For displaying a dense graph, an adjacency matrix is superior than a node-link diagram because it is more compact and free of visual clutter. A node-link diagram, however, is far better for the task of path finding because a path can be easily traced by following the corresponding links, provided that the links are not heavily crossed or tangled.We augment adjacency matrices with path visualization and associated interaction techniques to facilitate path finding. ...

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively ...

User studies, evaluations, and comparisons of tree visualization systems have so far focused on questions that can readily be answered by simple, automated queries without needing visualization. Studies are lacking on the actual use of tree visualization in discovering intrinsic, hidden, non-trivial and potentially valuable knowledge. We have thus formulated a set of tree exploration tasks not previously considered and have performed user studies and analysis to determine how visualization helps users to perform these tasks ...

The InfoVis 2004 contest led to the development of several bibliography visualization systems. Even though each of these systems offers some unique views of the bibliography data, there is no single best system offering all the desired views. We have thus studied how to consolidate the desirable unctionalities of these systems into a cohesive design. We have also designed a few novel visualization methods ...

We present a strategy for analyzing large, social small-world graphs, such as those formed by human networks. Our approach brings together ideas from a number of different research areas, including graph layout, graph clustering and partitioning, machine learning, and user interface design. It helps users explore the networks and develop insights concerning their members and structure that may be difficult or impossible to discover via traditional means, including existing graph visualization and/or statistical methods ...

Graph and tree visualization techniques enable interactive exploration of complex relations while communicating topology. However, most existing techniques have not been designed for situations where visual information such as images is also present at each node and must be displayed. This paper presents MoireGraphs to address this need. MoireGraphs combine a new focus+context radial graph layout with a suite of interaction techniques (focus strength changing, radial rotation, level highlighting, secondary foci, animated transitions and node information) to assist in the exploration of graphs with visual nodes ...

Decision trees are commonly used for classification. We propose to use decision trees not just for classification but also for the wider purpose of knowledge discovery, because visualizing the decision tree can reveal much valuable information in the data. We introduce PaintingClass, a system for interactive construction, visualization and exploration of decision trees. PaintingClass provides an intuitive layout and convenient navigation of the decision tree ...

We present RINGS, a technique for visualizing large trees with hundreds of thousands of nodes. We introduce a new ringed circular layout of nodes to make more efficient use of limited display space. RINGS provides the user with the means to specify areas of primary and secondary focus, and is able to show multiple foci without compromising understanding of the graph ...