Date Approved

8-17-2022

Embargo Period

8-18-2022

Document Type

Thesis

Degree Name

M.S. Computer Science

Department

Computer Science

College

College of Science & Mathematics

Advisor

Bo Sun, Ph.D.

Committee Member 1

Ning Wang, Ph.D.

Committee Member 2

Anthony Breitzman, Ph.D.

Keywords

immersive analytics, data visualization, human-computer interaction

Subject(s)

Virtual reality; Information visualization

Disciplines

Computer Sciences

Abstract

Data visualization is an important field of work that takes in uncountable amounts of indexes to create an easy-to-read interpretation of what was previously unreadable. Immersive analytics is the new field that brings 3D data visualization to virtual reality, immersing users directly into the data. Focusing on bringing humans and computers closer together through natural function can benefit the world of data science. In order to accurately utilize this field to benefit this world, principles must be laid out and observed to see which techniques and methods are best fit for an everyday immersive analytics platform. Our findings show that, within an immersive 3D environment, users that perform in a static state where no physical or virtual navigation of the environment is present is more beneficial to the interpretation of the data. While reported gender identity does not seem to affect the time to complete the given task, it seems the age of a given participant is one factor which affects the task time.

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