Abstract
The main purpose of information visualization is to act as a window between a user and data. Historically, this has been accomplished via a single-agent framework: the only decisionmaker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but from necessity: prior to this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This thesis aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. We demonstrate this system with a between-groups, two-by-two study measuring the effects of this mixed-initiative system on user interactions and system usability. We find little to no evidence that the adaptive system designed here has a statistically-significant effect on user interactions or system usability. We discuss the implications of this lack of evidence, and examine how the data suggests a promising avenue of further research.
Committee Chair
Alvitta Ottley
Committee Members
Alvitta Ottley Chien-Ju Ho William Yeoh
Degree
Master of Science (MS)
Author's Department
Computer Science & Engineering
Document Type
Thesis
Date of Award
Spring 2020
Language
English (en)
DOI
https://doi.org/10.7936/qhkg-9w35
Author's ORCID
https://orcid.org/0000-0001-9337-7189
Recommended Citation
Kern, Adam, "The Effects of Mixed-Initiative Visualization Systems on Exploratory Data Analysis" (2020). McKelvey School of Engineering Theses & Dissertations. 523.
The definitive version is available at https://doi.org/10.7936/qhkg-9w35
Comments
Permanent URL: https://doi.org/10.7936/qhkg-9w35