Evaluating and Visualizing Uncertainty in Cultural Data
Diana Stuart Sinton, Ph.D.
Mark P. Kumler, Ph.D.
The United States military operates in areas throughout the world, and knowledge about the ethnicity, religion, and languages spoken by people who occupy these areas is critical context for soldiers and marines. This type of cultural data varies region-by-region and is dynamic. Mixing among and between groups and gradual transitions between concentrations of cultural traits are common. Yet, the regions themselves are typically represented as polygons on maps, with definite and absolute borders or edges. The existing variability between and among groups is lost, and instead the depictions suggest absolute certainty. Analysts support the military needed methods to evaluate and visualize cultural data and share its complexities, but there were no automated tools available for dealing with these phenomena in ArcMap. The project addressed this issue by creating and organizing a set of tools that automated workflows for depicting confidence evaluations and uncertainty in cultural data. From seven initial and different approaches, four capabilities were ultimately consolidated into an ArcMap toolbar: a confidence analysis, a quad viewer, a fuzzy boundary representation, and similarity grouping.
McCarron, A. (2010). Evaluating and Visualizing Uncertainty in Cultural Data (Master's thesis, University of Redlands). Retrieved from https://inspire.redlands.edu/gis_gradproj/123