The vast amount of information generated by domain scientists makes the transitionfrom data to knowledge difficult and often impedes important discoveries. Forexample, the knowledge gained from protein flexibility data sets can speed advancesin ge...
A perennially interesting research topic in the field of visual analytics is how to effectively develop systems that support organizational knowledge worker's decision- making and reasoning processes. The primary objective of a visual analytic sys...
The explosion of large-scale time-varying datasets has created critical challenges for scientists to study and digest. One core problem for visualization is to develop effective approaches that can be used to study various data features and tempor...
Spatiotemporal visual analysis research is rapidly emerging and evolving, as scientists engaging in cross-domain research efforts, introducing novel systems to perform data-driven spatiotemporal analysis in several domains such as astronomy, clima...
Analysts and domain experts in various fields rely on collecting data about their subjects to understand and predict their behavior. Characterizing and modeling human behavior requires analyzing extensive amounts of data from heterogeneous sources...
High-dimensional data becomes common in application areas such as environmental studies and healthcare. The high dimensionality presents opportunities for understanding how certain outcomes happen by identifying significant variables contributing ...
