Gov 2.0 Summit: Clay Johnson

September 9, 2009 – 2:55 am

The second Clay, hairier and less well-dressed. Head of Sunlight Labs, part of the Sunlight Foundation. I was at his house on Monday night for a turkey cook-off between him and Chris DiBona of Google. Clay won, by the simple expedient of deep-frying his birds. Clay’s a good Southerner.

Apps for America, contest around This is their second contest. (I apologise for not linking here, I’m blogging on the run at the conf–Google will find you the projects I mention here)

Rule: any entry needs to be open source. OSI-approved license, just needs to be open source. Second rule: any feed from, even itself.

Prizes: $10k first prize, $5k second, $2500 third. And a $2500 visualization special category, and ten honourable mentions at $500 apiece.

47 open source projects were created, most still being maintained.

Local Spending: HTML5 geolocation to tell you what spending from USA is happening in the user’s area. Did the same with money.

Budget: takes the federal government and makes it a bit more comprehensible. “That’s enough to buy 4M mid-size cars at sticker price”. Gives the top-level line-items for the depts, drill down, graphs and human-comprehensible info.

FBI Fugitive Concentration

Fly On : Data from FAA, probability analysis to tell you how likely your flight is to be delayed, even before it’s announced that it’s delayed.

QuakeSpotter: desktop app showing you all the earthquakes happened over last few days. Can click and search Twitter around the earthquake to see people talking about it. Timeline: charts data from over time. So can play unemployment data over time, mash up data sets, drill into specific states.

Quake Alert: Facebook alerts when your friends have been in an earthquake.


GovPulse came in second. Completely visualizes and makes the Federal Register readable. Subscribe to different agencies in RSS. Geolocates.

This We Know: takes all the federal data for a locatable place and tells you about the neighbourhood.

Data Masher (winner): take two datasets from and mash them together, compare, graph.

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