I think it’s fair to say that all data visualizations kind of look the same. It’s usually the same 3 or 4 types of charts, the only difference is really in color, and it can get a little boring. Maybe that’s a good thing. Data visualizations are all about pattern recognition– that’s why they’re a useful tool. But, if our goal is to keep people engaged… maybe we should be focusing a little more on creativity.

One way to do this that I experimented with this week is the real life data visualization. Taking your data and representing it in the real world, with items related to the data set.

I tried my hand at creating one of these with this data visualization based on the EPA’s breakdown of municipal waste by material for 2018.

It’s to be read as a bar chart– with the y-axis representing what percentage of total trash each material makes up, and the x-axis showing the materials themselves. Yes, this was made with actual trash from my home.

Something important to note is this information is based in tons… so paper is the highest because there’s the most tons of it in landfills… but weight doesn’t necessarily mean there’s more. Paper is a pretty dense material. If you’ve ever picked up a document box you’d know. Meanwhile plastic packaging can be pretty lightweight, so there may well be more of it in volume, but not in weight.

That was a difficulty I hit in trying to make this visualization not misleading. I justified it by assuming data visuals are almost always consumed alongside text, like it is here, where I could explain that. 

Another issue I encountered was trying to make sure my y-axis isn’t misleading. Anytime I think of misleading bar charts, I think of this meme that was going around a few years ago, where someone tried to compare female musicians’ heights using a scaled bar chart.

As you can see, it’s pretty misleading, and as Iggy Azalea pointed out, kind of mean. Now, whenever I try to use a scaled bar chart… this is all I can think of. This was a big concern of mine going into the process of making this visual. I still opted to use a chart with a 0%-30% scale, because if I made it go to 100%, the items represented would have been miniscule and I think it would’ve been harder to make sense of– though I still think this current chart could raise some concerns about misrepresentation.

Still, I think this is an interesting and informative visualization. I certainly think using the actual item of trash for the bar is creative and engaging, and I think it does a good job to show, generally, what is taking up the most room in our landfills.

Another part I like is that it still follows typical conventions of a data visual that makes them easy to read– it’s still just a bar chart– but the real-life and 3-D aspects of it add just enough dimension to be compelling.

Bringing our visuals into the real world can be a challenge for people creating data visualizations– I know it was for me. But, sometimes that’s what pushes us to think outside the box… and that could be where some of our greatest ideas come from.