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
This blog post was triggered by UpSet winning the 10-year Test of Time Award at IEEE VIS. In this post, I reflect on how UpSet came about, and what made it successful.
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.
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!
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.
