Information Quality Assurance Models for Experts Assessing in Disaster Management

Disaster management depends on large volumes of comprehensive, accurate, relevant, on-time information that various organizations systematically create and maintain. One cannot assure information quality (IQ) without first being able to measure it meaningfully and establishing a causal connection between the source of change, the problem types, the types of activities affected, and their implications. In this paper we propose a model that can manage heterogeneous data and provide functions to support expert experts in the assessment of the fitness for use of given information. In contrast to other assurance approaches, this approach provides interactive, multi-granularity and context-sensitive IQ indicators that help experts to build and justify their opinions. The prototype system was designed and validated by enhancing IQ generated by remote sensing through the technologies of visualization.