DynaVis: Dynamically Synthesized UI Widgets for Visualization Editing

Fuente: arXiv
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Hauptverfasser: Vaithilingam, Priyan, Glassman, Elena L., Inala, Jeevana Priya, Wang, Chenglong
Format: Preprint
Veröffentlicht: 2024
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author Vaithilingam, Priyan
Glassman, Elena L.
Inala, Jeevana Priya
Wang, Chenglong
author_facet Vaithilingam, Priyan
Glassman, Elena L.
Inala, Jeevana Priya
Wang, Chenglong
contents 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 and editing confidence due to immediate visual feedback.
format Preprint
id arxiv_https___arxiv_org_abs_2401_10880
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle DynaVis: Dynamically Synthesized UI Widgets for Visualization Editing
Vaithilingam, Priyan
Glassman, Elena L.
Inala, Jeevana Priya
Wang, Chenglong
Human-Computer Interaction
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 and editing confidence due to immediate visual feedback.
title DynaVis: Dynamically Synthesized UI Widgets for Visualization Editing
topic Human-Computer Interaction
url https://arxiv.org/abs/2401.10880