Link round-up for July 2020

The Journal of Biogeography has an article from its editors about how to make a great figure. heir take-home messages:

1. Create introductory figures to set up your problem.
2. Create figures at final size.
3. Use vector graphics. (Emphatic agreement here!)
4. Make figure captions understandable on their own.
5. Don’t overuse colour.
6. Use maps to show geography.
7. Include node support in phylogenies.
   

There are no figures in this article (!), although it links out to several other articles for figures.

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This is a good blog post on choosing colours. In particular, it considers the problem where you are give a style guide and told, “You must use these particular colours, because that’s our brand.”

At one organization I worked for, before I created a data visualization style guide, the guidance for charts was to “use brand green.” This meant that all charts were green, no matter what data they represented. It was hard for readers to tell the difference between graphs in a report, because they all looked the same. Green. To show the complexity of the data, we needed more colors.

Your institution’s colours were probably picked by how they’d look on a t-shirt and not how visible they will look on a graph.

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This is a good post on how to make graphs more understandable. Excerpt (which was highlighted as “Important!” in the original):

If you’re going to show people a cumulative graph, it’s important that you tell them it’s a cumulative graph.

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Defaults are risky. At least this article on typefaces for research manuscripts suggests so. Because a lot of people do not like Calibri.

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A history of emojis from 1862 (!) to today. Some fun tidbits in there, like the role of AOL (remember them?) has by introducing buddy icons in the messenger app.

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How did Georgia hide a huge increase in COVID-19 cases?

Map on the left is 2 July 2020. Map on the right is 17 July 2020. Check the legend carefully.

That said,  Jonathan Schwabish offers a counterpoint here. Excerpt:

I believe that the issue of the changing legend is likely due to how the data visualization tool (whatever it is) automatically sets the map bins based on the data.

This is a Hanlon’s razor argument. I used to invoke Hanlon’s razor much more often, but living through 2020 has all but blunted that razor for me. I’ve seen far more heartlessness than cluelessness this year.

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This post on the billboard poster format proposed by Mike Morrison is from last September. Excerpt:

I had the most “traffic” at my poster than ever, especially from a more generalized audience. In the past, most of the people who have visited my posters were specialists who picked out keywords from my poster title and were working with the same organism. With the main takeaway of the poster front and center, I also met people who were interested in my methods and intermediate findings and the applications/implications for broader research.

Sorry I missed it then!