Maintaining knowledge about temporal intervals
Communications of the ACM
Ontology-Centered Syndromic Surveillance for Bioterrorism
IEEE Intelligent Systems
Extending the event calculus for tracking epidemic spread
Artificial Intelligence in Medicine
ACM SIGKDD Explorations Newsletter
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Surveillance applications to monitor health-related data have matured rapidly over the last several years. A newly emerging development is an emphasis on harvesting and evaluating the timely but potentially inaccurate information present in unstructured sources such as Internet news feeds and sites. An important development for the surveillance on both structured and unstructured datasets is the exchange not of the primary datasets that feed these systems, but of the evaluated results of such analysis. This paper introduces recent work addressing a model for the recording and tracking of events and for the dissemination of information about these events to other agencies. It will introduce a structured relational database model for events, an ontology for infectious disease events, and a semantic web representation. The strengths and weaknesses of the three approaches and future directions will be discussed.