"I had my own aha! moment when reading your post. As you know from some of our discussions, I am resistant to the idea that more data is "the answer." This is because I chased the holy grail of cost-benefit analysis during my World Bank days, and I came to realize that a) there are fatal conceptual flaws to the idea you can rank initiatives by the same metric, and b) such rankings don't motivate behavioral change in practice anyway. From your post below, however, I realize that you mean data in a broader sense - not just numbers but *information*. Now I can AGREE with that! And it is worth more discussion when we get a chance."
I've had a great time talking with data wonks, open government types, NGOs, communities, activists, White House staff, hospital IT directors and all kinds of other folks over the last many many months about data and the role they play as a platform for change.
But how does this work - why do data matter so much? And what kinds of data am I talking about?
Second answer first - any kind of digital data - photos, videos, stories, numbers, financial information - can play the role as platform for change. For example, think about some of the recent photos of oil covered birds from the Gulf of Mexico. They spark giving of time and money to animal and environmental groups (data encourage action). Some photos are the result of volunteer action - such as the pictures taken by GrassrootsMapping kite and camera systems.
As far as philanthropy is concerned, data MIGHT be anything - grants information, evaluation findings, videos of work happening, pictures from partner organizations, citizen provided survey responses about the state of the local community, text messages that map local crime or that tag community resources.
All of these data matter. They might be useful to lots of people for lots of reasons. If you think of data as anything that can be digitized, and realize that this is what we are sharing using communications technologies, you also quickly realize that data are why we use these technologies. I don't have any interest in what kind of email system is better than the other, I care about the news from my friends, family, and colleagues. This is why I use email. It's the data that matters (the news from my friends) not the technology (Eudora v outlook v Mail)
This recognition matters. It explains the big interest in the iPad from grandparents. They don't necessarily care about all the whiz bang features - they like that it is so easy to use that they can read and send emails to their grandkids.
I don't think data hold all the answers - this blog is named 2173 because I think we are on a constant cycle of learning what we didn't know before - which includes learning that what we thought was right is actually wrong. I don't think data are objective - what we collect, how we frame it, how we present it - every one of these is as subjective as the day is long and have, over the years, led to every kind of human suffering from eugenics to racial segregation to genocide.
And now the answer to the first question - how is it that data matter so much?
I think data are inherently subjective. And that is part of why I think sharing data is so important - as coders says "Many eyes make for shallow bugs." In other words, the more people looking at datasets the more apparent the biases of a few become. For centuries, only "experts," the powerful, and the wealthy had access to most data - whether we are talking about government data that has been locked away and hard to get, photos of abuse at prisons, the location and numbers of oil soaked birds, or health information that would be useful to patients and caregivers but was only accessible to researchers.
The whole power dynamic is shifting around data - THIS is why data can be so powerful. Read Joe Flood's incredible book, The Fires, for a recent and local (1960s, New York City) story about what can happen when "experts with data" don't listen to "experts from the streets." In a book reading I attended in Brooklyn about The Fires, Steven Berlin Johnson asked Flood if the story shouldn't be read as a warning about our faith in data. Flood answered (and I paraphrase here),
"No. The problems come when both data and decision making are centralized. I think the lesson of the book and more recent urban data experiments is we should centralize the data - by which I mean clean it up, store it, and make it mixable and readable - and decentralize the decision making."
I was reminded of this in reading about Sergey Brin's data centric approach to finding a cure for Parkinson's. In this month's cover article of WIRED about Brin's quest, Thomas Goetz writes:
“Generally the pace of medical research is glacial compared to what I’m used to in the Internet,” Brin says. “We could be looking lots of places and collecting lots of information. And if we see a pattern, that could lead somewhere.”This kind of thinking simply wasn't possible before the age of massive data. Time was the scientific method relied on a process of hypothesis - stating what you were looking for and then looking for it. Brin's proposed approach is to look first and ask questions later. The possibilities that lots of people might find lots of things - "Looking for a cure for cancer? Don't overlook this finding, which might be a cure for Parkinsons" - is exciting.
In other words, Brin is proposing to bypass centuries of scientific epistemology in favor of a more Googley kind of science. He wants to collect data first, then hypothesize, and then find the patterns that lead to answers."
And now return to philanthropy and communities. Imagine if the stakeholders in a community - be it the Bronx in the 1960s or those with Parkinson's and medical doctors and researchers - could bring their individual kinds of expertise to bear on a dataset? This is what happens with sites like Crimestopper and PatientsLikeMe. It is also what happens when people can act on their right to know, a shift marked by Freedom of Information and the #opendata movement. Read this story in Tuesday's New York Times for examples of how information access can change the behavior of the poweful vis-a-vis the poor.
The technologies to do this exist - the challenges in making this happen are about power, privacy, and organizational culture.