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Author ORCID Identifier

https://orcid.org/0000-0002-2784-3011

AccessType

Open Access Dissertation

Document Type

dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Computer Science

Year Degree Awarded

2022

Month Degree Awarded

September

First Advisor

Narges Mahyar

Subject Categories

Other Computer Sciences

Abstract

Although data visualizations have been around for centuries and are encountered frequently by the general public, existing evidence suggests that a significant portion of people have difficulty understanding and interpreting them. It might not seem like a big problem when a reader misreads a weather map and finds themselves without an umbrella in a rainstorm, but for those who lack the means, experience, or ability to make sense of data, misreading a data visualization concerning public health and safety could be a matter of life and death. However, figuring out how to make visualizations truly usable for a diverse audience remains difficult. In my thesis, I examined three areas where altering current practices may help make data visualizations more understandable and impactful in the future.

DOI

https://doi.org/10.7275/30844079

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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