*****About the Talk*****
Charts, graphs, and other information visualizations enhance cognition by allowing users to visually perceive trends and differences in data. While most visualization guidelines dictate how to choose visual encodings and metaphors that will maximize easy reading of the data, it is less obvious how to design visualizations that encourage good decisions and critical thinking about data. Jessica will address several challenges that have to be overcome for visualizations to truly help users reason about data. First, people's intuitions about how reliable data is often conflict with statistical measures of uncertainty. Jessica will describe how visualization techniques for conveying uncertainty by showing a set of sample outcomes can improve non-experts' ability to understand and make decisions from data. Second, people often bring prior beliefs and expectations about data-driven phenomena to their interactions with data (e.g., I suspect support for candidate A is higher than survey respondents reported) which influence their interpretations. Most visualization design and evaluation methods do not account for these influences. Jessica will describe why prior beliefs should matter in visualization interaction and how to create visualizations that encourage users to reflect on their expectations, including a publicly available line chart tool my lab has created to make this easier.
*****About the Speaker*****
Jessica Hullman is an Assistant Professor in Computer Science and Journalism at Northwestern. The goal of her research is to develop computational tools that improve how people reason with data. She is particularly inspired by how science and data are presented to non-expert audiences in data and science journalism, where the goal of conveying a clear story often conflicts with goals of transparency and faithful presentation of uncertainties. Her current research aims to develop uncertainty techniques and interactive visualizations that enable users to articulate prior beliefs and make more informed decisions. Jessica's research has been supported by the NSF (CRII, CAREER), Navy, Google, Tableau, and Adobe.Prior to joining Northwestern in 2018, she spent three years as an Assistant Professor at the University of Washington Information School. She completed her Ph.D. at the University of Michigan and spent a year as the inaugural Tableau Software Postdoctoral Scholar in Computer Science at the University of California Berkeley in 2014.
6:00 - 6:30: mingling and settling in; food and drinks provided by Braintree
6:30 - ~7:15: Jessica Hullman speaks
~7:15 - 8:00: more mingling and food
Thanks to Braintree for hosting and providing drinks and noms!
RSVPs will stop being accepted at noon on the day of the event. An ID will be required to enter. (Please reach out if this is an issue for you.)
Gender-neutral bathrooms available at this location.
And as always, if you are interested in giving a talk or being involved in the organization of the Chicago Data Viz Community meetup in some way, reach out! :)