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Title
Augmenting Graphic Design Practices for Expressive Visualization Authoring
John Thompson
PhD Candidate in Computer Science
School of Interactive Computing
Georgia Institute of Technology
Date: Tuesday, November 10, 2020
Time: 4:00pm - 6:00pm EST
Location: (remote via Zoom) https://us02web.zoom.us/j/79753853759?pwd=R1RUVmg4bUhrbklIOXFtRnlpSnlnUT09
Passcode (if prompted): john
Committee
Dr. John Stasko - Advisor, Georgia Institute of Technology, School of Interactive Computing
Dr. Alex Endert - Georgia Institute of Technology, School of Interactive Computing
Dr. Keith Edwards - Georgia Institute of Technology, School of Interactive Computing
Dr. Zhicheng Liu - University of Maryland, Department of Computer Science
Dr. Alberto Cairo - University of Miami, School of Communication
Abstract
Data visualization provides an effective method to tell stories, simplify complex concepts, support arguments, and make boring facts exciting. As communicative data visualization matures as a field in the computer graphics era, it has broadened into adopting practices from related fields such as graphic design. Designers employ a combination of methods to create expressive data visualizations in static or animated forms. These methods, however, are mismatched with their creative practice (e.g. writing textual code), or lack in generative power (e.g. graphic design tools). This dissertation explores opportunities to design and implement data visualization authoring tools for graphics designers. The goal of this research is to broaden practice and participation in data visualization. This dissertation contributes two interactive systems, Data Illustrator and Data Animator, that provide graphic designers with an understandable, feasible, and effective method to author expressive data visualizations (without writing textual code). These systems augment interfaces and interactions from graphic design practices to support control over expressive frameworks for static and animated data graphics. I demonstrate each system’s expressivity with a variety of example data visualizations and their usability through re-creation studies with designers. Finally, I reflect on the assumptions, strengths, and limitations of our approach, and identify future research directions for communicative data visualization.
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