Cone Trees: animated 3D visualizations of hierarchical information
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Graph Drawing: Algorithms for the Visualization of Graphs
Graph Drawing: Algorithms for the Visualization of Graphs
Multilevel Visualization of Clustered Graphs
GD '96 Proceedings of the Symposium on Graph Drawing
Research report: Interacting with huge hierarchies: beyond cone trees
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
Visualization of State Transition Graphs
INFOVIS '01 Proceedings of the IEEE Symposium on Information Visualization 2001 (INFOVIS'01)
Dynamic Drawing of Clustered Graphs
INFOVIS '04 Proceedings of the IEEE Symposium on Information Visualization
GEOMI: GEOmetry for maximum insight
GD'05 Proceedings of the 13th international conference on Graph Drawing
Sphere Anchored Map: A Visualization Technique for Bipartite Graphs in 3D
Proceedings of the 13th International Conference on Human-Computer Interaction. Part II: Novel Interaction Methods and Techniques
GEOMI: GEOmetry for maximum insight
GD'05 Proceedings of the 13th international conference on Graph Drawing
MultiPlane: a new framework for drawing graphs in three dimensions
GD'05 Proceedings of the 13th international conference on Graph Drawing
TGI-EB: a new framework for edge bundling integrating topology, geometry and importance
GD'11 Proceedings of the 19th international conference on Graph Drawing
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Clustered graph is a very useful model for drawing large and complex networks. This paper presents a new method for drawing clustered graphs in three dimensions. The method uses a divide and conquer approach. More specifically, it draws each cluster in a 2D plane to minimise occlusion and ease navigation. Then a 3D drawing of the whole graph is constructed by combining these 2D drawings. Our main contribution is to develop three linear time weighted tree drawing algorithms in three dimensions for clustered graph layout. Further, we have implemented a series of six different layouts for clustered graphs by combining three 3D tree layouts and two 2D graph layouts. The experimental results with metabolic pathways show that our method can produce a nice drawing of a clustered graph which clearly shows visual separation of the clusters, as well as highlighting the relationships between the clusters. Sample drawings are available from http://www.cs.usyd.edu.au/~visual/valacon/gallery/C3D/