Perceptual Based Visualizations for Time-Dependent Semantics
Nivedita R. Kadaba · Mspace (University of Manitoba) · 2005
Time-dependent semantics are concepts that vary over a period of time. We interact with time-dependent semantics on a daily basis, such as reading weather forecast, inspecting market fluctuations, and studying personal financial trends. However, some of them are difficult to comprehend due to their inherent complexity. Visualizations using simple animations have commonly been used for depicting and communicating time-dependent concepts. Research on visualizing time-dependent information places a strong emphasis on the adequate representation of the information being visualized. In this thesis I develop novel representations for a class of time-dependent concepts used in the information sciences. Despite the advantages of using animation for time-dependent semantics, a recurring problem is the visual overload of moving objects as the density of information increases on the screen. The visual overload hinders attention and comprehension. This thesis also addresses the issue of adequately presenting information to enhance attention in animated scenes. The first study (consisting of three stages) focuses on representing complex timedependent concepts using simple visual representations, modeled on existing perceptual theories. In the first stage, a set of visual representations are created for a selected class of time-dependent concepts. In the second stage, the best representations for the timedependent concepts are produced through a user evaluation. In the third stage, the visual representations are evaluated for their ability to enhance comprehension in an area of application, such as quantum algorithms. Results of the user evaluations show that there