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What is reVISit?

The reVISit project addresses a critical bottleneck in visualization research: how can we better and more efficiently empirically evaluate visualization techniques? ReVISit aims to democratize evaluation of interactive visualization techniques, an area that has been under-explored, due in part to the high technical burden and skills required to create complex online experiments.

The key innovations of this project are:

  1. Flexible study creation based on a domain-specific language, the reVISit Spec.
  2. Simple data collection — out of the box for standard response types, but with the ability to track detailed events based on provenance-enabled stimuli.
  3. Simple data storage — no need to run your own servers: data is stored in a relatively easy to set-up Firebase instance.
  4. Open source and free – share your study design with anyone, no license required.
  5. Compatible with crowdsourcing platforms — recruit your participants through your preferred provide, such as Prolific, Mechanical Turk, or Lab in the Wild.
  6. Keep track of study progress — see how participants are doing and identify issues with your study quickly.
  7. Export your data — in a format suitable for your analysis.

Demo​

You can check out a few example projects on our demo page. All of the demos on this site are build from stimuli and examples that you can find in the github repo.

Check out the getting started tutorial to learn how to build your own experiment.

Paper​

If you are using reVISit for a paper, please cite:

Paper Reference

Zach Cutler, Jack Wilburn, Hilson Shrestha, Yiren Ding, Brian Bollen, Khandaker Abrar Nadib, Tingying He, Andrew McNutt, Lane Harrison, Alexander Lex.
ReVISit 2: A Full Experiment Life Cycle User Study Framework.
IEEE Transactions on Visualization and Computer Graphics (VIS), 32: 2026.
 IEEE VIS 2025 Best Paper Award

If you use version 1 of reVISit, please cite:

Paper Reference

Yiren Ding, Jack Wilburn, Hilson Shrestha, Akim Ndlovu, Kiran Gadhave,
Carolina Nobre, Alexander Lex, Lane Harrison.
reVISit: Supporting Scalable Evaluation of Interactive Visualizations
IEEE Visualization and Visual Analytics (VIS), 31-35, doi:10.1109/VIS54172.2023.00015, 2023.

Project Team​

reVISit is a project developed at the University of Utah and Worcester Polytechnic Institute.

Alexander Lex, Co-PI, University of Utah
Lane Harrison, Co-PI, WPI
Zach Cutler, PhD Student, University of Utah
Yiren Ding, PhD Student, WPI
Tingying He, Postdoc, University of Utah
Jay Kim, Software Engineer, University of Utah Andrew McNutt, Assistant Professor, University of Utah
Hilson Shrestha, PhD Student, WPI
Jack Wilburn, Senior Software Engineer, University of Utah

Alumni​

Carolina Nobre, Co-I, University of Toronto
Brian Bollen, Senior Software Developer, University of Utah
Kiran Gadhave, PhD Student, University of Utah
Akim Ndlovu, PhD Student, WPI

Contact​

If you have any questions, please e-mail us.

Acknowledgements​

reVISit is funded by the National Science Foundation, under the title "Collaborative Research: CCRI: New: reVISit: Scalable Empirical Evaluation of Interactive Visualizations", trough CNS with award numbers 2213756 and 2213757.

We are grateful to Cindy Xiong Bearfield, Lace Padilla, and Danielle Albers Szafir for advice on the requirements of a study platform.