Shenghui Cheng

Learn More
The interface of our system demonstrating the linked display functionality – the highlighted parts are linked with the chosen area. ABSTRACT Contextual layouts preserve the context of the data with the associated attributes (variables). However, their linear mapping causes errors in the layout – similar data points and variable nodes may not map to similar(More)
A concept of shape coordinates system for visualization of data set is proposed in this paper. First, the visualization data set, visualization graphics, visualization process and visualization space are defined. Then, the definition, mapping, operation, theorems, properties and algorithms of shape coordinates system are described. Finally an example to(More)
Figure 1: Block diagram of the workflow in our MemViz tool. ABSTRACT Our paper describes a framework that aids users in the creation of data visualizations augmented with chart junk. Chart junk refers to graphical decorations that are irrelevant to the data, but are meant to make the data graphics more interesting, giving rise to visualizations with low(More)
Numerous methods have been described that allow the visualization of the data matrix. But all suffer from a common problem - observing the data points in the context of the attributes is either impossible or inaccurate. We describe a method that allows these types of comprehensive layouts. We achieve it by combining two similarity matrices typically used in(More)
In streaming acquisitions the data changes over time. ThemeRiver and line charts are common methods to display data over time. However, these methods can only show the values of the variables (or attributes) but not the relationships among them over time. We propose a framework we call StreamVis ND that can display these types of streaming data relations.(More)
Fig. 1. Each column shows a MDS-plot of feature vectors that describe the local neighborhood structure of the nodes in the TWITTER network (top) and a force-directed network layout of the same network (bottom). Colors correspond to a k-means clustering for k = 3 or 4 (right) on the local feature vectors. Abstract—Network exploration techniques aim at(More)
— Torus networks are widely used in supercomputing. However, due to their complex topology and their large number of nodes, it is difficult for analysts to perceive the messages flow in these networks. We propose a visualization framework called TorusVis ND that uses modern information visualization techniques to allow analysts to see the network and its(More)