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2.5D Graph Navigation and Interaction Techniques


This project aim to design, implement and evaluate new methods and algorithms for effective and efficient navigation and interaction with 2.5D graph layout.


Professor Seok-Hee Hong.

Research location

Computer Science

Program type



Recent technological advances have led to many large and complex network models in many domains, including social networks, biological networks, webgraphs and software engineering. Visualization can be an effective analysis tool for such networks; good visualisation may reveal the hidden structure of the networks and amplifies human understanding, thus leading to new insights, new findings and possible prediction of the future.

However, visualisation itself cannot serve as an effective and efficient analysis tool for large and complex networks, if it is not equipped with suitable interaction and navigation methods. Well designed and easy-to-use navigation and interaction techniques can enable the users to communicate with visualization much faster and effectively to perform various analysis tasks such as finding patterns, trends and unexpected events. 

Recently, 2.5D graph visualization methods have been successfully applied for visualization of large and complex networks, arising from biological networks, social networks and internet networks. However, the corresponding navigation method has yet been investigated so far. This project aim to design, implement and evaluate new methods for navigating 2.5D layouts of large and complex networks to enable users to perform analytical tasks.

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Opportunity ID

The opportunity ID for this research opportunity is 1035

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