PI2: End-to-end Interactive Visualization Interface Generation from Queries
arXiv:2107.08203 · doi:10.1145/3514221.3526166
Abstract
Interactive visual analysis interfaces are critical in nearly every data task. However, creating new interfaces is deeply challenging, as it requires the developer to understand the queries needed to express the desired analysis task, design the appropriate interface to express those queries for the task, and implement the interface using a combination of visualization, browser, server, and database technologies. Although prior work generates a set of interactive widgets that can express an input query log, this paper presents PI2, the first system to generate fully functional visual analysis interfaces from an example sequence of analysis queries. PI2 analyzes queries syntactically and represents a set of queries using a novel Difftree structure that encodes systematic variations between query abstract syntax trees. PI2 then maps each Difftree to a visualization that renders its results, the variations in each Difftree to interactions, and generates a good layout for the interface. We show that PI2 can express data-oriented interactions in existing visualization interaction taxonomies, reproduce or improve several real-world visual analysis interfaces, generate interfaces in 2-19s (median 6s), and scale linearly with the number of queries.
16 pages
References in corpus (4)
- NL4DV: A Toolkit for Generating Analytic Specifications for Data Visualization from Natural Language Queries
- Scout: Rapid Exploration of Interface Layout Alternatives through High-Level Design Constraints
- Falx: Synthesis-Powered Visualization Authoring
- Demonstration of PI2: Interactive Visualization Interface Generation for SQL Analysis in Notebook
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- DeepVIS: Bridging Natural Language and Data Visualization Through Step-wise Reasoning
- DIG: The Data Interface Grammar
- NoteFlow: Leveraging Charts as Sight Glasses for Consistent and Continuous Data Flow Tracing
- Evaluating Interactivity: Toward Automated Assessment of AI-Generated Explorable Explanations
- VIGMA: An Open-Access Framework for Visual Gait and Motion Analytics