An analytic framework fo space-time aberrancy detection in public health surveillance data.

Public health surveillance is changing in response to concerns about bioterrorism, which have increased the pressure for early detection of epidemics. Rapid detection necessitates following multiple non-specific indicators and accounting for spatial structure. No single analytic method can meet all of these requirements for all data sources and all surveillance goals. Analytic methods must be selected and configured to meet a surveillance goal, but there are no uniform criteria to guide the selection and configuration process. In this paper, we describe work towards the development of an analytic framework for space-time aberrancy detection in public health surveillance data. The framework decomposes surveillance analysis into sub-tasks and identifies knowledge that can facilitate selection of methods to accomplish sub-tasks.

Protégé-2000: an open-source ontology-development and knowledge-acquisition environment.

Protégé-2000 is an open-source tool that assists users in the construction of large electronic knowledge bases. It has an intuitive user interface that enables developers to create and edit domain ontologies. Numerous plugins provide alternative visualization mechanisms, enable management of multiple ontologies, allow the use of interference engines and problem solvers with Protégé ontologies, and provide other functionality. The Protégé user community has more than 7000 members.

BioSTORM: a system for automated surveillance of diverse data sources.

Heightened concerns about bioterrorism are forcing changes to the traditional biosurveillance-model. Public health departments are under pressure to follow multiple, non-specific, pre-diagnostic indicators, often drawn from many data sources. As a result, there is a need for biosurveillance systems that can use a variety of analysis techniques to rapidly integrate and process multiple diverse data feeds using a variety of problem solving techniques to give timely analysis. To meet these requirements, we are developing a new system called BioSTORM (Biological Spatio-Temporal Outbreak Reasoning Module).