"Graphical displays should … induce the viewer to think about substance rather than about methodology, graphic design, the technology of graphic production, or something else"
— Edward Tufte, The Visual Display of Quantitative Information
I'm using one of my favorite data sets today to explore a particular challenge: How do you clearly illustrate meaning in data that don't have intrinsic meaning? Put another way, how do you explain the methodology behind data without distracting from what the data have to say?
The data in this case come from an index — Freedom House's annual Freedom in the World index, which scores every country in the world based on civil liberties and political rights. It's a very popular and useful tool for foreign policy writers and researchers who want to compare different governments to each other or look at governance trends over time.
Like any scoring system, though, it uses a manufactured scale to rank qualities that are not easily quantifiable. In order to understand what the scores say about freedom, first you have to understand how the scores are created.
I've seen (and tried) several different approaches to graphing Freedom House scores, and every approach has pros and cons. Trend lines are most common for charting scores over time, although the Washington Post recently opted for columns to show scores for Iraq and Afghanistan. One drawback is that we're used to associating upward-sloping trend lines with positive changes, and in Freedom House's index higher scores actually mean less freedom. If you keep an ascending scale on the y axis, it might take readers a moment to realize a downward dip in scores is really a good thing.
When I was in graduate school I made a lot of these:
I liked this approach because the inverted y-axis values give gains in freedom an upward-sloping line. The colored regions show clearly whether a country is classified as "Free," "Partly Free" or "Not Free" without leaving the reader to interpret the scores. If I were making this chart today, I might leave the scores off the y axis entirely since they draw attention to Freedom House's methodology when the real take-away is the trend line. But, if you're really interested in how Freedom House rated Ukraine each year, the scores are there to see.
Back to the chart at the top of the post. Like everything on this blog, it's an experiment. Instead of an up-and-down trend line (does freedom go up and down? I guess it does when you assign scores to it), I wanted to try showing different levels of freedom by color only. The red-yellow-green scheme is widely recognized and familiar — green is good, red is not good, yellow is somewhere in the middle.
It's still hard to graph Freedom House's index without some explanation of the scoring methodology. See all the notes I added to the top chart just to feel like I was being thorough? And they don't even go into all the changes Freedom House has made to its methodology over the years.
One thing I might have done differently: The green, yellow and red areas on this chart don't correspond exactly to Freedom House's "Free," "Partly Free" and "Not Free" classifications. Freedom House's "Partly Free" rating encompasses scores of 3.0 to 5.0. On my chart, 3.0 is still pretty green and the true yellow doesn't show up until 4.0. Looking at it now, I feel it might be more important to show the three broad classifications more clearly than to show a continuous and symmetrical color gradient.
Data Source: Freedom House Freedom in the World data, 1972-2012.
Chart Tools: Adobe Illustrator (top chart), Microsoft Excel and Word.
