Background

Uncertainty information is an important characteristic associated with much of the data scientists encounter. While such uncertainty information is often available, incorporating uncertainty into visualization techniques has proved challenging. This paper presents novel visualization approaches for a class of uncertainty data that is generated from the sensitivity analysis of electrical conductivity within a model of bioelectric fields from the heart. The data can be characterized as a set of probability density functions (PDFs) defined across a triangular mesh; however, we are also interested in the relationship between input and output parameters of the sensitivity analysis. This increases the complexity of the data set and motivates a visualization approach that provides for exploration of the data set.

Associated publications

Towards the Visualization of Multi-Dimensional Stochastic Distribution Data K. Potter, J. Krüger, C.R. Johnson, Proceedings of The International Conference on Computer Graphics and Visualization (IADIS) 2008 [Bibtex]