In Partial Fulfillment of the Requirements for the Degree of Master of Science

Glenn Turner

will defend his thesis

A Visual Analytics System for Large-Scale Data Exploration

Abstract

Visualization aims to produce meaningful visual representation of data, which has been shown to be a powerful means to reveal information (e.g., structures and/or relations) hidden in large-scale and complex data where our knowledge to these data is sparse. From the visualization of these data sets, important details are often difficult to discern due to the occlusion caused by the excessive visual elements presented. In this thesis, I present a visual analytics system that offers a complete pipeline for processing and visualizing these large-scale, complex data, starting from data cleaning and analysis to visualization generation and user interactions. In particular, my system supports a level-of-detail exploration scheme, showing the overview of the data in the beginning with various visual representations, followed by the detail-on-demand exploration. This thesis provides a detailed description on the design and implementation of my system. In addition, the application of my system for the discovery of abnormal patterns hidden in a traffic control data is presented to demonstrate the utility and effectiveness of the system.

Date: Friday, November 08, 2019
Time: 10:00 - 11:30 AM
Place: PGH 501D
Advisor: Dr. Guoning Chen

Faculty, students, and the general public are invited.