Automated Assessment of Joint Training and Education

Period of Performance: 03/09/2006 - 03/09/2007

$98.6K

Phase 1 SBIR

Recipient Firm

Spec OPS
325 Hill Carter Parkway
Ashland, VA 23005
Principal Investigator

Abstract

The technical challenge of this SBIR is to research and develop a capability which will maximize knowledge derivation from joint force training and operational events to positively affect operational readiness from experiences encountered in operational, training and experimental environments. We put forth the technical solution for application to this complex situation as "Knowledge Discovery from separate heterogeneous data and information sources." Strategic to operational to tactical military operations requires not only the networking of data but the communication of information for knowledge derivation to allow effective decision making at all levels of command. Operational readiness can be subjectively and objectively measured through the use of automated measures of effectiveness and measures of performance. Automation of these measures is now needed to support the vast amount of information available with the use of network centric operations. Distributed Knowledge Networks (DKNs) provides the key enabling technology for translating recent advances in automated data acquisition, digital storage, computers and communications into fundamental advances that support data analysis and knowledge derivation in complex systems. DKNs include computational tools for accessing, organizing, transforming, assimilating, and discovering knowledge from heterogeneous, distributed, possibly mobile, data and knowledge sources.