Data Formulator: AI-powered Concept-driven Visualization Authoring
September 18, 2023 Β· Declared Dead Β· π IEEE Transactions on Visualization and Computer Graphics
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Authors
Chenglong Wang, John Thompson, Bongshin Lee
arXiv ID
2309.10094
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
47
Venue
IEEE Transactions on Visualization and Computer Graphics
Last Checked
3 months ago
Abstract
With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation remains a barrier in visualization authoring. To address this challenge, we present a new visualization paradigm, concept binding, that separates high-level visualization intents and low-level data transformation steps, leveraging an AI agent. We realize this paradigm in Data Formulator, an interactive visualization authoring tool. With Data Formulator, authors first define data concepts they plan to visualize using natural languages or examples, and then bind them to visual channels. Data Formulator then dispatches its AI-agent to automatically transform the input data to surface these concepts and generate desired visualizations. When presenting the results (transformed table and output visualizations) from the AI agent, Data Formulator provides feedback to help authors inspect and understand them. A user study with 10 participants shows that participants could learn and use Data Formulator to create visualizations that involve challenging data transformations, and presents interesting future research directions.
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