Interactive Data Lab

@idl.uw.edu

Visualization & data analysis research at the University of Washington. In a prior life was the Stanford Vis Group. https://idl.uw.edu

The Mosaic architecture for database-backed interactive visualization just hit 1,000 stars on GitHub! Thank you to all who have participated and contributed!

Screenshot from GitHub showing 1k stars for the Mosaic project, an extensible framework for linking database and interactive views.

People are now using LLMs to create charts and graphs. How might we assess the quality and consistency of the results? DracoGPT is a method that fits a visualization knowledge base (Draco) to LLM responses, enabling comparison across models, prompts, and results from human subjects experiments.

Overview of the DracoGPT-Rank pipeline. (1) User provides prompt templates for an LLM to rank chart pairs; (2) Draco featurizes charts and produces feature vectors consisting of constraint counts; (3) Draco learns constraint weights over LLM-labeled chart pairs by fitting a RankSVM model; (4) The fitted Draco model can be applied to score charts. Results at each stage of the pipeline afford insight into LLM ranking preferences.

Hi Bluesky! 👋 We’re the Interactive Data Lab at UW. We’ll post about data visualization, analysis, and human-computer interaction research, as well as open source projects. Over the years we’ve been involved with Protovis, D3, Data Wrangler (-> Trifacta), Vega/Vega-Lite, Mosaic, and other projects!