Database Reference
In-Depth Information
I'd say if you want to get a sense of what people in the nonprofit sector are
talking about, then NTEN, the Nonprofit Technology Network, is a good place
to learn how nonprofits can use technology. In general, the
Stanford Social
Innovation Review
is fantastic because they're looking at the ways and problems
social innovation is wrestling with.
Of course, I'd also recommend that people read up on other groups who
have similar missions to DataKind—Data Science for Social Good out of the
University of Chicago, the Data Guild, and Bayes Impact. They're all trying
to make the world better through data science and have unique perspectives.
I love the work they're doing.
Gutierrez:
What does a typical workday for you look like?
Porway:
Most people think that I do data science all day, but the first thing
I learned about becoming a founder/CEO is that I hardly touch data at all any-
more! My job is primarily governing the company, making sure we're funded,
building strategic partnerships, and plotting out DataKind's course over the
next one, five, ten years and beyond.
Of course, a big aspect of that is surveying the landscape and making sure our
work aligns. I spend a lot of time meeting with nonprofits, foundations, and
governments to understand their data problems so we can deploy programs
to address their issues. I also spend a fair amount of time at data science con-
ferences understanding what techniques could best be applied to social sector
problems. And, of course, I'm also scanning for other data science do-gooders
to join the movement.
I often check in with our chapters and project teams to understand how our
processes are working and what could be improved. DataKind serves as the
connector and translator for other data scientists and social organizations, so
I see my job as making sure we're delivering what everyone wants to get out
of this—that they're having their promise fulfilled.
Gutierrez:
What project have you worked on that you think showcases the
great work that DataKind does?
Porway:
We did an early, high-impact project with the Grameen Foundation's
Community Knowledge Program. The basic idea is that subsistence farmers
in Africa have a tough job. You're a farmer in Africa. You are poor and there-
fore you do not have a lot of access to information. You don't know what the
weather's going to be like the next day or if a storm is coming.You don't know
the crop prices in the town next door. So the Grameen Foundation's premise
was that if they got volunteers with cellphones in the community to go to
farmers and ask them what information they wanted, look it up, and give it to
them, the farmers could make better decisions. DataKind put together a team
of volunteer data scientists to work with the Grameen Foundation to find out
if the program was effective by using their data.
