April 5th, 2011 | Published in Uncategorized
This post is highly overdue, and I am constantly being reminded of why I need to write it. In this month’s Atlantic Issue James Fallows wrote a great article exploring the pluses and minuses of new media. He referenced arguments made by the great journalists, such as Ted Koppel, about the decline in objective & in-depth coverage, and discussed the new models of journalism presented by Fox News, the Colbert Report and Gawker. His reference to the perils of “giving the audience what they want, not what they need” stuck in my mind and reminded me again of the role of data visualization in this space.
Rewinding a bit, my South By South West talk this year was a part of a panel focusing on Geotemporal visualization. My co-presenters did a fantastic job offering an overview of geotemporal visualization methods, the role of trust and aesthetics, and alternate cognitive models of understanding events and histories. My original intent was to offer an overview of traditional and new media coverage of an important historical event – the Egypt revolution through the geo-temporal visualization lens. As I prepared my presentation however, the focus changed drastically.
I spent countless hours following the reporting on the Egypt revolution in an attempt to survey the type of coverage I saw. What I saw clustered (almost) neatly into the following spaces:
- Textual Lists – lists of key events that happened during the revolution. The granularity changed from report to report: Some used days while others went for minutes. Regardless, the start and end points were about the same – the first protest to Mubarak’s departure.
- Linear timelines – Some venues layered the textual timelines onto actual traditional similie-like timelines.
- Points on a map – Maps become prevelant in the larger news outlets when media such as photos and vidoes was overlayed on top of a map of egypt.
The more I read the various coverage, the less and less connected I felt to the revolution. I saw a tremendous amount of repetition, primarily focusing on the facts. What I didn’t see fell into several categories as well:
- Context – I can tell you that political corruption and nepotism were some of the reasons for the revolution, but I couldn’t cite an example. I also couldn’t tell you the history of nepotism in the Egyptian government even though I think it might be an important one. I’d be hardpressed to find any american that could, regardless of how devoted they were to paying attention to the revolution unfold.
- Personal Connection – I saw numbers, ranging from attendee counts, to time spent protesting at various locations to number of tweets at varying protest sites. What I rarely saw were personal accounts that amplified the narrative; that turned those facts into something tangible for me. What I wanted, was to know what the Egyptians felt, through their eyes.
- Breadth - When I saw the hash tag #egypt overlayed on top of a world map on TrendMap, I saw exactly what I expected. Egypt talked an awful lot about Egypt. By comparison, Egypt did not spend any time talking about Justin Beiber, but that was expected given that they were having a revolution. I couldn’t help and wonder what value are we deriving from this increased use of “point-on-a-map” with trivial data.
In years to come, as historians dissect this new age of revolution, the Egypt revolution will become a single point on a complex timeline. This timeline will contain histories that led up to this revolution, and histories that have yet to be formed. While it might take time to form the latter, the former is within our reach. I always viewed the role of data visualization to be more than just a visual mapping of data. We may want to believe that we don’t editorialize the data we portray, but we do so more than we care to admit. As the infographic style becomes more prevelant, we pay more attention to what we produce: we chose our layouts, we chose our fonts, we chose our default views and our filters because the space we are in is growing and we are learning from each other while competing for viewers. Not all the visualization tools we make are in their core for analytical purposes. Visualization can and is being used for infotainment and delivery of a narrative that we form in one way or another.
This turns us into what I like to call “reflective journalists”. While we strive to report the data as accuratly as we can, we also chose the data and the visual mapping; our choices thus have consequences. Our readers see the world through our eyes and we have some responsability towards them as a result.This proper-informing of our users leads us to a question that I hope we discuss more in the visualization community: the data. Arguing that the right data isn’t always there is a dangerous venture given the twittersphere, our sophisticated devices, etc.. However, is that data enough?
Many discussed the goal of social media in propelling the revolution, so I won’t discuss it here, but what was left out? What about the regions that do not have the type of connectivity that Cairo & Alexandria did? What about a huge and significant portion of the population that does not use cell phones to communicate in the way that young technologists (such as myself) do? What about the important tweets that got lost in the array of twitter-flatland because the flow was simply too much for any one human to parse? What about the back-room deals and negotiations that took place in physical space that weren’t being and won’t be digitized? While the social media data is a valuable piece of our reporting, we mustn’t forget these other sources of information.
The type of data I am talking about is hard to come by: it requires dilligent work, possibly beyond the realms of scraping. It might require finding the right people, listening instead of hearing, and understanding beyond gathering. It might require a bit more journalism, but it would do the story we’re trying to tell justice. I know many will argue that this is not the job of data visualization and I am open to having that conversation any day. I love seeing data visualization grow as a medium, and I love that the line between reporting and analytical tasks is blurring as well. The question is, how do we participate and what standards do we set for ourselves for our future work as we try to transition from offering information, to fostering understanding.