Abstract
User experiments are an important part of visualization research, yet they remain costly, time-consuming to create, and difficult to prototype and pilot. The process of prototyping a study—from initial design to data collection and analysis—often requires the use of multiple systems (e.g. webservers and databases), adding complexity. We present reVISitPy, a Python library that enables visualization researchers to design, pilot deployments, and analyze pilot data entirely within a Jupyter notebook. ReVISitPy provides a higher-level Python interface for the reVISit Domain-Specific Language (DSL) and study framework, which traditionally relies on manually authoring complex JSON configuration files. As study configurations grow larger, editing raw JSON becomes increasingly tedious and error-prone. By streamlining the configuration, testing, and preliminary analysis workflows, reVISitPy reduces the overhead of study prototyping and helps researchers quickly iterate on study designs before full deployment through the reVISit framework.
BibTeX
@article{shrestha2025revisitpy,
author = {Hilson Shrestha and Jack Wilburn and Brian C. Bollen and Andrew M. McNutt and Alexander Lex and Lane Harrison},
editor = {Alexandra Diehl and Kostiantyn Kucher and Nicolas M{\'{e}}doc},
title = {ReVISitPy: Python Bindings for the reVISit Study Framework},
booktitle = {27th Eurographics Conference on Visualization, EuroVis 2025 - Posters, Luxembourg City, Luxembourg, June 2-6, 2025},
publisher = {Eurographics Association},
year = {2025},
url = {https://doi.org/10.2312/evp.20251133},
doi = {10.2312/EVP.20251133},
timestamp = {Mon, 17 Aug 2026 14:43:44 +0200},
biburl = {https://dblp.org/rec/conf/vissym/ShresthaWBMLH25.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}