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Systematic Knowledge Management of Construction Safety Standards Based on Knowledge Graphs: A Case Study in China

Author

Listed:
  • Yukun Jiang

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Xin Gao

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Wenxin Su

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Jinrong Li

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

Abstract

Construction safety standards (CSS) have knowledge characteristics, but few studies have introduced knowledge graphs (KG) as a tool into CSS management. In order to improve CSS knowledge management, this paper first analyzed the knowledge structure of 218 standards and obtained three knowledge levels of CSS. Second, a concept layer was designed which consisted of five levels of concepts and eight types of relationships. Third, an entity layer containing 147 entities was constructed via entity identification, attribute extraction and entity extraction. Finally, 177 nodes and 11 types of attributes were collected and the construction of a knowledge graph of construction safety standard (KGCSS) was completed using knowledge storage. Furthermore, we implemented knowledge inference and obtained CSS planning, i.e., the list of standard work plans used to guide the development and revision of CSS. In addition, we conducted CSS knowledge retrieval; a process which supports interrogative input. The construction of KGCSS thus facilitates the analysis, querying, and sharing of safety standards knowledge.

Suggested Citation

  • Yukun Jiang & Xin Gao & Wenxin Su & Jinrong Li, 2021. "Systematic Knowledge Management of Construction Safety Standards Based on Knowledge Graphs: A Case Study in China," IJERPH, MDPI, vol. 18(20), pages 1-15, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:20:p:10692-:d:654316
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    References listed on IDEAS

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    1. Jianzhuo Yan & Tiantian Lv & Yongchuan Yu, 2018. "Construction and Recommendation of a Water Affair Knowledge Graph," Sustainability, MDPI, vol. 10(10), pages 1-15, September.
    2. Qi Zhang & Yuanqiao Wen & Chunhui Zhou & Hai Long & Dong Han & Fan Zhang & Changshi Xiao, 2019. "Construction of Knowledge Graphs for Maritime Dangerous Goods," Sustainability, MDPI, vol. 11(10), pages 1-16, May.
    3. Ziwei Xiao & Chunxiao Zhang, 2021. "Construction of Meteorological Simulation Knowledge Graph Based on Deep Learning Method," Sustainability, MDPI, vol. 13(3), pages 1-20, January.
    4. Zhang, Chuan & Romagnoli, Alessandro & Zhou, Li & Kraft, Markus, 2017. "Knowledge management of eco-industrial park for efficient energy utilization through ontology-based approach," Applied Energy, Elsevier, vol. 204(C), pages 1412-1421.
    5. Malerba, Franco & Orsenigo, Luigi, 1996. "Schumpeterian patterns of innovation are technology-specific," Research Policy, Elsevier, vol. 25(3), pages 451-478, May.
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    Cited by:

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    2. Akeem Pedro & Anh-Tuan Pham-Hang & Phong Thanh Nguyen & Hai Chien Pham, 2022. "Data-Driven Construction Safety Information Sharing System Based on Linked Data, Ontologies, and Knowledge Graph Technologies," IJERPH, MDPI, vol. 19(2), pages 1-18, January.
    3. Wenling Liu & Yuexiang Yang & Xinyu Tu & Wan Wang, 2022. "ERSDMM: A Standard Digitalization Modeling Method for Emergency Response Based on Knowledge Graph," Sustainability, MDPI, vol. 14(22), pages 1-18, November.

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