Information analysts, especially those working in the field of intelligence analysis, must assess not only the information presented to them, but the confidence they have in that information. Visual representations of information are challenged to incorporate a notion of confidence or certainty because the factors that influence the certainty or uncertainty of information vary with the type of information and the type of decisions being made. Visualization researchers have no model or framework for describing uncertainty as it relates to intelligence analysis, thus no consistent basis for constructing visualizations of uncertainty. This paper presents a typology describing the aspects of uncertainty related to intelligence analysis, drawing on frameworks for uncertainty representation in scientific computing.
@InProceedings{ thomson:2005:ATUV,
author = {Judi Thomson and Beth Hetzlera and Alan MacEachrenb and Mark Gaheganb and Misha Pavel},
title = {A Typology for Visualizing Uncertainty},
booktitle = {Proceedings of SPIE. Vol. SPIE-5669},
pages = {146--157},
year = {2005},
}
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