2 emissions, and enhance material efficiency. Despite their potential, the adoption of these innovative methods is hindered by the construction industry’s fragmented expertise. Building Infor...
Citations
... These integrated approaches, where the Semantic Web, ontology, and other cutting-edge fields like AI converge, are increasingly capturing the interest of construction informatics researchers. For example, Li and Petzold [46] developed an ontology-driven knowledge graph interfacing with advanced large language models (LLMs). This innovation facilitates effective question answering and knowledge retrieval within the domain of additive manufacturing in construction. ...
... In summary, while still in its early stages, the integration of Semantic Web technologies with emerging fields such as AI is gaining traction. This trend is exemplified by the works of Li and Petzold [46], focusing on ontologies and LLMs, and Qiang et al. (2024), who combined AI and Semantic Web technologies to address energy efficiency challenges. ...
The adoption of Building Information Modelling (BIM) in the construction industry has
been hindered by numerous barriers, notably the limited understanding of its concepts, protocols, and the intricate interplay between processes, people, and technologies. To address these challenges, a range of standards and guidelines have been developed, most notably the ISO 19650 series, which offer a comprehensive framework for implementing various aspects of BIM in construction projects. However, despite the BIM’s collaborative philosophy, the standards and specifications that guide its adoption and implementation seldom reveal and explain the relationships between
their key elements and concepts. This lack of clarity limits understanding and
undermines the very essence of collaboration that BIM seeks to promote in
construction projects. The text-based nature of the standards and specifications
makes it difficult to identify common concepts that cut across the different project
phases, their relationships, and interdependencies. This study proposes a BIM
ontology for information management (BIM-OIM) that makes BIM process data more
available and easily usable, allowing other researchers and practitioners to implement,
and extend its use within their domains of practice. To achieve the practice-driven goal
of BIM-OIM, Yet Another Methodology for Ontology (YAMO), one of the leading
ontology engineering methodologies, was used to develop BIM-OIM. BIM-OIM is a
formal and structured representation of ISO 19650 knowledge that is machine processable. This representation enhances understanding, promotes reusability, and
supports practical applications throughout the information management lifecycle. Key
applications include the development of BIM Execution Plans, compliance checking
for information containers, and identifying the roles of various stakeholders within a
project.
