Capturing Audiences with Data Visualization Systems and Pre-attentive Features

Data visualization has nearly unlimited potential but is often only as valuable as the story you are able to tell and the audience you can capture to see you story. In this interactive workshop, you’ll learn the foundations of data visualization. we will discover the power the power of pre-attentive features together, and then will nerd out with visualizations that have gathered national attention (or virality) using what we discovered. The workshop will finish by exploring creating a new visualization using a popular web-based visualization language (d3.js).

Wade Fagen-Ulmschneider is a Teaching Associate Professor of Computer Science at the University of Illinois at Urbana-Champaign (UIUC). With a passion for data, he often teaches thousands of students each year in his courses on Data Structures, Data Visualization, and Data Science. He was selected as one of the National Academy of Engineering’s Frontiers of Engineering Education scholars, awarded the Collins Award for Innovation Teaching, and has been consistently ranked as an excellent instructor by his students for the past ten years. His work on data visualizations has been used by governors of multiple states, featured by websites including Popular Mechanics and The Verge, and has been viewed by millions of readers.

Wade’s passion is at the intersection of systems, data, and creating tools to nerd out with both systems and data through interactive data visualizations. In his work, Wade works to educate, encourage, and inspire folks to change the world. View Wade’s viral data visualizations.

https://waf.cs.illinois.edu/slides/web21/

• PDF Slides of the Presentation
• CSV of Responses to the “Perception of People at a Party” Dataset
• Perception of People at a Party Visualization

Links

• Link 1: Google Form: Perception of People at a Party
• Link 2: GPAs of Every Course at The University of Illinois
• Link 3: 91-DIVOC
• Link 4: 91-DIVOC: Deaths from COVID-19, normalized by population
• Link 5: 91-DIVOC: Deaths from COVID-19 by States/Territories, normalized by population
• Link 6: 91-DIVOC: Daily Change in New Confirmed COVID-19 Cases per Day
• Link 7: d3.js
• Link 8: Perception of People at a Party Visualization