Grant: Discovery Grants Program - Individual

Our world today is flooded with networks generated from varieties of sources such as online activities, social media, business transactions, transportation networks, etc. Network visualization is thus becoming increasingly important for decision making across many Canadian sectors such as business industries, security, administration, emergency communication, immigration and so on. A visualization process faces many challenges. For example, a real-time visualization system for detecting fraud or emerging threats in a cellular communication network would require sophisticated algorithms to compute a layout of millions of network nodes, innovative visualization techniques to reveal the dynamic changes, and fast data structures for interactive filtering and selection. Similar scenarios may be seen in emergency evacuation through transportation networks, forecasting cash demand in ATM networks, detecting dissemination of official messages and exposing rumours in social networks. Although there are many potential applications, existing systems are not effective enough to meet our need. In fact, we do not yet have a clear algorithmic approach to develop an effective visualization system for large networks. We aim to address these challenges by developing a solid algorithmic foundation and software libraries for large network visualization. In the short term, we will design algorithms for layered network visualization that will explore the concept of visualizing large networks in the way we browse geographic maps, e.g., Google or Bing Maps. We will analyze the trade-offs among the visualization aesthetics, and concentrate on visualization updates in interaction time. Techniques that, for each query, compute the visualization from scratch, fall apart when many data queries need to be answered instantly, e.g., in financial and business applications. We will design data structures to maintain partially precomputed visualizations such that new queries or user interactions can be visualized quickly based on the precomputed information. We will also develop algorithms for intelligent systems that can ease network exploration by automatically suggesting the important parts of the visualization and generating on-demand visualization summaries.Our results will have a positive impact on Canadian business and industries, as well as enable individuals to use visualization routinely to deal with large networks. Our algorithms and software libraries will inspire the development of interactive network visualization systems, which will help Canada's government to make important decisions in resource allocation, policy development, security planning, and global investments. The people trained in this program will gain the most sought-after skills for developing real-life visualization. Thus they will play a key role in the future advancement of Canadian software industries.