A key aspect that this misses is the target audience. The general public is not the target of most scientific visualizations. Instead, it's other scientists i

A key aspect that this misses is the target audience. The general public is not the target of most scientific visualizations. Instead, it's other scientists in the field. There are invariably lots of conventions and general historical trends that it's important to follow to communicate clearly. For example, in seismology high sonic velocities are always shown in blue/cool colors and low sonic velocities are always shown in red/warm colors. This is non-ideal for colorblind users and confusing for other audiences (red != high value), but it's a near-universal convention. We can use a more perceptually uniform red to blue colormap, but keeping the warm/cool convention is very important. If your audience is used to seeing a certain type data in a particular way, you'll confuse people if you don't follow that convention. Clear labels and legends are great, but people follow convention first, labels second. When the goal is clear communication, following established convention is much more important than making a "better" visualization. That's not to say that these guidelines aren't very important, just that it's vital to keep your audience's expectations in mind. > "Scientists also tend to follow convention when it comes to how they display data, which perpetuates bad practices." In my experience, scientists follow convention because it enables clear, consistent communication with other scientists in the field. Violating convention is okay, but should be done with utmost care and the knowledge that you'll need to spend more time explaining things.