DynaVis: Dynamically Synthesized UI Widgets for Visualization Editing

要旨

Users often rely on GUIs to edit and interact with visualizations - a daunting task due to the large space of editing options. As a result, users are either overwhelmed by a complex UI or constrained by a custom UI with a tailored, fixed subset of options with limited editing flexibility. Natural Language Interfaces (NLIs) are emerging as a feasible alternative for users to specify edits. However, NLIs forgo the advantages of traditional GUI: the ability to explore and repeat edits and see instant visual feedback. We introduce DynaVis, which blends natural language and dynamically synthesized UI widgets. As the user describes an editing task in natural language, DynaVis performs the edit and synthesizes a persistent widget that the user can interact with to make further modifications. Study participants (n=24) preferred \tool over the NLI-only interface citing ease of further edits and editing confidence due to immediate visual feedback.

受賞
Best Paper
著者
Priyan Vaithilingam
Harvard University, Cambridge, Massachusetts, United States
Elena L.. Glassman
Harvard University, Cambridge, Massachusetts, United States
Jeevana Priya Inala
Microsoft, Redmond, Washington, United States
Chenglong Wang
Microsoft Research, Redmond, Washington, United States
論文URL

https://doi.org/10.1145/3613904.3642639

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Visualization and Sonification

323C
5 件の発表
2024-05-16 18:00:00
2024-05-16 19:20:00