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

• Main Authors: Jiseong Son, Chul-Su Lim, Hyoung-Seop Shim, Ji-Sun Kang
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Future Internet
• Subjects: knowledge graph; ontology; open dataset; flooding disaster
• Online Access: https://www.mdpi.com/1999-5903/13/5/124

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.