A Survey on Visual Design in Data-Driven Storytelling

PhD Qualifying Examination

Title: "A Survey on Visual Design in Data-Driven Storytelling"


Miss Xinhuan SHU


Communicating data insights effectively to a general audience has become a 
fundamental problem in the information explosion era. We have seen a growing 
interest in telling data-driven stories to alleviate this issue. Specifically, 
these data-driven stories are structured by findings from data and often 
incorporate visual representations into the process of narration. However, 
crafting such visual data stories is non-trivial and time-consuming. 
Particularly, effective visual design in a data story remains underexplored. 
Besides, narrative authoring tools are still in the infancy and do not keep 
pace with innovation in practice. These gaps catalyze the growth of research 
interest in the visualization field. Existing studies have shown typical visual 
design in data-driven storytelling, taking an initial step to ease the creation 
process. They indicate the potential to easily produce high-quality data 
stories for communication.

In this survey, we discuss the development of visual design in data-driven 
storytelling, as well as the authoring tools. The survey begins with an 
introduction to the motivation and challenges of data-driven storytelling. 
Then, based on the definition of the termĀ narrative, we review visual design in 
three primary story components, namely, scenes, sequences, and transitions, and 
discuss how they compose a visual data story. After that, we investigate 
existing authoring tools and reflect on evaluation methodologies. The survey 
ends with current research gaps and future directions in data-driven 

Date:			Friday, 28 September 2018

Time:                  	2:00pm - 4:00pm

Venue:                  Room 2408
                         Lifts 17/18

Committee Members:	Prof. Huamin Qu (Supervisor)
 			Prof. Chiew-Lan Tai (Chairperson)
 			Dr. Xiaojuan Ma
 			Dr. Pedro Sander

**** ALL are Welcome ****