We’ve always jokingly dreamt about creating an annual report of our work at Sheldon.studio. However, by the time we committed to the idea, our data was scrappily documented in bits and pieces. So, we decided to visualize the real, messy sh*t: the code, the pixels, the clutter of emails, the locations of people who viewed our projects and the music we grooved to while crafting our projects. So here you go, the visualized organized chaos of everyday life in a design studio...
What we did
Client
Self-commissioned
How do you visualize a year in data design through data design? Well, we told the story of our three largest projects of 2020, through their metadata, adding a special Sheldon touch. That’s why you’ll find, among other quirky data visualizations, the vinyl collection we grooved to in 2020.
One year of the good vibes and moods that comforted us through the lockdown!
While we were digging into the data we wanted to visualize in our annual report, we realized how many data points were impossible to collect accurately and how many data points were totally misleading. Many of our biggest projects we’re summarized in a few lines of code. Would it make sense to represent one of these projects with a scarce bit of code? Nope. That’s called data porn - using visualizations even when they tell inaccurate stories - and we avoid it. But this time we took the opportunity to explore, and visualize, the fact that data can lie.
What is data porn?
It’s a neologism to describe attractive data visualizations, that – once you take a closer look - don’t really paint an accurate picture of the data itself.
The numbers don’t lie.
That’s one of the biggest myths regarding data - and we demonstrated it with our first annual report.
If data is the new oil, we need to seriously consider the environmental harm it can do. When data is partially or inaccurately collected, it can paint a very misleading picture and the consequences are often detrimental. So, before taking data-based decisions, be sure to think twice about where that data comes from, how it was collected, in which way and by who? Who does it represent and who does it exclude?
Even though our annual report was a silly project, we hope it raises awareness about the importance of considering the quality of data.