Visualizing the evolution of Web ecologies
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Interactive visualization of serial periodic data
Proceedings of the 11th annual ACM symposium on User interface software and technology
Visualizing the evolution of a subject domain: a case study
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
Visualization of bibliographic networks with a reshaped landscape metaphor
VISSYM '02 Proceedings of the symposium on Data Visualisation 2002
Animated Exploration of Dynamic Graphs with Radial Layout
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
An explanation-based, visual debugger for one-way constraints
Proceedings of the 17th annual ACM symposium on User interface software and technology
prefuse: a toolkit for interactive information visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A system for visualizing and analyzing the evolution of the web with a time series of graphs
Proceedings of the sixteenth ACM conference on Hypertext and hypermedia
IdeaCrepe: creativity support tool with history layers
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
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We propose a "layered structured network diagram," which consists of layers of time differences. We have implemented a tool called "NeL2 " for handling layered structured network diagrams. Layered structured network diagrams have multiple accumulated layers and are not single diagrams. Using this layered structure, time differences can be included in one diagram. In addition, various type of information, such as the overall tendency in a diagram during a specific period of time, can be visualized.We used layered structured network diagrams to show the co-authorship network of academic literature. Changes in the co-authorship network become visible using the layered structured network diagram. We can read various information such as changes of active research communities and other phenomena. In addition to co-authorship networks, the layered structured network diagram can be applied to the visualization of various data, such as idea processors, changes of Web sites, and others.