SECURBORATION, INC. — Department of Defense SBIR Phase II: AF121-050

Description

ABSTRACT: Coordination, collaboration and integration across the many elements of the S&T community are critical to the success of the overarching joint planning and coordination process. Responding to expectations, queries or findings requires: alignment of the context to ongoing initiatives; a determination of the relevance to Research and Development (R&D) specifically; and discovery, representation and delivery of data that support informed decision-making. These activities are often executed by cross-organizational Communities of Interest (COI) that are organized and managed by the Reliance 21 initiative. Specific deliverables of COIs are 10-year R&D plans, roadmaps and portfolio reviews. Data sources used to produce these artifacts come from many authoritative sources and are both structured and unstructured. Semantic Services for Enterprise Analytics (SSEA) will enable ASD (R&E) to exploit semantic technologies and standards to support its mission as the authoritative source of information regarding ongoing activities within the R&D community. The proposed SSEA work in this document will encompass direct support to the diverse range of COIs in the preparation of their R&E roadmaps. The Command, Control, Comms, Computers and Intelligence (C4I) COI has been identified as an early adopter and we will begin SSEA efforts in collaboration with this COI. BENEFIT: Benefits to the Air Force parallel those to ASD(R&E), as Air Force is an active participant in critical R&E resources such as DTICs Unified Research and Engineering Database (URED). Air Force laboratories and strategic planners will all have access to the SSEA analytic and information discovery capabilities described here. These capabilities significantly automate large amounts of currently manual hunt-and-peck and sifting and sorting operations undertaken for multiple reporting and planning activities. SSEA greatly increases the ability of analysts to process massive amounts of structured and unstructured information through: Automated tagging of data with domain-relevant vocabulary. Organizing datasets for relevance ranking and navigation. Producing machine-executable representations of Critical Information Requirements. Extracting specific information from large volumes of text. Delivering decision support information to knowledge workers.