CMU-HCII-26-103
Human-Computer Interaction Institute
School of Computer Science, Carnegie Mellon University


CMU-HCII-26-103

Tool-making as an Intervention on the Accessibility of Interactive Data Experiences

Frank J. Elavsky

July 2026

Ph.D. Thesis

CMU-HCII-26-103.pdf


Keywords: Visualization, accessibility, data interaction, tangible interfaces, tactile data representations, sonifcation, graph theory, human-computer interaction, personalization, disability, malleable interfaces, guidelines, standards, heuristics, evaluation, human-studies, qualitative research, quantitative research, assistive technology, data science, software tools, hardware tools, input modalities, voice-controlled interfaces, gesture-based input, natural language system design, programming tools, sensory substitution, software debugging.


In this dissertation, we contribute practical advancements in tool-making as an intervention on the accessibility of interactive data experiences. The thesis of this dissertation is as follows:

This dissertation argues that the tools practitioners use to build interactive data experiences are themselves sites where accessibility barriers are produced, prevented, or alleviated for both end users and authors. This work contributes fve tools, Chartability, Data Navigator, Skeleton, Cross-perception, and Softerware, that collectively center accessibility work on the empowerment of disabled and non-disabled practitioners across the full arc of evaluation, data navigation, analytical interaction, and personalization.

Rather than framing accessibility research solely around ideal experiences for end users with disabilities, this thesis investigates why accessibility work is so diffcult for the practitioners who build interactive data experiences and what tool-making can reveal about those diffculties.We organize this investigation around four domains where practitioners face the most persistent challenges: evaluation, navigation, interaction, and personalization. Chartability, a heuristic framework, contributed frst and mapped the full landscape of accessibility barriers. Chartability helped us to identify and prioritize our three latter domains (navigation, interaction, and personalization) as the areas where the most severe gaps remain in practitioner work. Data Navigator and Skeleton then investigate navigation, fnding that practitioners struggle because navigation structure has no visible, manipulable representation in their workfows. Cross-perception engages interaction, demonstrating that blind data analysis has been constrained by existing tools and that a new interaction design framework can reshape what analytical work is possible. Softerware addresses personalization, revealing that access needs genuinely confict across users and that meaningful personalization requires system-level infrastructure that does not yet exist in practitioner tooling ecosystems.

Combined, these contributions provide empirical insights and practical advancements in the state of the art for tooling that bridges gaps in current accessibility practices in visualization and data science. Our work ultimately enables people with and without disabilities to better evaluate barriers in, analyze with, design for, develop, and personalize interactive data experiences. We demonstrate that tool-making is a productive intervention that both engages accessibility barriers and elucidates why those gaps exist in practitioner work.

248 pages

Thesis Committee:
Dominik Moritz (Co-Chair)
Patrick Carrington (Co-Chair)
Ken Holstein
Jennifer Mankoff (University of Washington)
Tamara Munzner (University of British Columbia)

Brad A. Myers, Head, Human-Computer Interaction Institute
Martial Hebert, Dean, School of Computer Science

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