Abstract: A machine-implemented Case-Managed ontology and decision support framework provides a basis for a family of machine database architectures for use in a system for countering forces of unknown intentions including fighting and winning the Global War on Terror. The system focuses resource allocation decisions on logically derived, targeted areas of interest with an emphasis on non-kinetic, non-destructive effects. The system combines proven doctrines and novel operational approaches. It employs readily available intelligence information, an ontological understanding of the problem domain, a three-level, metrics-driven, case-managed system and process to counter the forces of unknown origin, and an entire set of operational level activities combining strategic intent, tactical approaches, expected utility analysis, mission-level simulations, and integrated cost modeling.

Abstract: A machine-implemented Case-Managed ontology and decision support framework provides a basis for a family of machine database architectures for use in a system for countering forces of unknown intentions including fighting and winning the Global War on Terror. The system focuses resource allocation decisions on logically derived, targeted areas of interest with an emphasis on non-kinetic, non-destructive effects. The system combines proven doctrines and novel operational approaches. It employs readily available intelligence information, an ontological understanding of the problem domain, a three-level, metrics-driven, case-managed system and process to counter the forces of unknown origin, and an entire set of operational level activities combining strategic intent, tactical approaches, expected utility analysis, mission-level simulations, and integrated cost modeling.