Creating better models for data visualization

One of the easiest ways for people to take in new information is undoubtedly through a visual medium. Humans are, after all, visual creatures, going through their lives navigating principally by means of sight. So it makes sense that it would be desirable for anyone working in the area of information visualization — and more specifically communicative visualization (infographics, graphs and the like) — to better understand the best way to get one’s point across visually.

UMSI associate professor Eytan Adar aims to help with that. With a grant from the National Science Foundation for his project “Using Learning Objectives for Visualization Design,” Adar is working to better understand what sorts of visualizations work and why. Throughout the course of the project, Adar intends to develop methods of determining suitable learning objectives (things the designer wants the viewer to take away from the data visualization) and the best ways of testing whether those learning objectives are being met. Pushing this idea further, he will then work towards the creation of a set of tools that can be used “to support the practical and rapid and efficient creation” of learning objectives and test materials for one-off visualizations. 

In order to do this, Adar will use data mining techniques and natural language generation to create tools which can be employed in transforming ill-specified design goals into “actionable tests that quantify absolute and relative benefits of a visualization.” Furthermore, in order to validate his methods and the tools he develops he will seek to evaluate whether designers (journalists, scientists) tend to create more effective visualizations given design-oriented goals, rather than learning objective-oriented ones.  

Ultimately, the end goal of Adar’s project is to create a more efficient, results-oriented model for the way designers approach their visualization work. Through doing so, designers will improve the clarity and intent of their visualizations, and viewers will come away from their visualization viewing experience far better informed than they would otherwise be. 

Adar will receive $499,747 in grant money from the National Science Foundation over the project period, August 2018-July 2021.

Posted November 20, 2018