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ERSDMM: A Standard Digitalization Modeling Method for Emergency Response Based on Knowledge Graph

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  • Wenling Liu

    (School of Management, China University of Mining and Technology (Beijing), Beijing 100083, China)

  • Yuexiang Yang

    (School of Management, China University of Mining and Technology (Beijing), Beijing 100083, China)

  • Xinyu Tu

    (School of Management, China University of Mining and Technology (Beijing), Beijing 100083, China)

  • Wan Wang

    (Sub-Institute of Public Safety Standardization, China National Institute of Standardization, Beijing 100191, China)

Abstract

Standard digitalization is a crucial step in social and economic development and the transformation of digital technology. Standard digitalization is of great significance in the promotion of sustainable economic and social development. This paper proposes a standard digitalization modeling method for emergency response (ERSDMM) based on knowledge graph (KG). Firstly, this paper analyzes the knowledge structure of emergency response standards (ERS) and constructs a “seven-dimensional” model of ERS based on the public safety triangle theory. An ontology model of the emergency response domain is then created. Secondly, ERS and emergency scenario fine-grained knowledge are extracted. Thirdly, a standard reorganization model is constructed to meet the needs of the scenario response. Finally, the ERSDMM is applied to the GB 21734-2008, which proves that the ERSDMM is available. Taking RES as an example, this paper explores the path and practice of standard digitalization. ERSDMM solves standards-related problems, such as overlapping content, coarse knowledge granularity, incomplete coverage of elements, and difficulty in acquiring knowledge.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14975-:d:970792
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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.
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    3. 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.
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