AM10 PRINCIPLES OF EFFECTIVE DATA VISUALIZATION

Sunday, October 18, 2015: 9:00 AM - 12:30 PM
Mills Studio 2 (Hyatt Regency St. Louis at the Arch)
Course Director:


Course Type: Half Day
Course Level: Beginner

Overview: This short course will be divided into two sections. In the first, we will introduce participants to techniques for creating effective visualizations based on principles from graphic design and perceptual psychology. We will illustrate how these techniques can be used to create effective visualizations of complex data using a large number of both good and bad examples and case studies drawn from the field. The second section will introduce attendees to a variety of software tools available to create compelling static and interactive graphics, ranging from open source add-ons to Excel and R to independent graphics/visualization tools such as Tableau and JavaScript libraries, and discuss the strengths and limitations of each. After the course, participants will: Understand how principles from perceptual psychology, graphic design and cognitive science can be incorporated into the design and construction of graphics and visualizations Be familiar with the range of tools available to create visualizations and strategies for implementing recommended techniques.

Background: Decision makers must contend with and process a continually increasing amount of data, despite relatively constant perceptual and cognitive abilities. Effective visualization can help combat this information overload and improve comprehension and decision making. Furthermore, in order for science to advance policy and practice it is often necessary to move research results beyond the tables and static graphics common in academic publications. Dynamic and compelling visual representations could help engage and disseminate scientific results to a broader audience. In this course, attendees will learn basic principles of effective data visualization, which are grounded in graphic design and perceptual psychology. Attendees will also be introduced to a number of software tools that can be used to create interactive data visualizations.

Format Requirements: The course will include didactic lectures, discussions, and case studies. This course is designed for those with little or no prior training in data visualization.

Description and Objectives: Decision makers must contend with and process a continually increasing amount of data, despite relatively constant perceptual and cognitive abilities.  Effective visualization can help combat this information overload and improve comprehension and decision-making.  Furthermore, in order for science to advance policy and practice it is often necessary to move research results beyond the tables and static graphics common in academic publications.  Dynamic and compelling visual representations could help engage and disseminate scientific results to a broader audience.  In this course, attendees will learn basic principles of data visualization, which are grounded in graphic design and perceptual psychology. Attendees will also be introduced to a number of software tools that can be used to create interactive data visualizations. 

This short course will be divided into two sections.  In the first, we will introduce participants to techniques for creating effective visualizations based on principles from graphic design and perceptual psychology.  We will illustrate how these techniques can be used to create effective visualizations of complex data using a large number of both good and bad examples and case studies drawn from the field.  The second section will introduce attendees to a variety of software tools available to create compelling static and interactive graphics, ranging from open source add-ons to Excel and R to independent graphics/visualization tools such as Tableau and d3.js, and discuss the strengths and limitations of each.   

After the course, participants will:

  • Understand how principles from perceptual psychology, graphic design and cognitive science can be incorporated into the design and construction of graphics and visualizations
  • Be familiar with the range of tools available to create visualizations and strategies for implementing recommended techniques.  
Course Director:

Carrie Bennette, MPH, PhD
University of Washington
AHRQ Patient-Centered Outcomes Research K12 Scholar
Pharmaceutical Outcomes Research and Policy Program

Course Faculty:

Catherine Richards, MPH, PhD
Hutchinson Center for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center
Staff Scientist (equivalent to Assistant Research Professor)

I am a staff scientist at the Hutchinson Institute for Cancer Outcomes Research at Fred Hutch in Seattle, Washington and an adjunct assistant professor of Epidemiology at Columbia University. I have a PhD in epidemiology with expertise in hospital finance, multi-level modeling, and applying Geographic Information System (GIS) methods to health services research. My expertise also includes effectively communicating public health research through data visualization. Dot Data is a blog I created and maintain with the purpose of visualizing public health.