Issues of Uncertainty Analysis in High-Level Information Fusion Fusion2012 Panel Discussion

High-Level Information Fusion (HLIF) utilizes techniques from Low-Level Information Fusion (LLIF) to support situation/impact assessment, user involvement, and mission and resource management (SUM). Given the unbounded analysis of situations, events, users, resources, and missions; it is obvious that uncertainty is manifested by the nature of application requirements. In this panel, we seek discussions on methods and techniques to intelligently assess the problem of HLIF uncertainty analysis to alleviate high-performance statistical computational optimizations, unrealizable mathematical assumptions, or rigorous modeling and problem scoping which lead to time delays, brittleness, and rigidity, respectively. Given the various methods of LLIF and the complexity of HLIF, an interest to the ISIF community is to utilize diverse methods (such as those from other communities) that bridge the LLIF-HLIF gap of uncertainty analysis. To get a qualified and diverse viewpoint, we present a summary of HLIF uncertainty processes towards developing a multisource ontology of uncertainty to support HLIF modeling, methods, and management and systems design.