Big cities, big data: Big opportunity for computational social science
Datathon | 15-16 August 2014 | UC-Berkeley D-Lab
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.
Full information on "Big cities, big data" here.
Judging is open to the public on August 16th fron 6:30 - 8:30 and will award a monetary prize.
Who should apply?
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.
APPLY HERE until 1 June 2014.
What is a datathon?
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.
Why is a datathon a good idea?
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.
What happens to the work that gets done during the datathon?
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. IPK will help identify media partners and publication outlets.
We hosted our first datathon last March, to investigate the impact of climate change on New York City. The event was sponsored in part by Johnson Research Labs and judged by NYU University Professor Dalton Conley, Research Scientist at Microsoft Research Duncan Watts, and NYC City Planner Mariam Hariri.
A summary of the objectives of the first datathon is here:
Images from Team Turnstile, one of the two award winning teams are here:
Social and Meteorological Data
With the support of Johnson Research Labs, the Institute for Public Knowledge is convening a datathon to explore how social and meteorological data can be combined to enhance social science research on climate change and cities. The datathon will run Saturday March 9th - Sunday March 10th, 2013, starting noon Saturday, with final presentations at noon Sunday
The prompt: Climate change will increasingly shape everyday lives around the world and become a focal lens for social science researchers. Large publicly available datasets full of social and meteorological data exist going back for more than a hundred years.
+ How can these datasets be brought together to meaningfully examine the impact of climate change on cities?
+ Should social scientists and/or climate scientists call for new types of data to be collected to meet the challenges of climate change research?
+ What advantages are offered by focusing on the city as a unit of analysis?
+ What technological, political, and social challenges will need to be addressed as climate change grows as a focal lens in research communities?
Data Partner: Enigma.io is a web tool to quickly and effectively navigate through, collect and distill information from big public data. It gives users direct access to a curated collection of data sources ranging from a variety of sectors, industries and indices. Analysts and researchers can search across different pieces of raw data, regardless of origin and format. They can also perform analytical and specific queries on the fly and without technical knowledge, thereby saving time and uncovering hidden relationships between data points.
Invitees: Twenty invited academics, journalists and data engineers. Three panelists/critics will respond to the presentations.