// Image via Eric Fisher
Just before the American Sociological Association's annual meeting in San Francisco, we are holding a datathon to examine contemporary urban issues - especially around housing - with municipal data from cities including San Francisco, New York, Seattle, Boston, Austin, and Chicago.
Our title implies an interest in “big cities” but honestly, we’re more interested in real estate and housing data. Because a majority of the population lives in cities, cities will likely be important focal points in many of the projects that come out of the datathon. We’re hoping some teams focus on rural areas, too. Questions that we’ve considered include:
These are just some questions we’ve tossed around among ourselves. We’re sure our participants will come up with other great questions that use real estate and/or housing data.
Social scientists, data scientists, computer scientists, municipal staffers, start-up employees, grad students, and data hackers of all stripes. Quantitative + qualitative types are welcome.
People with experience doing research design, data management, statistical research, textual analysis and/or computational research are strongly encouraged to apply.
Once you are accepted, expect to work with 2-4 other people from different disciplines on a common problem related to contemporary urban issues. No technical experience needed -- just come and be willing to contribute!
A datathon is an intense 24-hour workshop that asks researchers to do their best to turn information into knowledge. It’s a format modeled after hackathons. The difference is that datathons use research questions and datasets to advance knowledge, not to launch apps.
At a datathon, participants work in teams to frame a research question, create and implement a research design, mobilize data resources and present their findings in front of a panel of judges.
Datathons allow social scientists to test new research ideas and meet potential collaborators in a working environment without requiring a great deal of commitment. Ideally, a datathon is an intellectual testing pit full of the data and constructive criticism it might take months to sort out otherwise.
Researchers are welcome to continue working on their projects after the datathon, but the goal is to have a complete or nearly complete document, image, or other deliverable (podcast? video? dataset? manifesto?) that is ready for distribution.
|13:00-13:30||Welcome, intros, review of the rules|
|13:30-14:00||Intro to datasets|
|14:30-15:00||Teams convene, transfer data, troubleshoot|
|Overnight||Up all night to get done|
|9:00-9:30||Breakfast at the D-Lab|
|9:30-12:59||Final work session|
|18:30-20:30||Judging at Hilton Union Square (SF), Fourth Floor, Room 3-4.|
|Afterparty||Up all night to have fun|