Koen Van den Eeckhout
@vandeneeckhoutkoen.bsky.social
1.7K followers 170 following 370 posts
📊 Turning complex data into powerful visual stories! Author of 'Powerful Charts'. Ex-physicist. He/him 🏳️‍🌈
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vandeneeckhoutkoen.bsky.social
Hey all!

With a large inflow of new followers across multiple platforms, it might be a good idea to re-introduce myself.

I'm a freelance information designer from Belgium, often operating under the alias 'Baryon Design'.

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A photograph of Koen Van den Eeckhout, smiling and wearing a dark red sweater, in front of the Ghent public library.
vandeneeckhoutkoen.bsky.social
A personal favorite of mine is this overview of languages, indicating how different languages have wildly different speaking rates (syllables per second), but roughly the same information rate (bits per second):
www.economist.com/graphic-deta...

2/2
Why are some languages spoken faster than others?
New research suggests that different tongues, regardless of speed, transmit information at roughly the same rate
www.economist.com
vandeneeckhoutkoen.bsky.social
Some languages are spoken faster, but most languages have similar information rates.

When it comes to insightful data visuals, The Economist is a source of inspiration you shouldn't miss. Their 'Graphic Detail' section is a goldmine of charts:
www.economist.com/topics/graph...

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Set of density plots by the Economist, titled 'Say no more: syllable rate and information rate in selected languages'. The left side of the chart shows syllables per second for different languages, with Japanese, Spanish and Finnish near the top, and Cantonese, Vietnamese and Thai at the bottom. On the right, the information rate is shown in bits per second, with nearly every language distributed around a similar average value of roughly 40 bits per second.
vandeneeckhoutkoen.bsky.social
Currently diving into this, so expect some more in-depth explorations and examples in the upcoming weeks. Make sure to connect/follow if you want to come along for the ride 😉

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vandeneeckhoutkoen.bsky.social
➡️ Different audiences and tasks require different levels of uncertainty information. A technical user may want full probability distributions; a lay audience might only need a rough idea of the error range.

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vandeneeckhoutkoen.bsky.social
➡️ The design challenge is: we need extra visual variables to show uncertainty, but often we have already crowded the visual design (color, position, size, shape). Finding effective, intuitive encodings is crucial. Often this will be transparency, brightness, or fuzziness.

5/7
vandeneeckhoutkoen.bsky.social
➡️ There is a distinction in the origin of the uncertainty: uncertainty in the data (e.g. sampling, measurement errors) vs uncertainty created during the visualization process (e.g. what gets lost in aggregation or interpolation).

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vandeneeckhoutkoen.bsky.social
➡️ But representing uncertainty is hard, especially to non-expert audiences. Data visuals that look “precise” tend to mislead into overconfidence.

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vandeneeckhoutkoen.bsky.social
➡️ Almost every dataset (especially forecasts, measurements, sampling, surveys) has uncertainty: measurement errors, sampling variability, assumptions, missing data, etc. Ignoring this uncertainty will overstates the confidence in results.

2/7
vandeneeckhoutkoen.bsky.social
I've been thinking a lot about visualizing uncertainty in #dataviz lately. Here are some of my current thoughts:

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vandeneeckhoutkoen.bsky.social
🔑 Vector images: your new best friend. To get something out of your head and onto your page, you need the flexible editing offered by vector shapes.

In my #infographics workshops we tackle each of these one by one, to give your next design that extra 'pro' touch!

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vandeneeckhoutkoen.bsky.social
🔑 Consistency: it's all in the details - make sure your fonts, colors and illustration style are hyper consistent throughout the #infographic. Every tiny detail counts!

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vandeneeckhoutkoen.bsky.social
Why do some infographics feel very professional, while yours feels amateurish?

There are 3 essential keys you might be missing:

🔑 Sketching: never start creating an infographic without working on paper first. Sketch ideas, explore layouts, iterate!

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vandeneeckhoutkoen.bsky.social
Thanks for reading until the very end! I'm an information designer with a background in physics, and love sharing tools and techniques to create powerful charts. Feel free to follow me, or read more at baryon.be !

15/15
vandeneeckhoutkoen.bsky.social
Note: visuals taken from Elia’s ‘Adequacy and flexibility study for Belgium, 2026–2036’, which you can access at www.elia.be/en/electrici...

14/15
vandeneeckhoutkoen.bsky.social
Of course, that’s something not every #dataviz tool will allow, so that’s only for when you’re willing to make some final custom modifications for your report.

Here’s the full comparison between our original visual, and the reworked chart.

13/15
vandeneeckhoutkoen.bsky.social
Finally, a small bonus tip. If you’re tight on space, you don’t have to make your gridlines go all the way from left to right. You could consider only adding them when they’re needed. That would give you some extra whitespace to fit, for example, your title and subtitle:

12/15
vandeneeckhoutkoen.bsky.social
Some final cleanup stuff:
- align the subtitle and note, move the GW label
- add ticks to the horizontal axis as well
- optimize the annotation to the right, brackets make more sense here than arrows
- add explicit data values for 2035 to further increase precision

11/15
vandeneeckhoutkoen.bsky.social
I’ve made the colored areas a bit transparent, so you can still see the gridlines clearly. Notice how you can easily see that the total value is growing to 200 GW by 2025, and reaching 300 GW by 2030. These intermediate values were hard to read in the original visual!

10/15
vandeneeckhoutkoen.bsky.social
✅ more precision if you’re trying to estimate data values
✅ this precision boost impacts all parts of the visual: left, middle, and right

Here’s how that looks like for our visual.

9/15
vandeneeckhoutkoen.bsky.social
I’m probably just nitpicking, but that doesn’t look so great to me! In these situations, I will always prefer to switch to gridlines. Yes, they take up more space and create more ‘stuff’ in the visual, but they have two major benefits.

8/15
vandeneeckhoutkoen.bsky.social
This is a clean, strong visual thanks to the use of direct labels and some helpful annotations. The only thing I don’t like is that vertical axis sticking out like a sore thumb at the left side. However, the labels and annotations are in the way when we want to move it.

7/15
vandeneeckhoutkoen.bsky.social
However, moving the vertical axis to the right hand side is not always an option. Often, we’ll have some direct labels or annotations on that side that make it harder to fit in the axis. It would create too much of a barrier between the data and the text.

6/15
vandeneeckhoutkoen.bsky.social
We had to move the legend to the left in order to free up some space for the axis, but it actually worked out really well. Notice also how we’ve added some explicit tick lines to increase the precision of the visual.

5/15
vandeneeckhoutkoen.bsky.social
A simple compromise is to move the axis to the right hand side of the visual, where it’s much closer to the ‘action’ — the values we’re actually most interested in.

4/15
vandeneeckhoutkoen.bsky.social
If you want to know the data values near the end of the chart, in 2036 in this case, we almost have to take out a ruler to measure, but the lack of axis ticks (the little horizontal lines next to the numbers) and the distance make that hard to do.

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