For Spring and Summer 2018, the Data Library will be hosting summer analysts and data scientists to work on special projects.

Special Social Analysis Projects

Pursue special projects in social analysis with large, individual-level  datasets like IPUMS, GSS and NLSY.

Social Science students, or any student interested in applying data science and statistical techniques to social questions, can learn to work with some of the most important datasets for studying individual attitudes, behaviors and beliefs. Each project will have 1 or two team members and will answer questions chosen by the students under the guidance of Data Library staff and analysts.

Build A Tract Level Demographic Datasets

Learn the data processing techniques at the heart of data science by linking, cleaning processing and analyzing a wide range of datasets, with topics including demographics, crime, business, society, poverty and land use.

For this project, the project team will , build and analyze a tract aggregate dataset, a derived, extensible, open-ended dataset that links data from other datasets to census tracts. It will provide easy to use data for a wide variety of topics. The dataset will consist of a index of all census tracts in the US that is linked to aggregated that are derived from: The American Community Survey; Tax Assessor Parcels; Crime incidents; Business locations; Public transportation; Social service locations; Non profit locations.

Project participants will learn the basics of working with large datasets, including data wrangling, working with metadata, batch jobs in Amazon Web Services, using Docker, and geographic analysis.

Prerequisites and Application

All work on these projects will be done in either Python ( Pandas and Jupyter ) or R, with Python being strongly preferred.  Participants must have a Github account, and should have some analysis checked into the account prior to application. To apply, email with: the url to your Github account, the url to your LinkedIn page and a statement about what projects and topics you’d like to explore.