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Management in mass gatherings is a complex process that consists of three major phases: planning, operational response, and debriefing. Each of these phases involves information exchange between different agencies involved in planning and running the event. It has been widely recognized that the data quality and access to critical information impact on the efficiency of the response and overall effectiveness of the emergency management. Therefore, there is a need for solid understanding of the information needs of the agencies pertinent to designing efficient decision support systems, which are truly integrated into the context of business environment and facilitate IT-enabled work of the personnel organizing and running mass gathering events. Introduction of such ubiquitous systems depends on availability of ontology of the problem domain, which provides a common ground for information integration, gathering and exchange. We propose a conceptual architecture for ontology-based, IT-enabled decision support that extends to all phases of mass gatherings. As an example, we describe a case-based reasoning (CBR) system which takes advantage of such an ontology and ontology reasoning and can be used for prediction of medical workload and providing better understanding of mass gathering events during planning or training of new staff.
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