Draco: Formalizing Visualization Design Knowledge as Constraints
Draco is a formal framework for representing design knowledge about effective visualization design as a collection of constraints. This knowledge can be applied with standard constraint solvers to recommend charts or explore the design space of visualization.
You can use Draco to find effective visualization designs in
Vega-Lite. Draco's constraints are implemented in based on Answer Set Programming (ASP) and solved with the
Clingo constraint solver. Draco can learn weights for the recommendation system directly from the results of graphical perception experiments.
You can learn about the Draco knowledge base
in the Draco code. Documentation about the APIs is coming soon.
People
Draco is being developed at the
Interactive Data Lab at the University of Washington. The main contributors are: Dominik Moritz, Chenglong
Wang, Greg L. Nelson, Halden Lin, Adam M. Smith, Bill Howe, and Jeffrey Heer.
