How not to lie with visualization
Computers in Physics
External memory algorithms
Large networks present visualization challenges
ACM SIGGRAPH Computer Graphics
Hierarchical geometric models for visible surface algorithms
Communications of the ACM
Exploring Large Graphs in 3D Hyperbolic Space
IEEE Computer Graphics and Applications
Dynamic Aggregation with Circular Visual Designs
INFOVIS '98 Proceedings of the 1998 IEEE Symposium on Information Visualization
NicheWorks - Interactive Visualization of Very Large Graphs
GD '97 Proceedings of the 5th International Symposium on Graph Drawing
Balanced Aspect Ratio Trees and Their Use for Drawing Very Large Graphs
GD '98 Proceedings of the 6th International Symposium on Graph Drawing
Multilevel Visualization of Clustered Graphs
GD '96 Proceedings of the Symposium on Graph Drawing
A rule-based tool for assisting colormap selection
VIS '95 Proceedings of the 6th conference on Visualization '95
Navigating large networks with hierarchies
VIS '93 Proceedings of the 4th conference on Visualization '93
Visual exploration of large data sets
Communications of the ACM
MGV: A System for Visualizing Massive Multidigraphs
IEEE Transactions on Visualization and Computer Graphics
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
Case Study: E-Commerce Clickstream Visualization
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
Proceedings of the Working Conference on Advanced Visual Interfaces
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We describe MGV, an integrated visualization and exploration system for massive multi-digraph navigation. MGV's only assumption is that the vertex set of the underlying digraph corresponds to the set of leaves of a predetermined tree T. MGV builds an out-of-core graph hierarchy and provides mechanisms to plug in arbitrary visual representations for each graph hierarchy slice. Navigation from one level to another of the hierarchy corresponds to the implementation of a drill-down interface. In order to provide the user with navigation control and interactive response, MGV incorporates a number of visualization techniques like interactive pixel-oriented 2D and 3D maps, statistical displays, multi-linked views, and a zoomable label based interface. This makes the association of geographic information and graph data very natural. MGV follows the client-server paradigm and it is implemented in C and Java-3D. We highlight the main algorithmic and visualization techniques behind the tools and point out along the way several possible application scenarios. Our techniques are being applied to multi-graphs defined on vertex sets with sizes ranging from 100 million to 250 million vertices.