Information management and decision support in critical infrastructure emergencies at the local level

In a critical infrastructure disaster incident, emergency managers are often compelled to make time-critical decisions based on incomplete information streaming in at disparate times from multiple data sources. As the incident progresses, the ability to predict where additional resources will be needed is crucial to both response and recovery. Decision making and prediction in this context requires combining (fusing) incoming data streams; presenting relevant information from these streams in a form appropriate for each user; and using data from similar historical events to predict resource needs and incident evolution. This paper discusses the role of data fusion, data integration, and data mining in decision making for municipal or regional emergency managers. It also explores the implementation of web-based decision support tools. Finally, the paper makes recommendations for improving information management and streamlining decision support.