Evaluating 5D Data Visualization Across Low- and High-Immersive Environments-Converted
Abstract
The amount of data in our world is increasing quickly. As data keep increasing, so does its number of dimensions and there is currently no official standard tool that can visually represent all dimensions of a multi-dimensional data without dimensionality reduction or just as a set of matrices in a 2D plane. It will become necessary for multi-dimensional data to be represented in an environment where all of its dimensions can be fully defined in order to be interpreted correctly, specifically by audiences with no background in data analysis. Therefore, immersive visualizations through Virtual Reality (VR) provide a great opportunity to its users as they have the advantage of including higher dimensions of data and providing a perspective from different angles which is not always possible in the traditional 2D interpretations. However, the problem is that there is minimal to no guidelines about using higher dimensions of data in a 3D environment through visual mediums. The purpose of this study is to understand how different applications (VR and Desktop) affect the interpretation of multi-dimensional data across various levels of dimensions. This comparison will lead to a better understanding of the development and use of proper visual techniques in Immersive Analytics.
Degree
M.Sc.
Advisors
Mousas, Purdue University.
Subject Area
Information Technology
Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server.