Analytics for Data Deconfliction
Analytics for Data Deconfliction

Summary/Abstract: This paper introduces a refactoring of the concept called “deconfliction” as it applies to analytical and data repositories deployed throughout the law enforcement and intelligence communities. The goal is to seamlessly and automatically identify similar targets of interest (e.g., people, places, etc.) from the queries and reports being generated by the analysts, agents, and end-users operating these systems. The similarities represent the underpinnings for a number of requirements, including more efficient utilization of resources, improved analytical support mechanisms, a foundation for information sharing functions, as well as internal controls to help minimize abuses related to data privacy concerns. The application of data deconfliction is quickly becoming a mainstream capability and closely parallels the adoption of more information exchange standards. This paper discusses several methods and issues related to the emergence of data deconfliction activities.

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