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Jake Porway is a matchmaker. He sees social change organizations working hard to make the world a better place, collecting mountains of data, but lacking skills and resources to understand and use that wealth of information to advance their mission. He sees data scientists with amazing skills and cutting- edge tools eager to use their talent to accomplish something meaningful, yet cut off from channels that would allow them to do so. He sees governments ready to make unprecedented amounts of data open and available, but disconnected from people who need it.
For Porway, it's a match waiting to happen and exactly why he founded DataKind (formerly Data Without Borders). "We're connecting nonprofits, NGOs, and other data-rich social change organizations with data scientists willing to donate their time and knowledge to solve social, environmental, and community problems," Porway explains.
He compares it to striking oil. "Data is like a bucket of crude oil. Potentially great, but only if someone knows how to refine it (data scientists) and someone else has vehicles that will run on it (the social sector)."
"My own job search was frustrating because, while I wanted to use my skills for social good, my resume only attracted attention from Wall Street or Silicon Valley. Nonprofits are so resource constrained they rarely have data scientists on staff," he says. "So I decided if I wanted a job that lets me use data to help the world, I'd just have to create it. Turns out I wasn't alone. The response to Data Without Borders has been incredible—from socially conscious new grads hungry to make an impact to people who've spent 20 years in big corporations and need to feel their life is worth more."
Porway's own day job? The New York Times R & D Lab—a group building prototypes of what news and information sharing will look like in a future defined by social media, new technologies, and nonstop data flow. He doesn't expect data experts to give up careers, salaries, and lifestyles, but he knows what makes them tick. "These people spend their spare time solving interesting problems for the love and fun of it. Yes, they have day jobs, but they also have evenings and weekends."
Porway is happy to help them fill those spare hours through weekend "DataDive" events. Unlike typical hackathons, where data scientists and developers huddle to create new software or apps, DataDive weekends also include people who will actually use the analysis and visualizations being invented.
"Social organizations come with specific problems and frontline experience with real, on-the-ground situations," he explains. "Data scientists work side by side with them as a collaborative team to find practical solutions, beginning with basics like making sure surveys are statistically valid, assessing how data is managed, and suggesting how open data sources might be used."
Events held in San Francisco, New York, Washington, D.C., and Chicago are proving the power of connecting technical savvy with strong social missions. The United Nations Global Pulse group arrived with aerial imagery of farms in Africa, some of which had used fertilizer and some of which had not. Did certain fields look greener because the fertilizer was helping, or because they were photographed in full sun versus others shot in shadow?
The New York Civil Liberties Union wanted to learn whether racial discrimination was behind police stops and frisks. By organizing and mapping a deluge of data, hot spots immediately appeared, highlighting areas with high stop-and-frisk rates that couldn't be seen in the rows of data before.
The Grameen Foundation brought data from a project that gives crucial weather and crop pricing information to African villages in tech-sparse areas. Analysis uncovered which investments in infrastructure were worthwhile and which weren't. Porway reports, "They were so impressed with the power of building tools and analyses around their data that they restructured their organization to include a data science team."
Mobilizing Health brought a basic question to the weekend and left with a completely unexpected new diagnostic tool that will allow earlier detection, diagnosis, and treatment of disease in remote areas.
Microfinance Information Exchange attended a DataDive to see whether gathering complex data they needed from a multitude of websites was feasible. The nonprofit estimated collecting and organizing the information would take their staff one year. Data science volunteers at the event completed the bulk of the task in about 24 hours.
"DataDives have been more valuable than we ever could have expected," says Porway. "Best of all, many participants have continued working together long after the weekend events. That's the world we want to engender—data scientists working permanently with social organizations."
This initial success paves the way for longer-term engagements such as month-long volunteer programs or ongoing part-time contract work. The step after that, Porway hopes, will be year-long paid fellowships creating full-time data science jobs within the social sector. Ultimately, he wants to build a globally connected network of dedicated experts who can be deployed at a moment's notice to tackle any big data science task worldwide.
"Data is so dynamic; organizations need full-time people devoted to monitoring information, looking more deeply at the numbers, and using it to plan strategies for the future," he stresses. In the short term, Data Without Borders is identifying core needs that surface across most organizations. "We'd like to build common, free, open-source tools that can help groups gain insights from their data even if they don't have a data scientist on staff."
"Often, tasks that are fairly straightforward for data experts can be transformative for groups who are trying to feed the poor, protect children, stop epidemics, and make the world a better place in hundreds of ways," he says. "If every organization had access to these skills, what kinds of questions could we all be answering?"