Jinhan Choi
Boston College, Chestnut Hill, Massachusetts, United States
When creating a visualization, designers face various conflicting design choices. They typically rely on their hunches to deal with intricate trade-offs or resort to feedback from their colleagues. On the other hand, researchers have long used empirical methods to derive useful quantitative insights into visualization designs. Taking inspiration from this research tradition, we developed VisLab, an open-source online system to complement the existing qualitative feedback practice and help visualization practitioners run experiments to gather empirically informed design feedback. We surveyed practitioners’ perceptions of quantitative feedback and analyzed the research literature to inform VisLab’s motivation and design. VisLab operationalizes the experiment process using templates and dashboards to make empirical methods amenable for practitioners while supporting sharing and remixing experiments to aid knowledge exchange and validation. We demonstrated the validity of experiments in VisLab and evaluated the usability and potential usefulness of VisLab in visualization design practice.
https://doi.org/10.1145/3544548.3581132
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)