Pointing to a need for better data presentation

1 minute read

Knowable magazine, which is an outlet of the Annual Reviews series of journals, has a great current article by Betsy Mason on the need to improve how scientists present their data: “Why scientists need to be better at data visualization”.

The problem of meaningful data visualization is approaching critical proportions in the study of human population genomics. Common means of portraying variation among genomes simply typically be interpreted by anyone without deep experience in examining them.

Mason’s article doesn’t touch upon these more difficult types of visualization, but it provides some solid context on the bigger picture of misleading graphs and color schemes across the sciences. I endorse this point about tools: Scientists won’t spend time learning good visualization methods themselves, but they have to use tools.

One way to combat the power of precedent is by incorporating better design principles into the tools scientists use to plot their data (such as the software tools that have already switched from the rainbow default to more perceptually even palettes). Most scientists aren’t going to learn better visualization practices, O’Donoghue says, “but they’re going to use tools. And if those tools have better principles in them, then just by default they will [apply those].”
Scientific publishers could also help, he says. “I think the journals can play a role by setting standards.” Early-career scientists take their cues from more experienced colleagues and from published papers. Some journals, including PLoS Biology, ELife and Nature Biomedical Engineering have already responded to Weissgerber’s 2015 work on bar graphs. “In the time since the paper was published, a number of journals have changed their policies to ban or discourage the use of bar graphs for continuous data, particularly for small data sets,” she says.

Even in paleoanthropology, where beautiful physical objects like fossils and stone tools are an important part of our work, we could do much better than most current practice in finding ways to make information comprehensible to readers.