This SGER project is concerned with incorporating uncertainty information into visualization to make the visualization trustworthy. We will study uncertainty information introduced particularly in the process of data analysis and visualization, and develop methods for working with uncertainty at all stages of the data visualization pipeline, including not only the visualization of data in the presence of uncertainty, but also visualization methods that provide insight into the nature of the uncertainty itself to assist in the development of improved experimental designs. The benefits of this research have the potential to provide fundamental improvements in the ability to understand and make decisions based on data with uncertainty. The main objective of this SGER project is to set a foundation for extensive research. In this one-year project we will first study and model the perception uncertainty and ambiguity of 2D visualizations of 3D or high-dimensional data in order to create refined visualizations that are less ambiguous. The proposed research is unique and ambitious because we attempt to effectively incorporate uncertainty information into visualization and data understanding by considering both the nature and effect of uncertainty in the human cognition context as well as representative application contexts.
