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dc.contributor.authorGilfeather, Frank
dc.contributor.authorCaudell, Thomas
dc.contributor.authorTaha, Mahmoud
dc.contributor.authorWeinberg, David
dc.date.accessioned2011-09-19T20:28:50Z
dc.date.available2011-09-19T20:28:50Z
dc.date.issued2011-09-19
dc.identifier.urihttp://hdl.handle.net/1928/13956
dc.descriptionTechnical Reporten_US
dc.description.abstractPolicy leaders have identified a need for a mathematical based computational system that would support requirements of situational awareness to analyze terrorist threats and risks given the vast amount of input data in the form of open source, intelligence as well as other indicators. In response to these expressed needs , the University of New Mexico (UNM) developed a proto-type system, the Pre Incident Indicator Analysis (PIIA) system, which is capable of combining open source and intelligence data with other indicators and information as inputs to provide a dynamic assessment of threats and risks along with a measure of the uncertainties inherent in that analysis. The object is to build a mathematical and then a prototype system to access large complex “faceted information ontologies” consisting of information and data available to analysts and in a fashion they can use. A framework has been established for such a system and demonstrated. In addition considerable progress has been made on the key challenge of creating faceted ontologies (combining specific views of data and information). This constitutes a data collection system that combines specific views or ontologies, allows for analyzing the integrated information and then ascertaining certain new views of the resultant information. This has the potential to evaluate specific threats for importance, provide temporal sensitivity and provide warnings for analysts to consider.en_US
dc.description.sponsorshipDefense Threat Reduction Agency and The Departmentof Homeland Security, Office of Risk Management Analysisen_US
dc.language.isoen_USen_US
dc.relation.ispartofseriesECE;EECE-TR-1-0008
dc.subjectRisk Analysisen_US
dc.subjectEvidence Theoryen_US
dc.subjectInformation Aggregationen_US
dc.subjectTree Visualizationen_US
dc.subjectSituational Awarenessen_US
dc.titlePre Incident Indicator Analysis (PIIA) Systemen_US
dc.typeArticleen_US


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