How to integrate open source resource to assess risk in emergency management: a framework and applications

The unconventional emergency, such as massive natural disaster, public health, food safety and social security incident, usually outbreak more suddenly, diffused more quickly, cause more secondary damage and derive more disaster and with fewer omens exceeding what it is expected. It needs a large number of environmental, social and economic development data to assess the risk when emergency happen. However, the conventional risk assessment is carried out mainly through the analysis of geographic data and non-geographic data released by officials. In this paper, we propose an emergency risk assessment framework using the open source data. Our proposed framework includes five sections: Automatic Data Discovery, Data Organization, Computing resource calling, Model selection and Visualization. The process of data discovery and organization can be done automatically. Distributed computing resources are used and users can select the spatial analysis models interactively for prediction and visualization. The infection disease example is implemented using the proposed framework and verifies the effectiveness and efficiency of our framework.