This session will provide an overview of uncertainty visualization. It will provide some historical perspective, early developments within the visualization community, and discuss some current and future directions for research. The tutorial will cover how uncertainty is represented and corresponding techniques and strategies for mapping uncertainty information to visual parameters.

We will start off with scalar representations of uncertainty and progress towards cases where uncertainties are represented together with the data as distributions – and present different ideas for presenting these types of information.

• Motivation and Introduction
• Historical review of uncertainty visualization
• Visualization of uncertainties quantified as scalar values
• Visualization of uncertainties quantified as range values
• Visualization of uncertainties quantified as distributions
• Open problems

• Overview of uncertainty representation and visualization
• Techniques and strategies for uncertainty visualization
• Historical perspective

• Alex Pang, Craig Wittenbrink, and Suresh Lodha, ``Approaches to Uncertainty Visualization'', The Visual Computer, Vol. 13, No. 8, 1997, pp. 370--390.
• Suzana Djurcilov, Kwansik Kim, Pierre Lermusiaux, and Alex Pang, ``Visualizing Scalar Volumetric Data with Uncertainty'', Computers and Graphics, volume 26, number 2, 2002, pp. 239--248.
• Alison Luo, David Kao and Alex Pang, ``Visualizing Spatial Distribution Data Sets'', VisSym'03, Joint Eurographics - IEEE TCVG Symposium on Visualization, May 2003, pp. 29--38, 238.
• Nathaniel Cesario, Alex Pang, and Lisa Singh, ``Visualizing Node Attribute Uncertainty in Graphs'', SPIE Proceedings on Visualization and Data Analysis (VDA), volume 7868, pp. 78680H--78680H-13, 2011, San Francisco, CA.

University of California, Santa Cruz

Alex Pang is a Professor of Computer Science at UC Santa Cruz. He received his PhD in Computer Science from UCLA in 1990, and his BS in Industrial Engineering from University of the Philippines with magna cum laude in 1981. His research interests are in comparative and uncertainty visualization, flow and tensor visualization, and collaborative visualization. His research has been supported by various funding agencies such as NSF, ONR, Darpa, DOE, LANL, and NASA, as well as industrial partners such as Sun and HP. Professor Pang has received a certificate of recognition for previous NASA work, as well as an excellence in teaching award from UCSC. He served as an associate editor of the IEEE Transactions on Visualization and Computer Graphics, papers co-chair for IEEE Visualization 2006 and 2007, and UCSC Chief Scientist for CITRIS during 2006 and 2007.