face your fear: xenographphobia

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In the states (and other countries worldwide), we are preparing to start the holiday season. First up for us is Halloween in October. It’s the one time of the year when I lean into my fears, subjecting myself to terrifying haunted houses and watching horror films on repeat. Therefore, it also seems fitting to face a chart-related fear—xenographphobia.

Xenographphobia is the fear of an unfamiliar graph. This typically refers to more novel—or downright strange—graphs and crossbreeds of charts. Horizon charts, swing graphs, vector charts, and tree map bar charts all classify (see below for a couple of examples).

Visuals from Maarten Lambrechts’ Xeno.Graphics.com

Visuals from Maarten Lambrechts’ Xeno.Graphics.com

I recall the first time I came across a horizon chart. Two thoughts came to mind: 1) this looks cool; and 2) I don’t have the energy to figure this out. Fast forward to now. I’ve learned how to read horizon charts, and I’ve even identified a few good use cases for them. This illustrates both the problem and the potential of xenographs. Let’s explore the potentially problematic side first.

Novel approaches to visualizing data can intimidate audiences. They introduce a learning curve because a never-before-seen graph typically requires time and energy to decipher. This obstacle could be enough to dissuade audiences from consuming the data altogether. Even if your audience does invest their time, the resulting conversation is often about reading the visual instead of the primary takeaway. This seems counterintuitive, especially in the explanatory analytics space, but it doesn't mean we should denounce everything novel.

At one point in time, a bar chart was a xenograph. Without learning and embracing something new, we might not have the standard charts that we rely on today. To move the data visualization field further, we should be open to experimenting with unique views. What seems scary today, may have the potential to be the next best visual in the future. 

That said, as we experiment and innovate, let’s be mindful of why we are doing this. It’s important to find a balance between being open-minded with new approaches and creating visuals that best serve our data and message. One way to do this is through thoughtful contemplation—take a step back and consider both the benefits and consequences of the visuals we create.

With real understanding, we can be reasonable about when a novel graph is appropriate or when something familiar is a better choice. We can also teach others how to interpret alternate views of our data rather than just putting something into the world and hoping for the best. Xenographs aren’t things to be afraid of, yet xenographphobia is common. This month we ask you to face your visual fears and create an unfamiliar chart—whether its something you’ve never seen before or something you’ve never had the chance to create.

Bring on the scary attractions, movies and graphs this month—we’re ready!

the challenge

Identify a chart that brings you pause or consider a dataset where your regular repository of graphs doesn't seem to work. Embrace the discomfort and visualize a different way. We recognize that everyone's idea of an unfamiliar chart will look a bit different. That's okay! The goal is to explore something new for you and think about when a novel approach would be worth exploring compared to what you might typically do. Better yet, consider how you will help your audience move beyond their hesitancy and embrace your xenograph.

For inspiration, check out the xeno.graphics website (created and maintained by Maarten Lambrechts). If you need help finding data, check out this list of publicly available data sources. Share your creation in the SWD community by October 31st at 4PM PST (Halloween!). If there is any specific feedback or input that you would find helpful, include that detail in your commentary. 

We are excited for you to embrace the strange and scary this month!

related resources

Here are some additional examples for inspiration. There’s a ton of great work out there—much more than we’ve called out specifically here—this is a starting point, but certainly not a comprehensive list (if there are other great examples you’d like to share, feel free to include links in your submission commentary).