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Cross Domain Dissemination


OBJECTIVE: Develop and automated means to provide intelligence data with assured and appropriate classification and releasability markings through metadata tagging. This will be used to enhance information sharing between multiple, independent security domains. DESCRIPTION: Automated cross-domain data dissemination is limited by the lack of consistent classification and releasability markings (imagery, signal intelligence (SIGINT), ground moving target indicator (GMTI), etc.) on metadata with integrity seals from sensors. Most Intelligence Surveillance and Reconnaissance (ISR) sensor data have fields which are inconsistently populated hampering sharing and discovery. This can extend the timeline for conducting analysis by requiring the analyst to manually search multiple sources for significant data, evaluate the various information sources to properly assess the situation, and then document and disseminate the findings internally and externally. The ability to generate a capability to mark data based upon mission profile and releasability for all pertinent sensors and generate a modifiable default value that would be used when unmarked data is received is required. Investigate ways through probabilistic methods and/or cloud-based distributed environments to automatically mark the unmarked data based on historical data with high accuracy. Having this capability would enable near real-time and real-time exchange, dissemination, search, access, display and association of disparate information across multiple communities of interest both internal and external to a given analytical organization. Measuring percentage of missing metadata from the document corpus prior to the systems use and after should be documented and measured. Developed prototype solution must leverage metadata tagging standards & tools from within Department of Defense (DoD) and Intelligence Community (IC) where appropriate. PHASE I: Create a prototype to evaluate completeness & correctness of metadata. Automatically add appropriate metadata to close any gaps. Data formats used must be representative of those used in ISR community (provided by Government). Use prototype to check existing data repositories for mis-tagged data. Identify cases where non-standard metadata is used. PHASE II: Test developed tool within sample ISR data repository and identify insufficiently tagged data that would inhibit secure exchange across disparate communities of Interest. Report results of investigation and identify plan for automatic data tagging enhancements for the tool. Report any newly identified cases of proprietary and non-standard data. Enhance prototype to automatically, consistently and appropriately mark existing data that is insufficiently or inappropriately tagged. PHASE III: Develop documentation and training program for this tool, sufficiently demonstrate this tool within a realistic ISR exercise and deploy it within ISR community. REFERENCES: 1. Understanding metadata, NISO Press; 2. DoD Data Services Environment; 3. Geospatial Metadata; 4. GOV standards for geospatial metadata;
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