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: Lessons Learned from Visualizing Multimodal Data... with Aardvarks... 30 Sep 2024
How do you analyze data with multiple modalities – say, images, trees and time-series? If you ask a visualization researcher, we will tell you visualizations are the solution, specifically composite visualizations! This blog shares some lessons we learned designing and developing composite visualizations to help understand cancer cell development. Regarding the aardvarks... this is clickbait, mostly. But we did get a best paper award for this project at IEEE VIS.

A cartoon anthropomorphized aardvark with boxing gear faces off against a gross cancer cell. The aardvark is determined to defeat the cancer cell. The cancer cell is afraid because it knows it is about to be whomped by the aardvark.
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Blog Post: reVISit: Taking Control of Your Online Studies! 20 Jun 2024
Today we’re announcing the release of reVISit version 1.0, our open platform for designing, debugging, publishing, and disseminating your online visualization user studies!

Diagram of the revisit workflow. The study specification and components are used to compile an interactive, web-based study. As participants complete the study data is stored in Firebase and can be downloaded as tabular or JSON files, for subsequent analysis in analytics tools.
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Blog Post: Persist — A JupyterLab Extension for Persistent Interactions 29 May 2024
Computational notebooks like JupyterLab have become indispensable tools, enabling seamless integration of code, visualizations, and text. However, modern notebooks limit the usefulness of interactions in visualizations in two significant ways. First, the results of interactions in visualizations cannot be accessed in code. For example, a filter applied in a visualization cannot be applied directly to the data in the notebook. Second, unlike code changes, interactions with data visualizations are transient — they are lost when the cell is re-executed or the kernel is restarted. In this post, we introduce our solution to these issues: Persist, a JupyterLab extension that enables persistent interaction and data manipulation with visualizations in notebooks.

Screenshots of the Persist table and visualization view showing Persist in action
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News: Kiran Gadhave Successfully Defends Dissertation 14 Mar 2024
Congratulations to Kiran!

Kiran celebrating that he passed his defense with the committee!

Kiran Gadhave successfully defended his dissertation on “Towards Reproducible and Reusable Visual Analysis”. Kiran was advised by Alex Lex, with Miriah Meyer, Jeff Phillips, Vivek Srikumar, and Marc Streit serving on the committee.

Congrats, and good luck with your next steps!

Kiran presenting

Kiran and Alex

Kiran opening a bottle of champaign

Kiran with a graduation sword

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