ScraperWiki and Columbia's Tow Center of Journalism - Data Camp NY

From the event organizers:

Why we need you: 

There are mountains of documents and websites out there that contain essential data about New York, but someone needs to liberate and analyze it to keep businesses and government accountable. ScraperWiki, together with the Tow Center at Columbia University School of Journalism and the Knight Foundation, are doing just that. We need journalists, students, computer scientists, programmers, statisticians and public officials to dig up the data! 
All you need is enthusiasm and a laptop – we supply the food, drink and wifi. Entry is free but space is limited. We’ve got something for everyone, so check out the three streams below, and reserve a ticket before they go. 
 

Pick a stream: 
 

Stream A: Journalism Data Derby 
Use data to uncover facts and drive your story home. Work in teams to identify stories, create hypotheses, and then gather, clean, analyse and visualise the data you need. The most innovative approaches and original ideas will win prizes. This stream is perfect for journalists with or without programming experience, or anyone who wants to dive deep into the production of a data story. 
 

Stream B: Liberate the Data 
We want to open up more data, and you’re the people to do it! This stream is the place for experienced Python, PHP or Ruby coders . Come pick up some high-level scraping skills and then get in the driver’s seat by liberating data for the Data Derby.  We’ll have a list of inaccessible datasets on hand that we need your help to access. And, of course, the most productive liberators will be recognized with prizes! 
 

Stream C: Learn to Scrape 
If you already have some basic Python or Ruby skills, but want to know more about using ScraperWiki to get at more of the data you want, this is the stream for you. We’ll be holding two tutorial sessions: one in Python on Friday morning, and one in Ruby on Friday afternoon. 
 

By the end of Friday you’ll have all the knowledge you need to come back on Saturday and join a race team in Stream A or liberate some data in Stream B.