Automatic Resizing Framework for Time-Varying Non-Space Filling Visualizations

We propose the development of an automatic resizing framework for time-varying visualizations. This framework would support easy deployment of visualizations on a multitude of devices with varying display sizes. The second objective of the project is to address issues of data is interpretation that could arise as a result of visualization resizing through the use of visual cues as well as interaction techniques. The developed resizing algorithms will be instantiated in the form of prototype applications of visualizations such as, dynamic networks and scatter plots. These prototype applications will be evaluated based on not only the memory and time requirements of the resizing operation but also the efficiency of
the retargeted visualizations at supporting the user in accomplishing analytical tasks. The resizing framework developed during the course of this project will be available as open source software to prompt further refinement by the research community.

Faculty Supervisor:

Christopher Collins

Student:

Partner:

Inria Lille - Nord Europe Research Centre

Discipline:

Computer science

Sector:

University:

University of Ontario Institute of Technology

Program:

Globalink Research Award