Colorbar Confusion

A press release from Purdue University describes the effect of greenhouse gas emissions on “heat stress,” using the diagram above to illustrate the difference in effect between accelerated emissions (top) and decelerated emissions (bottom). A description from the web page:

“This image illustrates heat stress in the 21st century for two greenhouse gas emissions scenarios. The top panel shows the expected intensification of the severity of extreme hot days given accelerating increases in greenhouse gas concentrations. The bottom panel shows the expected decrease in intensification associated with decelerated increases in greenhouse gas concentrations.”

(I apologize for the nearly illegible size… The Purdue website offers up the diagram in the teeny-tiny size above, or print quality, which I assumed would be excessive.)

There are a couple of things I find odd (and counterintuitive and frankly counterproductive) about the diagram…

Firstly, the color spectrum used in this false-color representation of the data feels wrong to me, since it ranges from cool blues through warm oranges and reds and thence to… The beginnings of a cool violet? Particularly since we’re talking about temperature (well, sort of) here, and most people have grown accustomed to weather maps colored by temperature. Stopping at red gives you plenty of color resolution. (And maybe next time, you can choose something other than the garish rainbow colors?)

A more egregious error permeates the diagram, however. Perhaps we can simply call this the “apples and oranges&rduo; issue: two images, side-by-side, offered up for comparison, need to share enough to allow for easy comparison. I last blogged about this in relation to an NCAR visualization of Hurricane Katrina, but the idea is simple enough: don’t ask the viewer to do unnecessary work in interpreting your imagery, because unnecessary work leads to unnecessary risk of miscommunication. In the case of the two images above, the color bars are flipped for no apparent reason, so increasing values get warmer (in hue) on the top and cooler (in hue) on the bottom. Why? Also, the scale of the two color bars changes, running from 3 to 8 on top and from –3 to 0 on the bottom. Why? Why? Why?

(Well, okay, I can acknowledge one drawback in this particular case. Since the two datasets do not overlap, coming up with a single colorbar would be a little tricky; indeed, you’d almost need to insert an intermediate model showing, say, no change in greenhouse admissions, which would presumably result in values in between. But the issue of inverting the colorbar still stands: “red on top bad, red on bottom goooood” simply leads to confusion.)

I find behavior of this sort annoying when watching a scientist presenting data in a talk, but as part of a press release, it just saddens me. My fear is that the folks in the university press offices don’t even try to fix these problems… Perhaps because they don’t care, but perhaps because they don’t even think the data should be easily understood.

Hmmm. Maybe it’s time for a Tufte-like “Graphics 101” for science types? I looked for such a thing just now, but I didn’t find anything. Anyone reading know of such a thing?

Breathing Earth

A frequent reader of this blog just pointed me to the “Breathing Earth” website, from which I took the snapshot pasted above. The site takes data about countries’ birth and death rates as well as carbon dioxide emissions and incorporates them into a single, interactive map of the world. Births and deaths show up as flashes on the world map, while the color of a country represents its carbon dioxide emissions.

What the snapshot above doesn’t show is the interactive bit of the site, which allows you to mouse over a country to learn about its particular birth and death rate as well as its carbon dioxide emissions. Plus, it features a running tally in the lower left-hand corner that shows how many people have been born, how many died, and how much carbon dioxide has been emitted since you personally opened the web page.

Overall, this strikes me as a spiffy visualization, and my initial inclination is to see more data represented—perhaps not all at the same time, since I would hate to see the pleasant design marred by overcrowding, but maybe as options. In other words, it seems like a good template. One of the challenges of presenting only a few data elements is that it suggests a causal connection between them, whereas having a more generous set of options would allow the user to explore more on her own. In terms of the content actually presented, I’m a little confused by what the color of the country really means, since the caption reads variously “country has emitted over/less than 1000 tonnes of CO2” and “is currently emitting more than 1000 tonnes of CO2.” The last statement is meaningless, since “currently” would require some rate of emission, not simply a quantity. So it seems that it could use a little more detail in the captioning.

(Then, on an utterly nitpicky note, the regular gridlines of the above image suggest a Mercator projection, but the layout of the geography looks more like the traditional Robinson projection. That annoys me, but I’m easily annoyed that way. For more on map projections, BTW, you can take a look at the “Geographer’s Craft” page or the more detailed but less complete page at USGS. For the truly anal-retentive, check out Hans Havlicek’s page for more information than most of us ever need on the topic.)

I actually took a very different approach to visualizing socio-economic data in an “art” piece I created as an interactive and for fulldome video. I dropped the map and put elements into a very abstract space, hoping to see patterns that could work on both an aesthetic and an intellectual level. Dunno if I succeeded, but I entitled it “Numerology 0.1,” if that gives any sense of how I feel about it.