The amount of network-centric data from repositories, sensors, and human inputs has created significant problems that impede the effective organization of this data into actionable knowledge that can improve situation awareness and, ultimately, mission performance. Many technologies, for instance, databases and on-line mapping, have been designed to manage this information for specific task sets. However these technologies are difficult to apply broadly because the analysis tools embed a particular command intent related to the way information is organized and processed. Moreover they make this process opaque creating a host of human factors problems. This proposal describes the Search Agents and Tools for Intelligent Net-centric Operations (SATIN) concept for the development of a knowledge management based decision support system. SATIN allows the operator to incorporate his CONOPS and commanders intent in interfaces designed to minimize cognitive workload and maximize situational awareness. SATIN will leverage an advanced filtering, fusion, and analysis (FFA) system based on a cloud-computing paradigm for processing the net-centric data sources to reduce extraneous information. It also uses advanced human interface technologies including Recognition-Primed Decision Making (RPDM) and Visual Thinking (VT) concepts to present relevant data to the human operator maximizing ease of comprehension and control.
Keywords: Knowledge Management Situational Awareness Cognitive Workload Net-Centric Operations Cloud Computing Data Fusion Recognition-Primed Decision Making Visual Thinking Se
