Fine-Grained Ontology Reconstruction for Crisis Knowledge Based on Integrated Analysis of Temporal-Spatial Factors

Previous studies on crisis knowledge organization mostly focused on the categorization of crisis knowledge without regarding its dynamic trend and temporal-spatial features. In order to emphasize the dynamic factors of crisis collaboration, a fine-grained crisis knowledge model is proposed by integrating temporal-spatial analysis based on ontology, which is one of the commonly used methods for knowledge organization. The reconstruction of ontologybased crisis knowledge will be implemented through three steps: analyzing temporal-spatial features of crisis knowledge, reconstructing crisis knowledge ontology, and verifying the temporal-spatial ontology. In the process of ontology reconstruction, the main classes and properties of the domain will be identified by investigating the crisis information resources. Meanwhile the fine-grained crisis ontology will be achieved at the level of characteristic representation of crisis knowledge including temporal relationship, spatial relationship, and semantic relationship. Finally, we conducted case addition and system implementation to verify our crisis knowledge model. This ontology-based knowledge organization method theoretically optimizes the static organizational structure of crisis knowledge, improving the flexibility of knowledge organization and efficiency of emergency response. In practice, the proposed fine-grained ontology is supposed to be more in line with the real situation of emergency collaboration and management. Moreover, it will also provide the knowledge base for decision-making during rescue process.