Information Visualization

 
 

Information visualization (InfoVis) uses visual elements to represent abstract data. It communicates information with people by making use of human vision, which is recognized as having the widest bandwidth of all senses. The goal of InfoVis is to seamlessly integrate the visual representations and explorative interfaces together, aiming to provide users with an informative, convenient, and pleasant data exploring and communicating environment.

 

Our research in information visualization focuses on structured data visualization and query-driven interaction. Graphs and trees are the most classic types of structures. We study the visual representation and the layout algorithms of these structures to fulfill the desired visual properties. As interactive query becomes an indispensable means for data analysi, we study the visual operations that can assist the user to glean insight into the data.

Publications on Information Visualization

Self-Adaptive Treemaps


Abon Chaudhuri and Han-Wei Shen. A self-adaptive treemap-based technique for visualizing hierarchical data in 3d. In PacificVis '09: Proceedings of IEEE Pacific Visualization Symposium 2009, pages 105-112, 2009.

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Data Projection for High Dimensional Data


Boonthanome Nouanesengsy, Sang-Cheol Seok, Han-Wei Shen, and Veronica Vieland. Using projection and 2D plots to visually reveal genetic mechanisms of complex human disorders. In VAST '09: Proceedings of IEEE Symposium on Visual Analytics Science and Technology 2009, pages 171-178, 2009.

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Multi-focus+Context Treemaps


Ying Tu and Han-Wei Shen. Balloon focus: a seamless multi-focus+context method for treemaps. IEEE Transactions on Visualization and Computer Graphics, 14(6):1157-1164, Nov 2008.

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Time-Varying Data Visualization using Treemaps


Ying Tu and Han-Wei Shen. Visualizing changes of hierarchical data using treemaps. IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Visualization / Information Visualization 2007), 13(6):1286-1293, 2007.

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Bridging infoVis and SciVis


Chaoli Wang and Han-Wei Shen. LOD map: A visual interface for navigating multiresolution volume visualization. IEEE Transactions on Visualization and Computer Graphics (Proceedings of the Visualization / Information Visualization 2006), 12(5):1029-1036, 2006.

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User Interface for LOD Selection


Chaoli Wang and Han-Wei Shen. Hierarchical navigation interface: Leveraging multiple coordinated views for level-of-detail multiresolution volume rendering of large scientific data sets. In Proceedings of the Ninth International Conference on Information Visualisation, volume 00, pages 259-267. IEEE Computer Society Washington, DC, USA, 2005.

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Visualization of PDF Data


Udeepta Bordoloi, David L. Kao, and Han-Wei Shen. Visualization and exploration of spatial probability density functions: a clustering-based approach. In Proceedings of IS&T/SPIE Visualization and Data Analysis 2004, volume 5295, pages 57-64, 2004.

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Clustering of PDF Data


Udeepta Bordoloi, David L. Kao, and Han-Wei Shen. Visualization techniques for spatial probability density function data. Data Science Journal, 3:153-162, 2004.

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