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Development of Knowledge Graph for Data Management Related to Flooding Disasters Using Open Data

Author

Listed:
  • Jiseong Son

    (Korea Institute of Science and Technology Information, Daejeon 34141, Korea)

  • Chul-Su Lim

    (Korea Institute of Science and Technology Information, Daejeon 34141, Korea)

  • Hyoung-Seop Shim

    (Korea Institute of Science and Technology Information, Daejeon 34141, Korea)

  • Ji-Sun Kang

    (Korea Institute of Science and Technology Information, Daejeon 34141, Korea)

Abstract

Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we must focus on these various data. Disaster data depend on the domain by disaster type and include heterogeneous data and lack interoperability. In particular, in the case of open data related to disasters, there are several issues, where the source and format of data are different because various data are collected by different organizations. Moreover, the vocabularies used for each domain are inconsistent. This study proposes a knowledge graph to resolve the heterogeneity among various disaster data and provide interoperability among domains. Among disaster domains, we describe the knowledge graph for flooding disasters using Korean open datasets and cross-domain knowledge graphs. Furthermore, the proposed knowledge graph is used to assist, solve, and manage disaster problems.

Suggested Citation

  • Jiseong Son & Chul-Su Lim & Hyoung-Seop Shim & Ji-Sun Kang, 2021. "Development of Knowledge Graph for Data Management Related to Flooding Disasters Using Open Data," Future Internet, MDPI, vol. 13(5), pages 1-9, May.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:5:p:124-:d:552339
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