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"Visualizing Big Hierarchical Data with CabinetTee" is the title of the lecture, which Prof. Kang Zhang will present during the PSNC seminar, presenting the latest works on the approach to visualization of large hierarchical data (published recently in the Journal of Big Data).

Hierarchical data could essentially be represented as a tree structure and be visualized as a tree. The traditional Treemaps are the most popular among many tree visualization approaches. Most tree visualization approaches, however, have been focused on layout algorithms and paid little attention to other display properties and interactions. Furthermore, the structural information in conventional Treemaps is too implicit for viewers to perceive. This talk will present our recent work on Cabinet Tree, an approach for visualizing big hierarchical data (recently published in Journal of Big Data at http://www.journalofbigdata.com/content/pdf/s40537-015-0022-3.pdf). Cabinet Tree draws branches explicitly to show relational structures, uses a space-optimized layout to maximize space utilization, and adopts coloring and labeling strategies to clearly reveal patterns and contrast different attributes intuitively. Our quantitative evaluations demonstrate that Cabinet Tree achieves good scalability for increased resolutions and big datasets. A usability evaluation in comparison with other approaches also confirms the effectiveness of Cabinet Tree in visualizing hierarchical overview and user exploration. Other projects will also be briefly mentioned.

 

Short Biography:
Kang Zhang is Professor and Director of Visual Computing Lab, Department of Computer Science, and Professor of Arts and Technology, at the University of Texas at Dallas. He is currently a Fulbright Distinguished Chair visiting Charles University. Zhang received his B.Eng. in Computer Engineering from University of Electronic Science and Technology of China in 1982, Ph.D. from the University of Brighton, UK, in 1990, and Executive MBA from the University of Texas at Dallas in 2011. Prior to joining UT-Dallas, he held academic positions in the UK, Australia, and China. Zhang's current research interests include generative art, visual languages, aesthetic computing, and software engineering; and has published 7 books, and over 240 papers in these areas. He is an ACM Distinguished Speaker and on the Editorial Boards of Journal of Big Data, The Visual Computer, Journal of Visual Languages and Computing, International Journal of Software Engineering and Knowledge Engineering, and International Journal of Advanced Intelligence. His home page is at: utd.edu/~kzhang.

Agnieszka Wylega│a