Recent uncertainty of human disaster raised necessity for scientific approach for risk assessment and risk management technology to disasters for flexible countermeasures. Future estimation and forecast model is needed to apply in human disasters.
The study purpose is to generate disaster pre-symptom information through data collection and analysis, and to use it to provide appropriate decision making structures.

Input data for Disaster pre-symptom information analysis and decision making process is composed of specific data and general data. The specific data include requirements for facilities and buildings, which include related laws, previous cases, and related expert's opinions. The general data is information of road establishment year, constructor, location information, etc.

B. Process
Composed of three modules; General factor model classified as ontology general factors, indicator calculation module calculated by related rules made of general factors, document generating model that supports decision making process by showing analyzed data input from indicator calculation module.

C. Output
It is linked with disaster pre-symptom related DB system, which deducts five outcomes, which is integrated as the user requests.