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Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies

Author

Listed:
  • Pedro, Akeem
  • Pham-Hang, Anh-Tuan
  • Nguyen, Phong Thanh
  • Pham, Hai Chien

Abstract

Accident, injury, and fatality rates remain disproportionately high in the construction industry. Information from past mishaps provides an opportunity to acquire insights, gather lessons learned, and systematically improve safety outcomes. Advances in data science and industry 4.0 present new unprecedented opportunities for the industry to leverage, share, and reuse safety information more efficiently. However, potential benefits of information sharing are missed due to accident data being inconsistently formatted, non-machine-readable, and inaccessible. Hence, learning opportunities and insights cannot be captured and disseminated to proactively prevent accidents. To address these issues, a novel information sharing system is proposed utilizing linked data, ontologies, and knowledge graph technologies. An ontological approach is developed to semantically model safety information and formalize knowledge pertaining to accident cases. A multi-algorithmic approach is developed for automatically processing and converting accident case data to a resource description framework (RDF), and the SPARQL protocol is deployed to enable query functionalities. Trials and test scenarios utilizing a dataset of 200 real accident cases confirm the effectiveness and efficiency of the system in improving information access, retrieval, and reusability. The proposed development facilitates a new “open” information sharing paradigm with major implications for industry 4.0 and data-driven applications in construction safety management.

Suggested Citation

  • Pedro, Akeem & Pham-Hang, Anh-Tuan & Nguyen, Phong Thanh & Pham, Hai Chien, 2022. "Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies," MPRA Paper 112007, University Library of Munich, Germany, revised 07 Jan 2022.
    • Handle: RePEc:pra:mprapa:112007
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    Cited by:

    1. Danling Yuan & Keping Zhou & Chun Yang, 2023. "Architecture and Application of Traffic Safety Management Knowledge Graph Based on Neo4j," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
    2. Wei Tong Chen & Theresia Avila Bria, 2022. "A Review of Ontology-Based Safety Management in Construction," Sustainability, MDPI, vol. 15(1), pages 1-17, December.

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    More about this item

    Keywords

    construction safety; information sharing; knowledge graph; linked data; ontology; semantic web; data-driven; knowledge engineering; knowledge management; accident prevention;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L74 - Industrial Organization - - Industry Studies: Primary Products and Construction - - - Construction
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • N6 - Economic History - - Manufacturing and Construction

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