Ontological Considerations for Uncertainty Propagation in High Level Information Fusion

Uncertainty propagation in a level 2 high level information fusion (HLIF) process is affected by a number of considerations. These include the varying complexities of the various types of level 2 HLIF. Five different types are identified, ranging from simple entity attribute refinement using situation status data to the development of a complete situation assessment assembled from applicable situational fragment data. Additional considerations include uncertainty handling in the input data, uncertainty representation, the effects of the reasoning technique used in the fusion process, and output considerations. Input data considerations include the data’s relevance to the situation, its credibility, and its force or weight. Uncertainty representation concerns follow the uncertainty ontology developed by the W3C Incubator Group on Uncertainty Reasoning. For uncertainty effects of the fusion process, a basic fusion process model is presented, showing the impacts of uncertainty in four areas. Finally, for output uncertainty, the significance of a closed-world versus open-world assumption is discussed.