4.7 Article

Semantic framework for interdependent infrastructure resilience decision support

期刊

AUTOMATION IN CONSTRUCTION
卷 130, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.autcon.2021.103852

关键词

Semantic Web; Ontology; Infrastructure systems; Interdependency; Data integration; Resilient decisions

资金

  1. Research Grants Council of the HKSAR Government [17204017, 17203020]

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This paper presents the use of Semantic Web technologies to address the issue of information integration across different infrastructure systems, providing support for resilience decision-making through ontology development, common data formatting, semantic query language retrieval, and rule language reasoning. Experimental results demonstrate that the proposed framework effectively facilitates information integration between diverse infrastructure systems and supports decision-makers.
The increasing need for interdependent infrastructure systems to withstand natural disasters has called for the cocreation of resilience decisions to minimize the impact on society. However, issues related to information integration across different infrastructure systems hamper decision making from a system-to-systems perspective. To resolve this problem, the Semantic Web technologies are presented in this paper to serve four functions: (i) linking cross domains through ontology development to represent different domain knowledge; (ii) integrating multiple-source heterogeneous data by a common data format; (iii) retrieving useful information using semantic query language; and (iv) deriving machine automatic logical reasoning by rule languages and logic engines to provide informed resilience decision making support. The proposed framework is tested by a case scenario involving intertwined drainage-transport-building systems under the influence of urban flooding. The result indicates that the framework effectively facilitates information integration between diverse infrastructure systems and helps decision-makers by providing resilience decision-making support.

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