Book chapter on Multivariate Network Visualisation

T. J. Jankun-Kelly, T. Dwyer, D. Holten, C. Hurter, M. Nöllenburg, C. Weaver, and K. Xu, “Scalability Considerations for Multivariate Graph Visualization,” in Multivariate Network Visualization, A. Kerren, H. C. Purchase, and M. O. Ward, Eds. Springer International Publishing, 2014, pp. 207–235. PDF.
Multivariate network is a quite challenging problem: it involves both the network structure and the attributes of the nodes and edges. Think of a social network: you have people as the nodes and their relationships as edges; there are information about the people (age, gender, profession) and their relationships (friends/colleague, when it started, etc). Considering both will provide  a deeper look into the social network, but makes the visualisation more difficult at the same time. This book chapter mainly surveys human performance related issues to this type of visualisation. This is an example of my previous work on this topic:

TVCG/VAST 2013: An Extensible Framework for Provenance in Human Terrain Visual Analytics


The paper is accepted by the VAST 2013 conference and will appear in the IEEE Transactions on Visualization and Computer Graphics. It provides visualisation for different uncertainties in Human Terrain Analyisis and a way to construct narratives of the visual exploration discoveries. PDF

Concern Level Assessment: Building Domain Knowledge into a Visual System to Support Network Security Situation Awareness

This is the journal paper about the VAST Challenge 2012 award. It is accepted by the Information Visualisation journal and will appear shortly. PDF


InfoVis 2012 paper! A User Study on Curved Edges in Graph Visualisation

This is an extended version of the work presented as a poster at Diagrams 2012 with new user study and analysis. Kai Xu, Chris Rooney, Peter Passmore, and Dong-Han Ham, “A User Study on Curved Edges in Graph Visualisation”, IEEE Information Visualization Conference, 14-29 October 2012, Seattle, US. PDF

A User Study on Curved Edges in Graph Visualisation

Kai Xu, Chris Rooney, Peter Passmore, and Dong-Han Ham, “A User Study on Curved Edges in Graph Visualisation”, Seventh International Conference on the Theory and Application of Diagrams, 2-6 July 2012, Canterbury, UK. PDF

Recently there has been increasing research interest in visualizing graphs with curved edges to produce more readable visualizations. While there are many automatic techniques, little has been done to evaluate them empirically. In this paper we present our study on the impact of edge curvature on graph readability by comparing the path finding performance on graph visualizations with varied curvature levels. We also asked the participants to provide subject ratings of the effectiveness and aesthetics of different types of curved edge.

Workshop on Human-Computer Interaction and Knowledge Discovery and Data Mining (HCI-KDD)

B.L. William Wong, Kai Xu, and Andreas Holzinger,  “Interactive Visualization for Information Analysis in Medical Diagnosis”, Workshop on Human-Computer Interaction & Knowledge Discovery and Data Mining (HCI-KDD) @ 7th Conference of the Austrian Computer Society Workgroup: Human-Computer Interaction (USAB), Graz Austria, November 2011. PDF

International Conference on Data and Knowledge Engineering (ICDKE) 2011

Qing Liu, Ji Zhang, James Forbes, Kai Xu, Dinesh Nair, “A Knowledge Discovery Service System for Provenance Exploration”, International Conference on Data and Knowledge Engineering (ICDKE) 2011, Milan, Italy, September 2011. PDF