Welcome to episode 26 of Data Viz Today. Being able to see the difference between well-designed and poorly-designed data viz is half the battle! But when your work always looks amateurish to you, it can be really frustrating. In this episode, host Alli Torban identifies specific ways that you can close the gap between your good taste and your developing skills. Featured data visualization by Jane Pong perfectly illustrates how dense data can still be designed in a clean and engaging way, and I take notes from her to remake my viz from a past episode!
Welcome! I'm Alli Torban.
00:25 - Today’s episode is about how to cultivate your design eye. I think before you can design well, you need to be able to see the difference between good and bad design. It comes more naturally to some people than others, but that doesn’t mean it’s not learnable! This is important because by training your design eye, you can elevate your taste and know what it takes to create even more beautiful and functional data viz.
01:45 - In this episode, we’ll talk about the viz that inspired this, how it was built, and my 3-step process that I’m going to call the “IRA method” that I plan to execute every time I come across a data viz that I love so that I never waste an opportunity to further cultivate my design eye.
02:09 - Today’s featured data viz project is called “Rain Patterns” by Jane Pong. Jane is a data visualisation designer based in Hong Kong.
02:20 - I came across Jane’s viz because she was interviewed by Jon Schwabish from the PolicyViz podcast.
02:55 - Her viz was exactly what I tried to do in my inspired viz in episode 23 where I wanted to show daily rainfall in D.C. over the past decades, except Jane did it for a Chinese newspaper back in 2013 and her design was so beautiful.
03:15 - Jane created this viz because Hong Kong was heading into the monsoon season and she was curious to see whether it occurred at the same time every year, and when the typhoons were happening. The daily rainfall and cyclone warning data is from the Hong Kong Observatory.
03:40 - Design inspiration: She knew she wanted to create a bar graph showing daily rainfall, but wanted to invert the y-axis so the bars looked like they were falling down from rather than rising up out of the axis. She thought it’d be a really nice visual metaphor for rain falling, which was inspired by Simon Scarr’s viz on the Iraq War where he showed the number of fatalities in red as if it was blood dripping down.
04:18 - Jane said the hardest part of creating this viz is that back in 2013 she was just getting into data viz and her coding skills were pretty minimal so she spent a lot of time looking up how to load the data and draw the data with code. Another wrinkle is that since she was creating this for a newspaper, it had to published with the right timing, so she had to update the graphic several times while she was waiting for the rain to come!
04:50 - The final viz was created in Processing, exported as a PDF and touch up for publication in Adobe Illustrator.
05:58 - After seeing Jane’s viz, I became super interested in figuring out WHAT made the design of her viz so beautiful and effective?
06:18 - It’s easy to see good design and appreciate it and also feel frustrated that your own designs look so amatear in comparison to others, but that thought reminded me of a short video by Ira Glass that I had seen a while ago. In the video, he said “If you’re someone in a creative field, you probably started because you have good taste.” And he went on to make the point that when you first start creating, there’s a gap between what you are capable of creating and what you think is good. And it’s frustrating… and this is where most people quit because it’s hard making amateurish work when you know it looks amateurish… but keep pushing! Ira says to keep creating because through practice you can start closing that gap.
07:22 - If I can analyze good design in an intentional way, I can start training my design eye to see all of the little choices that produce really amazing work. Which also reminds me of Andy Kirk’s blog series called “The Little of Visualisation Design” where he highlights and comments on a small design choice that can make a big difference in data viz.
08:23 - I put together three questions to ask yourself whenever you see a data viz that you really like, so you can quickly identify what’s making it good design so you’ll know how to apply it to your own work.
1. What is my first impression? What feelings or emotions is it bringing out in me?
2. What makes it easy to read? Things like visual hierarchy, font choices, color, and sizing. It’s general readability.
3. What’s making this viz stand out or unique? What specifically is making it so alluring to me?
09:00 - So in honor of the sage advice from Ira Glass, I’ll use the acronym IRA to remember these questions: Impression, Readability, Allure.
09:15 - Every time you find a viz that pulls you in, ask yourself IRA and write down your answers: Impression - What’s my first impression? Readability - What’s making this easy to read? Allure - What makes it unique and alluring?
09:27 - And list out a few specific things that are contributing to your answers… like is it specifically the color palette that’s making it alluring? Is it the abundance of white space that’s making it easy to read?
09:40 - Listen for how I put the IRA method to the test on my data viz from episode 23 using Jane’s viz as inspiration!
12:55 - My final takeaway is that we should take the advice of Ira Glass - don’t be discouraged if your work doesn’t match up with your taste - be patient and keep practicing and you’ll close the gap. Specifically for data viz, take a well designed viz and turn it into actionable edits to your work by using this IRA method. Write down what exactly is giving you a good first impression of the viz, what exactly is making it so readable, and what’s giving it that special allure or uniqueness. By taking note of these little design decisions, we can cultivate our taste and design eye so that we can edit our own work in a more refined and elevated way, and keep closing that gap.
13:40 - Jane’s advice to designers just starting out: “Always remember the audience you’re designing for, and what you want to achieve with your data visualisation. Experiment and iterate, and judge your designs based on the goals you want to achieve.”
14:10 - Join the in-person data viz book club if you’re in the Northern Virginia area.