When you have it all visualized, it really jumps at you. — Giorgia Lupi
Update: Check out the postcards you mailed us here!
For 52 weeks, Giorgia Lupi and Stefanie Posavec built their friendship one postcard at a time. Lupi and Posavec are both data visualization professionals who met at a conference, and beginning in the fall of 2014 they decided to send one postcard to each other every week with a hand-drawn rendering of an agreed-upon data set: animals they saw, drinks they drank, desires they had, compliments they gave or received. They called their project “Dear Data.” It’s a website now and will be a book in September.
On this week’s What’s The Point, Lupi and Posavec discuss what their project taught them about living a quantified life, and how they became more attuned to their surroundings as they also learned more about each other. Stream or download the full episode above, or subscribe using your favorite podcast app.
And now it’s your turn. We’re asking you to take part in a Dear Data-esque project by spending one week collecting a data set of your own and then visualizing it. Here’s the angle: Pick one week (any week-long stretch in the month of March) and keep track of all your podcast listening. Then, visualize it on a postcard, and mail it to me:
147 Columbus Ave, 4th Floor
New York, NY 10023
We’ll feature some of our favorites on the site, and one of our favorites will get a copy of the “Dear Data” book when it comes out in September.
If you want to take part, keep in mind the basic rules of the Dear Data series:
- The front of your postcard should only feature the visualization.
- On the reverse, include a legend to explain your work.
- You can use any shapes, colors, or materials you want, just as long as it fits on a postcard. But be creative! Can you move beyond a bar chart?
For inspiration, check out the full Dear Data gallery.
I asked Giorgia and Stefanie (who are also going to take part in the challenge) for some advice about how one might go about tackling this particular data challenge. Here’s what they had to say:
Tracking personal data around a vague topic can be scary and paralyzing. An easy way to start is by asking a question: What do you want to know and explore?
For example, you can start by setting up your main question:
- How much of my time do I spend listening to podcasts?
- What are the podcasts I listen to?
And then set up additional questions to both answer your main question, and add details and context to your logs:
- What time of day do I listen?
- For how long do I listen?
- Where am I when I listen?
- What genre of podcasts do I listen to?
- How do they make me feel?
- While listening, do I get distracted at any point?
- Do I listen to an entire episode or do I skip some parts?
The questions you ask are up to you!
- Record your data in real time. Set up a log on a piece of paper, or on your phone, and make sure you record your data right away, rather than waiting until the end of the day. That will make sure your data is more accurate.
- Try to collect everything you can. Allow yourself a way to add any miscellaneous details. They might be important later!
- Be honest! No cheating, no fudging of the data — personal discovery comes through being honest with yourself.
At the end of the week, analyze and visualize your data:
- Start looking for patterns, identify categories and anomalies. You can use different colors to highlight the different categories and start “seeing” them.
- Visually count your logs. You can use simple tally marks to get a sense of the numbers, the quantities, and then play with simple attributes. Every mark represents one of your logs and even merely color-coding these offers a chance for insight. Try alternative ways of sorting your data and see what jumps out: Use colors to see patterns, highlight anomalies, visualize only a subset with more attributes, etc.
- How do you want to tell your story? Starting from your analysis, identify how you want to tell your data’s story. Chronologically? Per group of entries? Per importance or rankings of the entries? Geographically? This will lead you to decide the “architecture” (or layout) of your data drawing. Choose what feels best for your data and start to play around.
- Create your personal legend with your personal rules for visualization. Assign your entries visual attributes according to your analysis. What do different shapes and colors represent, for instance?
The final step: Draw your postcard (visualization on the front, legend on the back) and put it in the mail! Deadline: Any seven-day stretch in March. We’re flexible.
We’ll continue to update the project as we collect your submissions!
If you’re a fan of What’s The Point, subscribe on Apple Podcasts, and please leave a rating/review — that helps spread the word to other listeners. And be sure to check out our sports show Hot Takedown as well. Have something to say about this episode, or have an idea for a future show? Get in touch by email, on Twitter, or in the comments.