On data and progress
In my can’t-get-out-of-bed-so-let-me-read-the-news delirium a couple days ago, I was browsing Roger Cohen’s op-ed about the stalled inevitability of liberal democracy. It’s a little overly dramatic, and I don’t agree with its conflation of economic liberalism with a liberal democratic order, but his thesis once again reminded me of how tentative our democratic experiment is. It is an historical anomaly, it is messy, and if we are ever to succeed it will be through the free flow of information.
It was this belief that motivated Sean McIntyre and myself to set out 18 months ago to make data available and accessible, to everyone; it’s this belief that still motivates us today. It’s easy to get bogged down by the realities of running a company — who’s your target user? how do you make money? why not just sell rotting vegetables to rich people? — but we’re doing this because we think there are few things as meaningful and important.
Data is such a buzzword that I might have to ban it from my lexicon, and ‘big data’ and ‘data analytics’ far too often refer to applications that I couldn’t care less about. So what if some machine learning algorithm helps Coca-Cola extract that last bit of profit? Whether they do or not, the company will still be worth zillions of dollars and their executives will still earn in one year more than pretty much anyone in the world does in a lifetime:
But as we roll our eyes at the mere mention of data, it’s important to remember that this information is as crucial to our society and humanity as any other. It was data in the Kinsey Reports that unmasked and began to normalize the broad array of human sexuality, and it was data last week that shined a light on the intolerable discrimination in Chicago’s policing practices. These data give weight to experience and anecdote, and armed with this information we can begin to push back against the naysayers who would challenge our society’s progress. Data alone won’t create change, but they can provide the justification and impetus for solving some of our most intractable, and urgent, problems.
Sean and I set out to make a crowd-sourced data repository (i.e., a Wikipedia for data), and we quickly learned why one of the most common reactions to our idea was “this sounds hard.” With encyclopedic knowledge, we have an established medium for communication: written language. The language of data is far less defined, and its literacy sparse. Moreover, there were questions of how we might handle validity — we still read Wikipedia articles with a healthy skepticism, and it’s far easier to deduce that Jeremy Renner isn’t a velociraptor than it is to spot an error in a sea of numbers.
These challenges are real, but there are examples we can learn from to overcome them. The mathematical world of data may be restrictive, but people are inherently visual; coupled with our desire to explore and our innate curiosities, interactive visualizations provide an accessible point of entry. Additionally, platforms like Github give us a perfect model to handle validity: a repository restricts those who have write access, but anyone can suggest an edit or fix a bug (in fact, fundamental internet security software is based off this model). We can trust the validity of the dataset as much as we trust its owner(s), but the added transparency and support of a community can give us that much more confidence in the data’s validity.
We’ve only made it this far because of the incredible, motivating, and inspiring people who have supported us and who believe in our mission, and our path to success will be through the ideas and support of our community. You can sign up for our beta, send us your ideas, and we’re always glad to sit down over a coffee or beer (we’d probably genuflect for a free lunch). We’re motivated by how far we’ve come, excited for the future, and eager to work with all those who believe in the power of open information to move society forward.
