Background In Japan, the National Institute of Technology and Evaluation (NITE) has done a lot of work collecting consumer product injury data to prevent accidents. However, a wealth of narrative data is still available within the collection system, which needs to be interpreted by safety experts.

Objective This paper describes the initial approach that combined ontology with the network analysis method to quickly and efficiently provide injury prevention experiences for data learning.

Methods A sample of 1221 carrying device-related injuries in preschool children from the NITE collection system was used in the study. Based on injury process description ontology (IPD-Onto), the narrative injury data were represented as a graph with the safety expert’s interpretation in a machine-readable format. An open graph platform, Gephi, was used to represent and understand injury processes, network graph analysis and visualization.

Results The results of the analysis show that the ontology-based network graph analysis could give a better understanding of the injury mechanism, which helps quickly identify the essential nodes and bridges in different risk scenarios.

Conclusions This provides a computer-assisted processing bridge between narrative injury data and graph analysis methods. It also demonstrates a possible approach to injury prevention decision-making from the perspective of safety theory, including the perspective of the Safety-I and Safety-II.