Graph Visualization: Quality Metrics
Published:2018-07-22

Title:         Graph Visualization: Quality Metrics
Time:     10:00-11:30, July23  Monday,2018
Location:  Room 504, Science Building
Lecturer: Prof.Peter Eades Sydney University

 

Abstract:

Graphs have been broadly used to model binary relations since the beginning of Information Technology. Nodes represent entities, and edges represent relationships between entities. Such models become more useful when the graph model is represented as a diagram, because visualization of a graph enables humans to understand the underlying model. The first part of this talk briefly reviews research and practice in graph visualization.

 A quality metric assigns a number q(D) to each diagram D such that q(D) is larger than q(D') when D is a higher quality diagram than D'. Quality metrics for graph visualization have been discussed since the 1970s.  However, this early work does not scale to today's data sets. The second part of this talk concerns quality metrics for graph visualization, concentrating on large graphs.

 Much of this talk is based on joint work and discussions with Quan Nguyen, SeokHee Hong, and Karsten Klein, among others.

 

Biography:
Professor Peter Eades is currently an Emeritues Professor in the school of Information Technology at the University of Sydney where he was a chair professor and the head before his semi-retirement. Prof Peter Eades got PhD in Math from National University of Australia. He taught at the University of Queensland, the University of Newcastle, and the University of Sydney.  Professor Peter Eades has been investigating methods for visualization of networks since the 1980s and he is one of the few giving the name of graph drawing. The algorithms described in his papers on this topic are currently commonly used in diverse software systems, from social networks, biological networks, CASE tools, to security. Currently, he continues to research the mathematics and algorithmics of geometric graphs.

Software Engineering Institute

Address:Zhongshan North Road 3663, Shanghai
                Nanmu Road111, Shanghai

E-mail:office@sei.ecnu.edu.cn  | Tel:021-62232550

Copyright Software Engineering Institute

XML 地图