Convergent Evolution

As I was in my car this morning, I heard a story on the radio about an interesting population genetics study based on the Melanesian people of the Solomon Islands in the South Pacific. It turns out that some 10-15% of the children of this predominantly dark-skinned, dark-haired group of people have bright blonde hair traditionally associated with people of northern European descent. Through careful analysis, it has been concluded that the blonde gene that expresses itself in the Melanesians is unique and distinct from any of the blonde genes in Europe.  This proves that while the two traits appear very nearly the same, they are genetically unrelated and arose independently of one another. The term for that in genetics is “convergent evolution” and while it is uncommon and often unexpected, it is a real thing.

Later on this same afternoon, I was confronted with another case of convergent evolution but on a lot more personal level. As I explore the dataviz field (as the embodiment of the term “neophyte”), I realize that so many of the great epiphanies about data that I’ve experienced in my professional and academic contexts have been expressed incredibly well already by many of the giants of the field.  On the one hand, as I learn of expert after expert who already shines so brightly in this  field and listen to them expound the same concepts that I (in my very hand-wavey, inexperienced, undisciplined fashion) try to communicate to my friends, I feel like a charlatan.  But on the other hand, convergent evolution explains the potential for two equivalent and equally useful occurrences to arise independently, and I suddenly feel slightly less utterly fraudulent.

Jer ThorpI spent a good deal of time this afternoon immersing myself in the works of one Jer Thorp, Data Artist in Residence at the New York Times (and fellow Canadian), one of the visionaries who has already established himself as a groundbreaker in all almost all of the exact same fields of data visualization that I have been aching to carve out.  A key tenet of his is the need for better tools to make the ever-inflating cloud of data growing all around us sensible and useful and he has done much to serve that need.  He expresses the urgency of this exploration so well at his TED Talk in Vancouver in November 2011 (click here to watch it on YouTube).

My OpenPaths Map View

Jer has been involved in some pretty exciting projects. For example, OpenPaths is a project that allows users to exploit the historical locational data stored on their iPhones or Android devices to visualize where they (or at least their phones) were and when they were there. Said like that, it sounds fairly “Big Brother-ish.” However, if you think about how valuable that information could be to YOU, and not just to an application developer or Google or Facebook or Apple, the outcome seems less sinister and more personally useful. If YOU could better visualize that data then you could relate it back to the personal narrative of your own life, thereby enriching your ability to recall and express those moments in the future. I can’t put it any better than Jer does in his Talk:

“What we didn’t expect was how moving this experience would be. When I uploaded my data, I thought ‘big deal, I know where I live, I know where I work… what am I gonna see here?’

Well, it turns out, what I saw was that moment when I got off the plane to start my new life in New York… that restaurant where I had Thai food that first night thinking about this new experience of being in New York. The day that I met my girlfriend… right?” (@13:50 – 14:12)

The convergent aspect for me is that this is the exact same reason why I still use Foursquare and Google Latitude and Facebook Places to check in to places… so that I can bookmark moments of my life for MY OWN personal consumption and use.  In 2011, I moved from one side of the country to the other… and then back again, so I have a very sincere interest in being better able to use any of the available data regarding that journey to help me chronicle that part of my life’s history.  I understand that this opens me up to a couple very undesirable potential scenarios – I like to think of these as the “Enemy of the State/Eagle Eye” scenarios.  But the likelihood of those scenarios coming to pass seems too unlikely compared to the value of this rich source of passively-collected data.  Jer’s prototype proves to me that other people feel the same way about their personal data, which is very encouraging.

Avengers AssembledWhat else has Jer done that is awesome? Well, shamefully, the whole reason that I found Jer in the first place was that I am supposed to go to see The Avengers tonight, and FlowingData had a striking visualization of the first appearances of each Avenger (apparently, there have been over 120 Avengers introduced in the 570-some issues). This one post blew my mind – not just for the clever and beautiful visualizations, but also because it exposed me to a great open data source for comics that seems pretty sophisticated and complete! As if all of this goodness weren’t enough, Jer has shared some of his visualization tools and prototypes with the community. Incredible guy!

Theories and ideas about DataViz are much easier to explore and have a far shorter life span that Melanesians from the South Pacific, so I don’t feel as fraudulent as I did earlier this afternoon about convergently evolving so many of Jer’s conclusions.  On the contrary,  I’m actually relieved and a little self-contented to have landed so squarely on the right path and facing the right direction to pursue my interests, and to have even been pushed forward quite a number of leagues ahead of where I could get on my own.  It’s almost like I’ve made a quantum leap in my dataviz evolution… but then… that would be more like mutation and the X-Men, and tonight, it’s all about the Avengers! 😉

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