HCII PhD Thesis Proposal: Frank Elavsky
When
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Description
Tool-making as an Intervention on the Accessibility of Interactive Data Experiences
- Frank Elavsky
PhD Thesis Proposal
Carnegie Mellon University, Human-Computer Interaction Institute
Date and Time: Friday, April 18th at 4pm Eastern Time
Location: Newell Simon Hall 1305
Zoom: https://cmu.zoom.us/j/92071484019?pwd=83n1wO2TSMSrmRAbTy9H43mbLuL0FY.1
Meeting ID: 920 7148 4019
Passcode: 529207
Committee:
Dominik Moritz (co-chair), CMU HCII
Patrick Carrington, (co-chair), CMU HCII
Ken Holstein, CMU HCII
Jennifer Mankoff, external, UW
Tamara Munzner, external, UBC
Abstract:
This thesis demonstrates practical advancements in making interactive data experiences accessible through a suite of tools and frameworks. Central to this work is the reframing of accessibility as a process that not only addresses the functionality of data visualizations but also considers how the underlying tools and methodologies that are used to build interactive data experiences can produce barriers, enable new interactions, and improve work for people with disabilities. Rather than framing research in accessibility towards correcting perceived deficits in users, this research posits that tools and toolmakers have a responsibility to enable designers, developers, and end-users towards more accessible outcomes.
This thesis introduces Chartability, a heuristic framework that enables designers, developers, and auditors to systematically evaluate data visualizations and interfaces for a wide range of accessibility barriers, considering people with visual, motor, vestibular, neurological, and cognitive disabilities. Through Chartability, practitioners—especially those with limited accessibility expertise—gain confidence and clarity in assessing and improving their work.
Complementing this, the thesis presents Data Navigator, a dynamic system designed as building blocks, which can be used to construct accessible navigation structures such as lists, trees, and graphs from underlying data. By supporting various input modalities—screen readers, keyboards, speech, and gestures—Data Navigator enables practitioners to construct data exploration experiences for users who rely on non-visual interaction, making complex datasets navigable and interactive for a wide range of people with disabilities.
Further, the concept of Softerware is introduced to address the tension between standardized accessible design and the diverse needs of real users with disabilities. This approach focuses on system design principles and empirical research to inform tool-makers to build interfaces that can empower end users with disabilities to customize and adapt interfaces to suit their data interaction preferences and needs.
This thesis also presents a blind-centered data analysis hardware tool, the Cross-feelter. This research project introduces a tactile input device that allows blind users to efficiently perform spatial cross-filtering tasks by providing simultaneous tactile input and output feedback. Evaluations with braille displays show that the device significantly improves interaction speed and exploratory query generation for blind users working with data.
This document culminates in a proposal for Skeleton, a development and de-bugging tool built on top of Data Navigator. Skeleton will be designed to visually represent non-visual navigation and interaction experiences, which we conjecture will assist sighted designers in rapidly prototyping and fixing custom screen reader experiences for diagrams, maps, and bespoke visualizations. We hypothesize that by enabling visual inspection and iterative design, Skeleton will not only speed up the development process but also serve as an educational resource for understanding non-visual data interactions.
In our proposal, we will outline our approach, evaluation process, timeline, and expected contribution of our project, Skeleton.
Together, these contributions provide both theoretical insights and practical tools that bridge gaps in current accessibility practices, ultimately enabling practitioners to build richer, more inclusive data experiences for people with disabilities.
Proposal Document: https://drive.google.com/file/d/1X-AOtEC8USsdcjojeEG0I4x9MKNdmAaH/view?usp=sharing
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Regards,
Frank Elavsky
he/him/his
PhD student, accessibility and data work
Human-Computer Interaction Institute
School of Computer Science
Carnegie Mellon University