Reinforcing Visualization Design Using Graphical Primitives of Visual Objects
Data visualization has been established as a powerful tool to help humans understand and communicate information concisely and effectively. It exploits visual perception to extract facts and meanings from data. The visualization also allows people to examine data even if they do not know what to look at in advance. However, most visualization techniques follow a one-size-fits-all paradigm concerning users and data. It is seldomly designed for a specific kind of data or users. In addition, designing competent visualization is increasingly challenging due to the complexity and overflow of data in every field. Visual objects are the backbone of any complex visualization tool. It is a collection of graphical primitives arranged in a structured way. Although previous studies on graphical primitives of 2D graphs yield exciting results, there were no studies on visual elements of 3D graphs. This dissertation investigates basic 2D graphs and 3D graphical primitives of visual objects. It proposes a new interactive sensor monitoring tool for smart manufacturing set up by leveraging the results of a 2D graph study. The results were also useful to build an interactive visualization tool for multidimensional data on 2D display. I conducted user study to evaluate 3D visual elements for numerical and nominal data. The outcome of the study was applied to build application for estimating cognitive load in Virtual Reality environments. I also propose a new visualization tool for gaze-based data that can be integrated with any webcam-based eye tracker. A case study to evaluate the effectiveness of the tool was conducted.