This year’s eyeo festival focused not on beautiful information, or on amazing new visualization libraries, or data transformation techniques, but rather, as Megan Miller put it, on failure and slow data. That’s horrible, isn’t it? It’s wrong, or at least somehow antithetical to the upward-and-onward march of progress through technology* that acknowledges everything will be out-of-date in 18 months. Of course, slow data isn’t about baud rates and failure isn’t really failure–rather, these are movements toward longer, more contemplative engagement with data and the process of processing data. As I’ve mentioned before, I think the overwhelming amount of data and its incredible growth rate means we’ll have to move away from concepts of data management toward less idealistic terminology (such as “data harnessing”) to reflect the change in how we deal with innovation, data, digital integration, and the rest of that messy tangle midwifed for us by a man whose 100th birthday just passed.
Would that Alan Turing could have seen the effect that computing machines have had upon people, most especially those people who little understand them. I think it is no longer controversial to recognize how completely out of touch the University of Virginia Board of Visitors must be to look at their university and blanch at its digital pedigree. Instead, they relied on the notion that all is in constant flux toward the next big technological shift, despite the fact that there is growing evidence among data practitioners that the shift is actually social, inward, and philosophical. Digital artists increasingly look toward 8-bit aesthetics, information visualization is hand-drawn with colored pencil or made to resemble textile patterns (or made into textiles), humanists and OpenGeo developers increasingly distance themselves from traditional GIScience, and network visualization and analysis continues to be used in reprehensible fashion by madmen who little understand the dangers of a tripartite hypergraph.
The slow growth of digital innovation at UVA has produced remarkable success and resources technological, theoretical, and personal, all of which I have looked to in trying to achieve success in digital humanities work here at Stanford. That this would be ignored, and hastily set aside in the pursuit of some kind of poorly-understood Massively Open On-line Course, or other Great University-wide Upgrade, is yet another example of university leadership mobilizing to fight the last war.
What if the upgrade cycle no longer defines digital innovation? What if certain technologies and methods are mature? It makes more sense to interpret the popularity of Massively Open On-line Courses as a sign of the stabilization of Internet-delivered content, rather than some ground-breaking innovation that would result in a Khan Academy Google Doodle a hundred years from now. If that’s the case, then institutions like the University of Virginia should be on exactly the opposite course, not trying desperately to catch the latest wave but rather promoting the slow growth of their existing, successful digital initiatives. This could be called “incrementalism” but I prefer the term “slow innovation” and it focuses not on identifying hot, new trends, but deep investment in digital commodities, by which I mean the infrastructure, expertise, and research that utilize the growing stable of mature methods, libraries, and technologies. That’s what the university should do, and the library in particular, which then affords motivated scholars the opportunity to expend their effort on sophisticated, pathbreaking work. How do I know this would work? Take a look at the incredible work coming out of the University of Virginia as a result of its sober and long-term commitment to digital innovation.
One of the great signs that universities might be moving away from an infantile fascination with hip, technological boosterism is that the justification for removing UVA’s president has been almost universally derided as hip, technological boosterism. Much of the professional and scholarly academic community that I’m exposed to has grown quite comfortable with that which Turing’s machines have wrought. As a result, they and the digital natives they teach are much less willing to treat it as magic. I’d like to imagine that there was an intuition among the staff, faculty, and student body that the upgrade path is broken, and that appeals to it should be enshrined as a particularly modern logical fallacy. But I don’t know how much of this had to do with the reaction to the mess at UVA, or how much of it had to do with neo-Jeffersonian angst, or even how those would differ. It’s my hope, though, that one of the lessons we can take from this debacle is a more mature view of digital innovation in academia.
*Like better living through nuclear energy.