arXiv subjects

Krisha Mehta

Publications and source records attributed to Krisha Mehta.

3 recordsLinked to original sources

arXiv2026

Investigating Ethical Data Communication with Purrsuasion: An Educational Game about Negotiated Data Disclosure

Data communication entails ethical dilemmas where situational constraints forbid full disclosure of source data. Whereas visualization research and pedagogy often frames ethics as a matter of individuals making deceptive design choices or being misled, disclosure problems involve negotiation between pro-social actors. To provide observability into these situated judgments, we contribute Purrsuasion, an open-source visualization game where participants play the roles of (i) data providers designing visualizations subject to disclosure constraints and (ii) data seekers requesting information and awarding a contract. We deploy Purrsuasion in an undergraduate data science class (N = 27), gathering gameplay data to support a mixed-methods analysis of students' communication dynamics, problem solving, and trust formation. We find that difficulties envisioning an ideal visualization solution lead to satisficing in visualization authoring and difficulties attributing authorial intent. Given these challenges, we approach scoring student solutions by developing a heuristic rubric that supports sociotechnical judgments of disclosure adherence.

cs.HC↗

arXiv2025

Designing for Disclosure in Data Visualizations

Visualizing data often entails data transformations that can reveal and hide information, operations we dub disclosure tactics. Whether designers hide information intentionally or as an implicit consequence of other design choices, tools and frameworks for visualization offer little explicit guidance on disclosure. To systematically characterize how visualizations can limit access to an underlying dataset, we contribute a content analysis of 425 examples of visualization techniques sampled from academic papers in the visualization literature, resulting in a taxonomy of disclosure tactics. Our taxonomy organizes disclosure tactics based on how they change the data representation underlying a chart, providing a systematic way to reason about design trade-offs in terms of what information is revealed, distorted, or hidden. We demonstrate the benefits of using our taxonomy by showing how it can guide reasoning in design scenarios where disclosure is a first-order consideration. Adopting disclosure as a framework for visualization research offers new perspective on authoring tools, literacy, uncertainty communication, personalization, and ethical design.

cs.HC↗

arXiv2022

Maybe, Maybe Not: A Survey on Uncertainty in Visualization

Understanding and evaluating uncertainty play a key role in decision-making. When a viewer studies a visualization that demands inference, it is necessary that uncertainty is portrayed in it. This paper showcases the importance of representing uncertainty in visualizations. It provides an overview of uncertainty visualization and the challenges authors and viewers face when working with such charts. I divide the visualization pipeline into four parts, namely data collection, preprocessing, visualization, and inference, to evaluate how uncertainty impacts them. Next, I investigate the authors' methodologies to process and design uncertainty. Finally, I contribute by exploring future paths for uncertainty visualization.

cs.HC↗