Welcome to episode 33 of Data Viz Today. How can you consistently generate interesting visual story ideas from your data set? I’ve been on a quest to find a process for this, and I recently found guidance in a book for authors who are trying to get their non-fiction short stories published by editors. I used what I learned to create a worksheet that brings me from a basic stat to eight story ideas! In this episode, you’ll learn about the reasoning behind it and hear it in action. DOWNLOAD THE WORKSHEET
Welcome! I'm Alli Torban.
01:34 - In this episode, I’ll share the 3 things I learned that editors look for when they publish non-fiction short stories, how that led me to creating a data viz workflow diagram that takes me from one basic stat to eight relevant story angles, and of course I’ll show it in action with an example!
01:53 - If you’re ready to create fully customizable charts in Adobe Illustrator, check out my new course → Design Your First Visualization in Adobe Illustrator in Under 30 Minutes
02:43 - The book I was reading is called The Byline Bible by the writing professor Susan Shapiro. It’s a guide for authors of non-fiction short stories on how to get published in magazines and newspapers. I saw so many parallels between her advice to writing relevant short stories that will get an editor to publish you, to creating a visualization out of a data set that’s going to mean something to someone.
03:20 - So from the book, there were three pieces of advice for getting published that I thought were super relevant to finding a story in data.
1. Avoid the obvious. You want to focus on drama, conflict, and tension. Susan Shapiro says in her book: “confront unresolved emotional issues about something that’s bothering you.” What’s the use in visualizing something that everyone already knows?
2. Make it timely. You need to compel your reader with a fresh angle or a reason why now is the time to take notice.
3. Clarify your emotional arc. Susan says “start in delight, end in wisdom” - you want to start strong, introduce conflict, and have a resolution. For data viz, the start strong part I think is wrapped up in the visuals - to varying degrees you’ll use your design to catch someone’s eye, then your angle on your data will introduce the conflict and possibly resolution, depending on whether it’s exploratory or explanatory.
04:25 - Ok, then I took these three elements and made a workflow diagram out of it to use before I do any analysis to get me warmed up and ideally take me from one statistic or fact, and turn it into 8 possible interesting angles to pursue.
04:51 - First, write your stat or fact at the top. Then we move into conflict: If that stat is true, then what’s the consequence? Who is affected? Then tackle the timeliness of each consequence: Why is this important now? If it’s not, what can I compare it to that is important now? Then think about possible resolutions: What can help? What action can we take?
06:10 - Listen for my example using the Makeover Monday dataset on avocados!
08:44 - My final takeaway is that you can take an editor’s viewpoint, and squeeze interesting angles out of your dataset so that your visualizations are telling a compelling story. So try out this workflow, and let me know if it’s helpful to you! Remember you’re looking for Conflict, Timeliness, Resolution.