Data Formulator: AI-powered Concept-driven Visualization Authoring
This addresses the problem of data transformation complexity for visualization authors, offering an incremental improvement by automating steps that previously required programming or separate tools.
The authors tackled the barrier of data transformation in visualization authoring by introducing a new paradigm called concept binding, which uses an AI agent to separate high-level intents from low-level steps, resulting in a tool that enabled participants in a user study to create visualizations involving challenging transformations.
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.