I was excited and honored that I won Tableau's "Evil Viz" contest last week. Thank you Tableau for the awesomely evil Funko Darth Vader (that you see in the picture at the left)! After seeing some of the other entries, I wasn't very optimistic about my chances. However, even though I was in it to win it, I also wanted to show that I could learn from my previous entry in the sports contest. I wrote about 4 lessons that I learned from my hockey stats entry previously. Let's see how I applied those lessons to my Evil Viz submission.
- Less is more. With my evil viz submission I kept the data points to a minimum and the types of methods to a minimum as well. I had just enough data points to fit on the visual without the map looking too cluttered. I also choose a handful of methods of doom. This kept both the map and legend part of the visual looking clean and neat.
- Data visualizations should be visual! Yes, as I said previously this should be a no-brainer. However I am very good at overlooking things that should be no-brainers. For the evil viz I managed to find compelling, relevant shapes to use as my data points on the map. My particular favorite was the evil monkey from Family Guy. I wasn't even thinking of that monkey when I created that method. I just thought the idea of evil monkeys was fun. The ray gun and robot were playful and obvious (for the most part).
- Reign in my use of various font sizes. I chose one font style and pretty much kept the sizes consistent throughout the visual. I thought the Lucinda font was probably the best "evil mad scientist" font available from the list I had to choose from.
- Less ego. This part is difficult for me. Not because I am egotistical, but because I can have difficulty putting myself in someone else's shoes and seeing what I make from their perspective. However, I think the first three lessons made this last lesson a success. By keeping it simple, making it visual, and not cluttering up the visual with obnoxious fonts, I was able to create a visual that was appealing AND told a story.
So what did I learn from this visual? How to tell a story. Data visualizations should tell a story. I have a hard time with that concept because I like data for the sake of data. I like exploring data. I like mashing up stats against one another, comparing and contrasting. But being able to create a visualization like this from scratch, especially one with a creative theme as a guide, helped me develop a better appreciation for the story telling of data visualizations. I have already begun to map out future projects with this new line of thinking. What is the story I want to tell, and then how do I tell it. It sort of goes back to the "less ego" lesson. I prefer data to be more like a choose your own adventure. But not everyone likes that. Some people like a story that is read front to back with a moral at the end.
On to the next data viz creation!