Category: Publications

The term “guideline” is both ambiguous and loosely defined, and what one researcher considers a guideline may be too broad, too loose, or too strict for another. We take a closer look at a broader set of terms that can express desirable results around visualization research, and untangle how these words are understood in the community in relation to other similar terms.

We present Site Accessibility Auditor, a Chrome DevTools extension with two coordinated lenses. The interaction lens automatically drives the page through its reachable states and overlays interaction-dependent issues as inspectable visual evidence on a full-page capture. The reading & focus order lens aligns the visual, screen-reader, and keyboard orders, shows where they diverge, and suppresses intentional patterns such as skip links.

We present a case study redesigning the Utah Wastewater Surveillance System dashboard to improve accessibility and usability across desktop and mobile settings. The redesign was informed by WCAG and developed iteratively with Utah DHHS collaborators, and we collected feedback on the final design from an external blind researcher.

We introduce VisPeerReview, a visualization-specific learning analytics dashboard (LAD) designed to scaffold peer feedback through an integrated visualization display, rubric-guided prompts, and inline annotation tools. We evaluated VisPeerReview through a three-phase mixed-methods study conducted in an undergraduate data visualization course, comparing it with Canvas’s default peer-review workflow.

We conducted a two-phase qualitative study: interviews with ten practitioners from diverse backgrounds revealed the heuristics they draw on when creating annotations, and interviews with seven visualization educators offered complementary perspectives situated within broader concerns of clarity, guidance, and viewer agency. These studies provide a systematic account of annotation design knowledge in professional settings, highlighting the considerations, trade-offs, and contextual judgments that shape the use of annotations.

We investigate whether users benefit from algorithmic choice when adapting line charts across screen sizes. In a within-subjects study (N=30), participants simplified nine datasets under three conditions: single pre-assigned technique (C1), multiple techniques (C2), and multiple techniques with manual point selection (C3), each with control over simplification level.

We conduct a between-subjects (N=40) observational study of representative data cleaning tasks performed with four tools spanning distinct interface paradigms: Jupyter (notebook), Excel (spreadsheet), ChatGPT (conversational AI), and OpenRefine (visual wranglers).

In this paper, we study the propagation of data uncertainty through the marching cubes algorithm for isosurface visualization for correlated uncertain data.

We introduce ChannelExplorer, an interactive visual analytics tool for analyzing image-based outputs across model layers, emphasizing data-driven insights over architecture analysis for exploring class separability.

We conducted a visual stenography task, where participants re-drew line charts to solicit information about the visual features they believed to be important. We systematically varied noise to observe how visual clutter influences which features people prioritize in their sketches. We identified three key strategies: Replicator, Trend Keeper, and De-noiser. Further, we found that participants tended to faithfully retain trends and peaks and valleys when these features were present, while periodicity and noise were represented semantically.