introducing the 2018 #SWDchallenge

One of the best ways to learn is to do. This is something I strongly believe. We learn and get better through practice and application. It is by practice and practice—and more practice—that I’ve sharpened my own data visualization, presentation, and storytelling skills. I believe that you can do so as well.

While practicing on the job is great, it can also present some challenges. Constraints are often imposed. It can at times feel like a scary (or even risky) place to test out something new. But what if there were a safe space each month where you could take a turn flexing your skills or trying something you haven’t attempted before?

To that end, I’m happy to launch the 2018 monthly #SWDchallenge. Each month will have a different topic—I’m planning to start with some different graph types, but may change this up as we go along. I’ll announce the focus at the beginning of each month and share some related thoughts and examples. Then I’ll turn it over to you. You’ll have a week to find your data, create your visual and write any commentary you’d like to go with it (full specs follow). I’ll circle back with a follow up post later in the month, where I’ll share back what you’ve shared with me.

Think of this as a safe space to try something new: test out a new tool, technique, or approach. Or simply take it as a reason to practice as you continue to hone your data visualization and data storytelling skills. There’s no obligation—participate in one, a couple, or all. You are welcome to remain anonymous (I’ll only share first name and possibly last initial, though I’m also happy to include your social media profile or site if you’d like).

The instructions are simple:

  • Make it. Identify your data and create your visual with the tool of your choice. If you need help finding data, check out this list of publicly available data sources. You are welcome to use a real work scenario, but please don’t share any confidential data.
  • Share it. Email your entry to SWDchallenge@storytellingwithdata.com by the deadline (midnight PST). Attach your image as a .PNG. Put any commentary you’d like included in my follow up post in the body of the email; if there’s a social media profile or blog/site you’d like mentioned, please embed the links directly in your commentary. Note: if you’re going to write more than a paragraph or so, I encourage you to post it externally (I believe LinkedIn allows for posts like this) and provide a link or summary for inclusion here.
  • The fine print. I reserve the right to post and potentially reuse examples shared.

Now that we've covered those details, let's move on to the first challenge...

JANUARY #SWDchallenge: annotated line graph

While not always the case, I find frequently that the line graphs I use depict time. When you have time on the x-axis, you have a natural built-in construct for storytelling: the chronological story. When presenting data live, I’ll often build the time series point by point, talking the audience through the interesting context as I show the relevant data. Then I end with a final version where the most important parts of this context are annotated directly on the graph. This is the version that would be sent around (where you aren’t there to talk through it) and the audience has to process it on their own. Let's look at a few examples of annotated line graphs.

There is an example in the book I highlight in Chapter 9 that illustrates a progression similar to what I outline above, then I summarize with the following annotated line graph:

 

One amusing annotated line graph—one of my personal faves—that I sometimes discuss in my workshops was created by David McCandless and Lee Byron:

 

For another business example, here's an annotated line graph I created for a recent workshop based on a client example (details changed to protect confidentiality):

 

This is all prelude for my inaugural challenge for you: to create an annotated line graph. Sure, you’ve likely made a line graph before. But what could you try out that’s a little different this time? Or what data might you look at to learn something new?

Submit your entry, following the instructions above, by Tuesday, January 9th. Stay tuned for a post later in the month where I'll summarize the examples received. I look forward to seeing what you come up with!