Description Themes Participants Collaborating Groups Call Organizers Contact
Connect 2 Congress
Peter Kinnaird
http://connect2congress.com/

Connect 2 Congress (C2C) is a visualization system designed to allow voters, activists, and journalists to directly interact with Congressional voting data. The goals are three-fold:

1) to provide an unbiased, investigative tool;
2) to ease the discovery of unexpected patterns or outcomes; and
3) to provide a persuasive means of storytelling.

Initial evaluation provided substantial anecdotal evidence of utility. A political journalist from the Atlanta-Journal Constitution newspaper identified 8 different stories he could write after a single 1 hour session. Congressional voting records are a straightforward and clean data set which provided a nice starting point. Other projects in this space may have to address complex questions concerning data integrity, ambiguity, and intent. For example, many transparency cites center around the role of campaign contributions in politics. Should we differentiate between contributions from those in a profession (for example, doctors contributing to those who voted for or against the health care bill) and contributions from corporations (perhaps entirely owned by doctors)? Additional complexity arises with the presentation of the data. See http://goo.gl/DjcTa for example.

I'm currently working to release an updated version in advance of CHI 2011 which will incorporate additional data sources and automatically update.

Bio
I am a PhD student in Human Computer Interaction at Carnegie Mellon University. My research focuses on the development of information technology systems designed to enable novel methods of civic participation and oversight. Every day, hundreds of government agencies release vast quantities of publicly available data. These data are often prohibitively large and complex for ordinary citizens to gain meaningful insights and understanding. Currently, the public relies on experts to interpret these data into information. These interpretations are then filtered and passed on to us through commercial and government media. My research aims to turn these data into information, allowing citizens to derive their own interpretations and reducing reliance on third-parties. Prior to starting my PhD I completed a Masters in HCI at Georgia Tech, worked as a Supply Chain Consultant and completed a BS in Computer Science at Georgia Tech.

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