In this interview, I talked with Kizley Benedict, the winner of the 8th Data for a Cause challenge - visualizing chicken factory farms for The Humane League and their 88% campaign. The goal of the challenge was to create a map visualization of factory farms.
I talked with Kizley after returning from Tableau's conference in Las Vegas. He found out about the Data for a Cause challenge after seeing the hashtag #dataforacause and data visualizations on Twitter. Kizley has a computer science background; he does data analysis in the IT services industry. Initially his role involved data modelling, and cleaning and preparing data, but since 2016 he has started to seek out projects with a data visualization component.
How did your visualization come together?
I was really inspired by the cause. Learning about the conditions for farm animals was an eye-opener. I learned about the part that can be prevented, through educating people and campaigns, such as the 88% campaign. So I decided I wanted to contribute to the cause. In terms of the visualization, I put a lot of thought into the design and layout. The requirement was for a map, so I decided that the map should be the center of attention in the visualization and to put all the other elements around it.
Initially I considered plotting all the farms on the main US map, but it looked a bit cluttered; you couldn't distinguish the points. So I decided to use a two-level map, where the main map would show the number of farms in each state and the user could drill down to view the location of the individual farms. Next I wanted to draw the user's attention to the issue of animal cruelty, and what the 88 campaign is all about. I filtered out a lot of information and just included the most important points - essentially, what the issue was, what has been done about it, and how you can help. I wanted to keep it very concise and bring the user's attention to these three points.
In terms of the colors in the design: I like the design of the 88 campaign and their website, so I incorporated the same colors. I also like the waffle chart. Instead of the dots I put icons for the animals. I gave a lot of thought to the map. I wanted to show both the number of animals as well as the location of the farms. That's why I decided to break it down into two levels.
How long did it take you to create the visualization? Did you start with a sketch?
I spent a couple of days just thinking about it. Once I had a rough idea in mind, it took about a day. The majority of my time was spent on the design. I knew where I wanted to put the map. I played around with the text and some of the charts. I had to decide where to show the text. I alternated between a waffle chart and a scale that shows the most farms.
I don't usually draw a sketch of the visualization I'm building; I use the export image option in Tableau to continuously check how the visualization looks as I'm working on it.
What are some of your favorite data visualization resources?
I've done some courses on infographics and currently am doing one on Coursera from Michigan State University. I also keep looking at infographics in newspapers and online. There are a lot of data journalism graphs everywhere, and on some level I'm interested in the design of these, so am trying to learn Adobe Illustrator.
I think one of the best ways to learn is by looking at the work of others. I follow the Tableau community. There are a lot of people who are doing great work and I try to learn from them. Apart from the Tableau community, there are people who are doing interesting work on D3 and Adobe Illustrator. So I'm not limited by a tool; I find inspiration wherever I can.
What is your favourite data visualization tool?
Right now it’s Tableau. It is really intuitive, and for beginners not intimidating at all. Within a few hours you can come up with a decent dashboard. You don't need to have a programming background like you do with some other tools. Also, as I mentioned, I've seen D3 visualizations as well, and have been really impressed by interactivity and flexibility it offers.
Kizley's data visualization (click on the image to view the interactive version):