报告题目：Larger Crossing Angles Make Graphs Easier to Read
报告人：Tony Huang（Lecturer at the University of Tasmania and Director of Collaboration and Visual Analytics Lab）
A great deal of real world data has a relational or graph structure. Data sets of such a structure are often visualized into node-link diagrams for a better understanding of them. However, the same graph can be drawn in indefinitely ways by simply changing the layout and different layouts affect human graph comprehension differently. In graph drawing, drawing principles, or aesthetics, have been proposed to produce quality layout. Among those aesthetics, edge crossings have been identified as the most important, having the greatest negative impact on humans. Subsequently, much effort has been devoted to crossing minimization in the design of graph drawing algorithms. However, crossing minimization is NP-hard. Further, algorithms that are designed for crossing minimization are often difficult to understand and implement, limiting practical use. A question that has long been asked is: is it possible to achieve a better or the same level of layout quality if we do not minimize the number of crossings?
In this talk, Dr Huang will introduce his research that led to a positive answer to this question and a finding of a new aesthetic: crossing angles. This talk will start with an exploratory eye tracking study of how people read graphs. This study revealed a surprising finding that crossings may not as bad as we normally think. He will demonstrate that a drawing with large-angle crossings can be as good as a drawing with no crossings and that the negative impact of crossings can be minimized or eliminated by maximizing crossing angles.
As an additional note, the finding of this new aesthetic shows that the classical criteria that were used for the previous 25 years to judge the quality of graph visualization were inadequate and has sparked a new research direction in the field, which is to represent graphs with large crossing angles called RAC (Right Angle Crossing) and LAC (Large Angle Crossing) drawings.
Dr Tony Huang is a senior lecturer in the School of Engineering and ICT at the University of Tasmania, Australia and the director of Collaboration and Visual Analytics Lab. He received his PhD in computer science from University of Sydney, in association with National ICT Australia (NICTA). He also has formal training in experimental psychology and professional experience in psychometrics. His main research interests are in Information Visualization, Visual Analytics, and Human-Computer Interaction. He is the author of over 90 publications in these areas including a book entitled “Handbook of human centred visualization”. His research has been supported by various funding agencies including commercial partners, Australian federal and state governments with a total value of over 1.3 million Australian dollars.
He is an editor of Journal of visual languages and computing, a funding chair of the technical committee on visual analytics and communication for IEEE SMC Society. He was a keynote speaker at the 9th International Conference Computer Graphics, Imaging and Visualization in 2012, a general chair for the 7th International Symposium on Visual Information Communication and Interaction 2014, the 10th International Conference Computer Graphics, Imaging and Visualization 2013, and the 2010 International Workshop on Mobile Collaborative Augmented Reality, and a PC chair for the 24th Australian Computer-Human Interaction Conference 2012.