- 'exciting' versus optimal representation of data
- out-of-context data
Philosophically, we want to make information exciting, truthful, and human. We think that it's possible to create eye-catching, audience-drawing displays of information that feature truthful illustrations of data.
In the second part of this blog, we'll be taking a look at the work that might be involved to generate a more compelling and informative visual picture of this particular issue.
For Comparison: Visual Representation of Data
Here, we have a striking time series trendline of data that provides a comparison of outbreaks. Looking at this trend, we can hypothesize a correlation for three important inflection points. The first is the introduction of the DPT vaccine in 1942. The second is considerable, widespread concern during the late 1970's and early 1980's that the DPT vaccine was causing infantile brain damage (evidence later mounted against this claim). The third is between 2000 and the present day, possibly related to the Wakefield-generated vaccination concerns.
Let's now look back at the original selection of a visual:
To recap, the source of the data for the visualization was the Council on Foreign Relations' tracking and collection of news media reporting on vaccine-preventable diseases. This scraping was used to generate ongoing information for monitoring versus annual summary data for reporting.
The CFR's scraping of media reporting, and the statistics generated using that scraping are inherently less rigorous than a proven methodology that an organization like the World Health Organization or the United States' Center for Disease Control. This is not to say that either organization has a perfect process, but we will assume that the CDC and WHO will generally have more complete and validated information. And to be clear, it better suited the CFR's desire to track outbreaks in a more timely fashion.
In defense of the L.A. Times, the visualization (should a reader click through to the CFR site), provides zooming into the map and filtering for certain diseases. .
It should be clear to everyone that a time-series of data here would be much more effective at communicating what happened and helping people develop hypotheses. However, it's in competition now with this admittedly striking image. The CFR presentation evokes an impression of organic infection. It's eye-catching, and clearly audience-catching. The time series trendline? Unless the audience is a maven of pure data visualization, it's hard to expect that they'd be drawn to the trendline.
In the third and final part of the case study, we'll take this rendering and try to make it as visually arresting as possible, while still maintaining the integrity of the information and the reporting. And, we'll look at how the visual can be better integrated into the written copy and overall story.
We'll be heading into difficult territory, mindful of purists' admonitions such as "no chartjunk" and "every pixel must convey information." It's going to be a difficult brief.
Michael Thompson, Adam Vigiano, Vivian Peng