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Wednesday, August 23, 2017

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PHILANTHROPY 2173 - What I meant when I said "Data are new platform for change"
Lucy Bernholz

June, 2011

Four examples of what I meant when I said "data are new platform for change."

1. Safecast - a website populated with volunteer, crowdsourced data on radiation in Japan alongside data from official sources and experts. Started by a concered advertising executive in Denmark, this well-designed website is one of the most up-to-date, most referenced sources. As its founder, Marcelino Alvarez, says in this radio interview on The World:

“My background is actually not in physics or nuclear physics or science or radiation data, it’s actually in advertising,” Alvarez said. “So building websites, and doing product development.”
So he built a useful, well-designed site to which those with data and those looking for data could come.

2) The nascent #DataWithoutBorders (DataCorps) effort. Launched by a data scientist with the New York Times, this nascent idea is to match data visualization and analysis experts with nonprofit organizations to help them unlock what they know. The organizers explained it this way in the Guardian UK:
"The data world is a new and thorny place right now and we find that many groups don't even know what they don't know. We feel DWB has the potential to help organizations at all levels of competency, from NGOs with project-specific goals to non-profits who need someone to show them how to use data in ways they hadn't yet imagine."
I couldn't be more excited about DWB as it makes real an idea I shared at #PDF11 for "data circuit riders" - the 21st century equivalent of the do-gooder techies who helped put nonprofits online in the 1990s. DWB brings this kind of expertise together with organizations at the core of civil society to help unleash information we already have, to answer questions we're already asking, so we can all work together better. Who knows? Maybe we'll find answers we otherwise never would have known existed?

3) Data mashups that take government data and add to it the experiences of real people. Here's one - Don'tEat.At - use FourSquare to checkin to a restaurant and this App will ping you with health inspection info from the city database - might just keep you from getting sick. GovLoop has a nice story on how it came to be. Gives me hope for a request I posted recently on Twitter - can someone figure out a way to pull together hashtags from different conferences that are happening simultaneously and then play the role of "conference curator" - looping together discussions from the Millenial Donors Summit with new tools being launched at the Civic Media Summit (for example)? Literal network weaving, in real time?

4) Catching James "Whitey" Bulger by putting out an ad aimed at women who might have seen his girlfriend. Say what you want about the FBI and their 16 year manhunt - one hour after they aired an ad aimed at women the FBI got a tip that led to the Most Wanted Man on their list. What does this have to do with data? It's all about asking and listening - in this case, asking the same question "Have you seen this man?" of a previously unasked constituency - older women. A great example when you think about who knows what and where the expertise we need might be.

A few things to note about these data for change efforts:
  1. Data are anything that can be digitized - not just numbers, but ideas, stories, observations, questions, street smarts
  2. These mashups "listen" to people - pulling personal geiger counter data into a platform with data from the national sources on radiation.
  3. Data and stories - together - can make change.
  4. Sense making of data takes lots of skills - from data visualization to the wisdom of the person who lives in a neighborhood and knows who lives next door, which buses run on schedule, which stores carry fresh fruit, and who's had their "face done."
Note: none of the above are about complicated sets of numbers. Yes, numbers are data. And we need better quantitative data on lots of things. But data are much more than numbers. Think about Facebook. Everything on Facebook is data. And there's data on everything on Facebook.

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