If you have been alive for longer than five minutes, you've heard "big data" and "city" used in a sentence. But talking about big-city data is easy. Doingit is tougher.
Big data (and sometimes just plain old data) was the subject of a panel discussion at Monday's CityLab eventat the Conrad Hotel in lower Manhattan. Enthusiasm for using city data to create just about any application one can imagine has been high in recent years, but the panelists were frank in admitting that we're still several hurdles away from having the data-driven cities many have been envisioning.
Here's a look at four challenges, as outlined by Monday's panel.
1. Data's Catch-22
Let's start with the money. As Geoff Mulgan, the panel's moderator and chief executive of the independent charity Nesta, said at the start of the session, there are "grand claims" being made about how much money can be earned from public data. But there's not much evidence to support those claims, and when it comes to investing government money, there's a lot of pressure on officials to be able to confirm that there will be a return on their investment.
Emer Coleman, an architect with the London Datastore, who previously held a position at the Greater London Authority, called this a Catch-22. "You don't want to spend money on data if you're not guaranteed to make money from it," but no one will know if money will be made on data if they don't spend on it first.
Oh, the conundrums of our digital age.