Moving America Forward

DataKind: A Justice League for Geeks

January 27, 2014
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DataKind: A Justice League for Geeks
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By day they work for the Man. But on weekends, these computer whizzes volunteer their services to analyze big data and help nonprofits foster social change.

What if a group of data scientists, computer wizards, coding geniuses and statistical savants were able to come together and combine their talents to solve some of the nation’s thorniest problems?

The result would be a kind of Justice League for geeks, an organization dedicated to assisting nonprofits by crunching the complex data they collect and using the results to help foster environmental, social and economic change.

Aspiring to fill this role of information hero is DataKind, a Brooklyn, N.Y.-based nonprofit co-founded in 2011 by Jake Porway, 31, a former data scientist at the research and development lab of The New York Times. The philosophy behind DataKind is simple: to gather together some idealistic young data scientists who want to do good, and match them up with nonprofits that need their services. Many nonprofits and social-change ventures collect mountains of data on the projects and people they’re involved with, but they lack the expertise to analyze the information and figure out how to use it to their advantage — for example, to streamline their operations or to create more effective interventions.

So DataKind holds weekend “data dives,” events at which data scientists brainstorm ways to tackle the specific needs of various nonprofits, such as the Sunlight Foundation, a group in Washington, D.C., that promotes government transparency, or DC Action for Children, a child welfare organization also based in Washington. Both of these data dives launched successful long-term pro bono projects for the scientists.

“We’re using data science and intelligent machines in the service of world problems,” says Porway, DataKind’s executive director.

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In October 2012, DataKind completed the first of its long-term projects — for DC Action — creating a series of interactive Web-based maps, a visualization tool, essentially, of microneighborhoods in D.C., designed to be used in the fight against poverty. Based on government data on childhood well-being that DC Action had collected, the data scientists were able to pinpoint areas of extreme poverty and high unemployment in Washington. They uncovered sobering facts: for instance, 1 of 3 kids in D.C. lives in a neighborhood with no grocery store.

This kind of project allows policymakers to target neighborhoods where services and amenities are most needed, says Hye Sook Chung, DC Action’s executive director. “I look at DataKind as the Craigslist or Yelp of data,” says Chung, who is continuing to work with DataKind on additional projects, and is now paying a consultant’s fee for the services. “The uniqueness of DataKind is that they connect us to data people we would never have access to.”

DataKind was born in 2011 (originally called Data Without Borders). That year, with the emergence of big data, Porway wrote a manifesto online proposing the creation of a league of data scientists. The post went viral within a week, and a congratulatory call from the White House encouraged him to move forward. Porway’s enthusiasm and energy for the project helped lure corporate sponsors like IBM and National Geographic.

He introduced his first data dive in October 2011 in New York City, as a matchmaking meet-up for data scientists and nonprofits. Since then, the meet-ups have become hugely successful, attracting scores of enthusiastic volunteers — typically 150 at a time — and a backlog of organizations seeking help. “I’m still shocked and surprised about how many people show up,” Porways says. “Computer scientists enjoy working on juicy problems.”

Weekend marathon dives have been held in Chicago, Washington and London. A new DataKind chapter was even formed recently in the United Kingdom. “We have overwhelming demand for new DataKind chapters around the world,” Porway says. “We’re growing deliberately because we want to make sure we can maintain the same high level of quality we’ve established.”

The data dives attract young techies who want to do something altruistic, but who also know that the events present opportunities to work on projects that they wouldn’t otherwise be assigned at their day jobs. The events are also networking bonanzas, and the pro bono projects can be powerful resume builders.

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In 2013, DataKind worked with the New York City Department of Parks and Recreation on a project to measure how tree pruning and preventive care can reduce hazardous tree conditions, like broken limbs or trees and branches at risk of falling that could potentially injure or even kill people. The cause and effect relationship seems commonsensical, but the data had never been quantified. The DataKind team found that simply pruning trees more often could decrease emergency cleanups by 22 percent and that “trees pruned every five years, as opposed to 10 or 15, pose less risk,” says volunteer “data ambassador” Brian d’Alessandro, who works by day as the vice president of data science at Dstillery, a New York digital media agency (which d’Alessandro jokingly refers to as the “evil side,” says Porway).

D’Alessandro recalls “massaging” reams of data, including census records, pruning data, forestry records, a tree management database and 311 requests for forestry work to figure out how to approach the hazardous tree problem.

Jackie Lu, director of geographic information systems and analytics for forestry, horticulture and natural resources at NYC Parks, says the results of the DataKind study grabbed the attention of the parks department leadership and allowed her to make “a rational argument” to her bosses that additional funding and maintenance are needed.

On the heels of these successes, DataKind has continued to choose a wide range of nonprofits with data problems for its long-term projects in 2014. One volunteer team will work with San Francisco-based Medic Mobile, a group that aims to use mobile technology to improve health in underserved communities; the DataKind project will measure the impact of an infant mortality tool. Another team will work with a St. Louis-based veterans group called the Mission Continues, helping to gather data from online surveys in order to better serve post-9/11 veterans who are transitioning to civilian life.

The possibilities for Porway and his team of data detectives are limitless, bound only by the frontiers of the information that drives social change.

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