IEEE TVCG Special Session on Visualization

Sunday, 9 August, 9 - 10:30 am, Room 402AB
Session Chair: Charles Hansen, University of Utah

ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery
Large-scale data analysis is a crucial part of drug discovery. ConTour is an interactive visual-analytics technique that enables exploration of these complex, multi-relational datasets. This talk presents case studies conducted with a team of chemical biologists who investigate the effects of chemical compounds on cells and need to understand the underlying mechanisms. 

Christian Partl
Technische Universität Graz
Alexander Lex
Harvard University
Marc Streit
Johannes Kepler Universität Linz
Hendrik Strobelt
Harvard University
Anne-Mai Wassermann
Novartis Institutes for BioMedical Research
Hanspeter Pfister
Harvard University
Dieter Schmalstieg
Technische Universität Graz

Learning Perceptual Kernels for Visualization Design
Visualization design can benefit from careful consideration of perception, as different assignments of visual encoding variables such as color, shape, and size affect how viewers interpret data. This talk introduces perceptual kernels: distance matrices derived from aggregate perceptual judgments.

Cagatay Demiralp
Michael S. Bernstein
Stanford University
Jeffrey Heer
University of Washington

Trajectory-Based Flow Feature Tracking in Joint Particle/Volume Datasets
Studying the dynamic evolution of time-varying volumetric data is essential in countless scientific endeavors. This talk presents a new trajectory-based feature-tracking technique for use in joint particle/volume datasets and demonstrates the effectiveness of this technique using real-world combustion and atmospheric datasets.

Franz Sauer
University of California, Davis
Hongfeng Yu
University of Nebraska
Kwan-Liu Ma
University of California, Davis

Visualization of Brain Microstructure Through Spherical-Harmonics Illumination of Spatio-Angular Fields
Diffusion kurtosis imaging (DKI) data, which have high-fidelity spatio-angular fields, are difficult to visualize. This talk presents a systematic way to manage, analyze, and visualize high-fidelity spatio-angular fields from DKI datasets by using spherical-harmonics lighting functions to facilitate insights into the brain microstructure. 

Sujal Bista
University of Maryland, College Park
Jiachen Zhuo
Rao P. Gullapalli
University of Maryland School of Medicine
Amitabh Varshney
University of Maryland, College Park