STAFF: Semantic Targeting and All-source Fusion Framework

Modus Operandi proposes the development of the Semantic Targeting and All-source Fusion Framework (STAFF), an innovative, net-centric framework for fusing human intelligence (HUMINT), video and imagery intelligence (IMINT), signals intelligence (SIGINT), and other intelligence data for high-value entity (HVE) targeting. STAFF leverages text analytics and semantic technologies to identify, extract and model entities, relationships and events depicted in unstructured information such as intelligence reports, news stories and web pages, and in the metadata of other intelligence types. STAFF also has access to structured data from the Combined Information Data Network Exchange (CIDNE), which is the US Central Command (CENTCOM) directed reporting tool for the majority of operational reporting within Afghanistan and Iraq. This combined information is semantically enriched and processed for use by warfighters and analysts to rapidly build comprehensive threat target packages, which can then be disseminated as auto-generated briefings or as highly-linked information within a feature-rich targeting tool. STAFF and the targeting tool will significantly reduce intelligence analyst workload and improve tipping and targeting effectiveness within the DCGS-N and other DCGS Programs.