This resource page features course content from the Knight Center for Journalism in the America's massive open online course (MOOC), titled "Data Visualization for Storytelling and Discovery." The four-week course, which was powered by Google, took place from June 11 to July 8, 2018. We are now making the content free and available to students who took the course and anyone else who is interested in learning how to create data visualizations to improve their reporting and storytelling.
The course was taught by Alberto Cairo, He created and curated the content for the course, which includes video classes and tutorials, readings, exercises, and more.
The course materials are broken up into four modules:
As you review this resource page, we encourage you to watch the videos, read the readings, and complete the exercises as time allows. The course materials build off each other, but the videos and readings also act as standalone resources that you can return to over time.
We hope you enjoy the materials and share them with others who are interested in learning more about how to use data visualizations to improve reporting and storytelling. We also encourage you to visit the Google News Initiative’s training site for journalists -- g.co/newstraining. If you have any questions or comments, please feel free to email us at email@example.com.
Alberto Cairo is the Knight Chair in Visual Journalism at the University of Miami. He’s also the director of the visualization program at UM’s Center for Computational Science. Cairo has been a director of infographics and multimedia at news publications in Spain (El Mundo, 2000-2005) and Brazil (Editora Globo, 2010-2012,) and a professor at the University of North Carolina-Chapel Hill. Besides teaching at UM, he works as a freelancer and permanent consultant for companies like Google. He’s the author of the books The Functional Art: An Introduction to Information Graphics and Visualization (2012) and The Truthful Art: Data, Charts, and Maps for Communication.
This module offers an introduction to visualization, what it is, how it works, and what ethical considerations are involved in its design. It also teaches how to prepare data before visualizing it, which will be covered in module 2.
Module 1 will cover
2. What Visualization Is
3. Elements of Visualization
4. Identifying Encodings
5. The Core Principles
6. What Comes Next
1. Data Cleaning with Excel
2. Excel Pivot Tables
Introduction to Data Wrangler
2. Wide To Long
Files for Wrangler VideosDownload
5. Tidy Data
This module covers how visualization can be used to explore and discover features that often hide behind data. The materials will show you how to use software tools that will allow you to import a data set and then visualize it in multiple ways to reveal patterns and exceptions to those patterns.
Module 2 will cover
Files for INZight VideosDownload
Look for an interesting data set in public sources (https://data.worldbank.org/) or any other public source for global, national, or local data), explore it, and write down what interesting features you've find in it. Remember that visualization never gives you answers, but it can suggest what leads to follow, by revealing compelling facts hidden in the data.
GoalsThis module explains how visualization can be used to communicate with the public. The video classes will show you how to use a Google tool called Flourish, to design static and interactive maps and charts, and then put them together in sequential narratives.
Module 3 will cover
Videos1. Choosing Encoding
Readings1. The Truthful Art, Chapter 5
Flourish Videos1. Introduction to Flourish
Files for Flourish VideosDownload
1. Take the U.S county data set used in the Flourish tutorials and see whether you can design a compelling visualization (or a series of visualizations, forming a story) based on the data. For instance:
2. To design this project you may need to do more than merely visualize data. Try to find papers or articles that may help you make your visual story more solid.
3. You are not limited to the data file I used in the tutorial. You can look for complementary datasets if you need to.
This module is focused on designing a visualization based on a topic and data sets of your choice.
Module 4 will cover
Design a personal visualization. Choose any topic, choose a data set, and build a visualization based on it. We can give students ideas ("Does economic growth lead to more CO2 emissions?”) but this should largely be their personal exercise.