[okfn-za] Data hackathon challenges and why questions are important

Adi Eyal adi at burgercom.co.za
Tue Mar 12 17:22:21 UTC 2013

---------- Forwarded message ----------
From: "FlowingData" <newsletter at flowingdata.com>
Date: 12 Mar 2013 6:03 PM
Subject: Data hackathon challenges and why questions are important
To: <adi at burgercom.co.za>

 Data hackathon challenges and why questions are
Mar 12, 2013 04:38 am

Jake Porway, executive director of
data hackathons and why
they require careful planning to actually

Any data scientist worth their salary will tell you that you should start
with a question, NOT the data. Unfortunately, data hackathons often lack
clear problem definitions. Most companies think that if you can just get
hackers, pizza, and data together in a room, magic will happen. This is the
same as if Habitat for Humanity gathered its volunteers around a pile of
wood and said, "Have at it!" By the end of the day you'd be left with a
half of a sunroom with 14 outlets in it.

Without subject matter experts available to articulate problems in advance,
you get results like those from the Reinvent Green Hackathon. Reinvent
Green was a city initiative in NYC aimed at having technologists improve
sustainability in New York. Winners of this hackathon included an app to
help cyclists "bikepool" together and a farmer's market inventory app.
These apps are great on their own, but they don't solve the city's
sustainability problems. They solve the participants' problems because as a
young affluent hacker, my problem isn't improving the city's recycling
programs, it's finding kale on Saturdays.

Without clear direction on what to do with the data or questions worth
answering, hackathons can end up being a bust from all angles. From the
organizer side, you end up with a hodgepodge of projects that vary a lot in
quality and purpose. From the participant side, you're left up to your own
devices and have to approach the data blind, without a clear starting
point. From the judging side, you almost always end up having to pick a
winner when there isn't a clear one, because the criteria of the contest
was fuzzy to begin with.

This also applies to hiring freelancers for visualization work. You should
have a clear goal or story to tell with your data. If you expect the hire
to analyze your data *and* produce a graphic, you better get someone with a
statistics background. Otherwise, you end up with a design-heavy piece with
little substance.

Basically, the more specific you can be about what you're looking for, the

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