About

We are a team of visualization researchers at the University of Utah. Our interests include the process of designing and developing visualizations, visualization for biology, visualization frameworks, and, more generally, visualization of big, heterogeneous, and complex datasets.

VDL is part of the Scientific Computing and Imaging Institute and the School of Computing.

Blog And News

Blog Post: How People Actually Lie With Charts 17 Apr 2023
Online audiences and visualization researchers often share, discuss, and critique misleading visualizations. Existing critiques typically point out suboptimal choice of visual encoding or violations of common design guidelines. But is this how charts are used to deceive audiences and spread misinformation in practice? This blog post discusses the findings from our paper on misleading visualizations.

Figure shows an overlapping pile of screenshots of Twitter posts that include data visualizations.
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Blog Post: Reusing Operations In Interactive Visualizations and Computational Notebooks 3 Jan 2023
Interactive data analysis leverages human perception to enable various analysis tasks; however, a prior analysis can rarely be used when the dataset updates or is transferred to a different analysis environment, like a computational notebook. In this post, we discuss how we can capture reusable interactive workflows.

Figure shows a scatterplot with a cluster dataset. One cluster is selected. Next to the scatterplot is a provenance graph with three steps - adding scatterplot, select 61 points, and apply cluster selections. The caption reads 'Curate workflow from analysis provenance' There are two arrows originating from the scatterplot. One points to another scatterplot, which shows the selected cluster moving along Y-axis. Polygons indicate selected cluster. The caption reads 'Reapply the workflows on updated datasets' The other arrow points to a screenshot of jupyter notebook which demonstrate use of the Reapply library. The caption reads 'Apply the workflow in different environment'
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News: Jen Rogers Successfully Defends Dissertation 10 Nov 2022
Congratulations to Jen!

Jen celebrating that she passed her defense!

Jen Rogers successfully defended her dissertation on “Traceability in Design-Oriented Visualization Research”. Jen was co-advised by Alex Lex and Miriah Meyer, with Marina Kogan, Chris Johnson, and Uta Hinrichs serving on the committee.

Jen is moving to Boston to join Remco Chang’s lab at Tufts as a PostDoc. Congrats, and good luck with your next steps!

Jen and her committee

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Blog Post: Can We Guess Why you Selected Something in a Scatterplot? 28 Oct 2022
Selections are a key interaction in data visualization. They are used for highlighting and as the starting point for subsequent actions, including filters, group assignments, etc. Capturing the intent – WHY were these items selected? – can be used to help users refine their selections and to keep a meaningful history of the analysis process. This post discusses our paper on techniques to capture such intents.

Figure shows the techinque for predicting intent. First step shows a scatterplot with a brush selection, captioned 'Selection' with a small human silhouette. Second step shows stacked scatterplots with a cluster selected. The caption reads 'Predictions' with small robot face. Third step shows list of three patters - Range, cluster and outlier with bars beside each to show ranking. Cluster pattern is selected with orange background. The caption reads 'Ranking' and shows a small robot face. The fourth step shows a scatterplot with a cluster selected. One of the points is highlighted in orange. The caption reads 'Confirming intent & annotation' with a human silhouette.
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