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Monday, February 3, 2014

Frankenstein's Creature, Vaccinations, and Data Viz: A Case Study (Part 1 of 3)

Beginning in the late 1700's and continuing through the first part of the 1800's, galvanism was an exciting topic for western society. Galvanism, named after Italian scientist Luigi Galvani, supposed that electricity was the primary animator of biological mechanisms. Galvani theorized, based on experiments in his laboratory, that if it electricity could be accurately channeled into biological organisms, an "operator" could physiologically direct an organism (alive or deceased) according to his or her whims.  

Inspired by this idea, Mary Shelley wrote her famous work Frankenstein; or the Modern Prometheus. Part science fiction, horror, tragedy, and social commentary, the story tells of Dr. Frankenstein's Creature blundering and crashing about through 19th century society as it becomes self-aware and struggles with human realities. The Creature experiences disaster and psychological torment due to its horrible dislocation from its proper context: a natural birth, a nurtured upbringing, a social life, and a final resting place in death.  

In this blog, we'll deal with a slightly less dramatic but still fundamentally important galvanization: the repurposing of a data visualization for a rhetorical news feature. 


A January 20th feature in the Los Angeles Times business section by Michael Hiltzik, titled "The Toll of the Anti-Vaccination Movement, In One Devastating Graphic" referred to a Council on Foreign Relations visualization of reported outbreaks of vaccine-preventable diseases. 

Hiltzik writes that the outbreaks shown in the visualization are "an artifact of the anti-vaccination movement." The anti-vaccination movement he refers to here is represented primarily by parents who defer or avoid their children's vaccinations due to fears of the supposed linkage between autism and vaccines.  

To be clear: this blog posting is NOT attempting to settle or even debate linking autism to vaccinations. Rather, this blog posting is illustrating the difference between repurposing of information visualizations for the purposes of advancing arguments, and developing original, in-depth data journalism.  

The data visualization originally caught our attention due to its less-than-effective use of a "bubble" chart in a point map format. The article features a still image of the visualization at a global "height" where one can see most of Europe and the Americas countries. Bubble charts make excellent imagery for various nasty things, evoking thoughts of mold or petri dishes.  But here, bubbles overlap and it is impossible to discern the geographical location of the outbreaks. This is simply solved by visiting the interactive site where we can zoom in and better discern where the outbreak occurred. However, we are then caught up in a slightly less difficult but still significant problem of comparing the relative magnitude of outbreaks. This problem stems from the well-documented perceptual limitations of bubble charts.

The data doesn't offer control groups or relative comparisons to history or proportion of overall population. Consequently, there's no baseline indicating a 'normal' level of outbreak, or expected levels of outbreak relative to the percentage of population vaccinated. Furthermore, the only longitudinal visualization of change is a slider that allows us to see five years of data - and an unclear trend.  

The source data for the visualization is available at the Council on Foreign Relations website. Although we had expected traditional sources of global disease data like those available from the World Health Organization, we were surprised to learn that the data was instead sourced from local news articles.  

Wanting to understand this more, we put in a call to the Global Health Program at the Council on Foreign Relations. The researcher with whom we spoke said that the visualization had been developed for tracking, in real time, regional and local disease outbreaks. This explained their choice of using news reports, not WHO data (published annually) as the source of data. And, to support a purpose, it sounded, much more like observation and inquiry rather than statistical analysis and conclusion. Finally, the data visualization had been launched several years before this article - and had not been commissioned by the newspaper for the sake of the article.   

Essentially, the Council on Foreign Relations data visualization appears to have been repurposed by the Los Angeles Times for the sake of advancing an argument that vaccine avoidance and vaccine-preventable disease are related. The purpose of this blog and the next two of these series is not to dwell on a possibly 'galvanized' use of a data visualization, but rather to illustrate the challenge and complexity of crafting proper data journalism. 

The next two blog entries will address some steps that we'll take to try to describe how a newspaper like the Los Angeles Times might more thoroughly and carefully depict the hypothesized linkage between vaccination and an increase in outbreaks of vaccine-preventable disease. In it we'll talk about provenance, context, statistical considerations, narrative, and design choices. We'll also write about the inherent challenges of depicting data about humans, who do not follow the same kinds of rules of physics or other natural laws that these visualizations were originally developed to depict.  

Extending outward - we'll invite this blog's audience to offer their own interpretations, suggestions on improvements, and other technical guidance.  

And most importantly - we'll assume that the readers of such a prominent newspaper as the Los Angeles Times, regardless of their level of education or familiarity with the topic or scientific techniques, can in fact be interested and learn from a careful storytelling and visual rendering of an observed phenomenon. The readers of the Times deserve that honor!

-Michael Thompson and Adam Vigiano

Note: Out of fairness and collegiality, we tried to reach Michael via e-mail and Twitter to get his perspective on his involvement, process and choices for framing this visualization under his by-line. As of this blog posting he has not responded to us. However, we also did not expect him to readily respond due to his unfamiliarity with our team.  

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