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

Abstract

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 ontology-based 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.