Risk identification in Japanese consumer product injury data throughout an ontology-based knowledge base

Xiaodong Feng, Kun Zhang, Fang Jiang and Yoshiki Mikami

Journal of Risk Research, 2024, vol. 27, issue 4, 541-561

Abstract: Risk identification and further risk assessment of consumer product injury data are critical tools for accident prevention. However, in Japan, existing risk assessment methods face challenges due to issues such as inconsistent semantic understanding of risk-related vocabulary among Japanese analysts, posing obstacles to the effective identification and assessment of risk information. This study develops an ontology-based knowledge base (JCPRI-KB), which includes an ontology (JCPRI-Onto) and a total of 41 standardised vocabulary sets, for the risk information identification and standardization of consumer product injury data in Japan. A graph database was used to represent and store the risk knowledge of JCPRI-KB. Finally, the JCPRI-KB is applied for a case study of risk identification and further risk assessment of child product injury data. The risk assessment results of this study demonstrate that the JCPRI-KB offers a promising new approach to the field of consumer product safety in Japan, contributing to the enhancement of accuracy and efficiency in risk identification and thus promoting consumer product safety.

Date: 2024
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DOI: 10.1080/13669877.2024.2387334

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