46 ODD: Design choices in data visualization
I have curated this collection of external video sources on design choices in data visualization.
46.1 How to spot a misleading graph
When they’re used well, graphs can help us intuitively grasp complex data. But as visual software has enabled more usage of graphs throughout all media, it has also made them easier to use in a careless or dishonest way — and as it turns out, there are plenty of ways graphs can mislead and outright manipulate. Lea Gaslowitz shares some things to look out for.
46.2 Data Visualization and Misrepresentation
This animation was produced by some of my colleagues at Brown.
46.4 Vox on Shut up about the y-axis. It shouldn’t always start at zero
Also a nice example of appropriately choosing a y-axis window (cf. @sharoz) https://t.co/wCiOeyTo6k
— Brenton Wiernik 🏳️🌈 (@bmwiernik) February 18, 2021
46.5 Nature’s Top 10 Figure Mistakes
Nature’s Research Figure Guide gives good general advice about elements of a figure, and highlights the top 10 ways figures can delay your paper. These are common figure mistakes that reviewers and editors encounter, ranging from poor color choices and missing scale bars to figures that are too small to read or inconsistent in style. Although the guide is aimed at researchers submitting to scientific journals, the tips apply broadly to any data visualization intended for an audience.