DynaVis: Dynamically Synthesized UI Widgets for Visualization Editing
Priyan Vaithilingam, Elena L. Glassman, Jeevana Priya Inala, Chenglong, Wang

TL;DR
DynaVis combines natural language commands with dynamically generated UI widgets, enabling users to efficiently edit visualizations with immediate feedback, overcoming limitations of traditional GUIs and NLIs.
Contribution
The paper introduces DynaVis, a novel system that synthesizes UI widgets based on natural language input to improve visualization editing.
Findings
Participants preferred DynaVis over NLI-only interface.
DynaVis enhances editing confidence and ease of use.
Provides immediate visual feedback during editing.
Abstract
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 DynaVis over the NLI-only interface citing ease of further edits…
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Taxonomy
TopicsSoftware Engineering Research · Multimedia Communication and Technology · Usability and User Interface Design
