Efficient creation and analysis of visualizations for data communication

PhD Thesis Proposal Defence


Title: "Efficient creation and analysis of visualizations for data 
communication"

by

Mr. Aoyu WU


Abstract:

The influential rise of the Internet and social media has accompanied 
ever-increasing public needs for accessing information and data. In light 
of this trend, data visualizations have emerged as one of the primary 
mediums for public data communication. Thus, a large number of 
visualizations have been produced and shared on the web, raising new 
challenges and problems in both society and academia. In this thesis, I 
investigate this phenomenon and accompanying problems through a careful 
combination of research methods, including literature survey, empirical 
studies, and machine learning. Specifically, this thesis focuses on:

(1) Building novel recommenders for authoring high-quality visualizations. 
Many web visualizations are made by non-experts and suffer from quality 
problems such as poor readability and insight. I present three automated 
approaches to assist the general public in creating visualizations, 
including MobileVisFixer for generating mobile-friendly designs, LQ2 for 
authoring aesthetic layouts, and MultiVision for designing analytical 
dashboards.

(2) Formalizing visualizations as a new first-class object for efficient 
analysis. Through a comprehensive literature survey into ten research 
fields in computer science, I argue that visualizations are becoming a new 
data object like images and text. I further formulate the emerging 
research field as visualization processing and analysis that concerns 
processing digitized visualizations and extracting meaningful information. 
My work ComputableViz presents a formalism for operating on multiple 
visualizations, thereby creating novel applications such as interactively 
combining visualizations in AR environments.

By integrating those two perspectives, this dissertation contributes to a 
new online knowledge ecosystem – both analyzing web visualizations to 
distill knowledge and assisting the public in producing new visualizations 
to communicate data. I hope that this ecosystem will continue stimulating 
new theories, problems, techniques, and applications to further bridge the 
public with data.


Date:			Monday, 6 June 2022

Time:                  	2:00pm - 4:00pm

Zoom Meeting: 
https://hkust.zoom.us/j/94818568037?pwd=RUpieVZjbVI3SStIcjBWYjcwQzB2dz09

Committee Members:	Prof. Huamin Qu (Supervisor)
  			Dr. Amir Goharshady (Chairperson)
 			Prof. Chiew-Lan Tai
 			Dr. Dan Xu


**** ALL are Welcome ****