UVA Public Interest
Data Lab

About the Lab

This is a 10-week hands-on lab; we’ll be learning how to use data and data science to answer important and public-minded questions. You don’t need to be an expert in statistics or R or coding coming in - though the project will provide plenty of opportunities to become more adept. Good data-oriented work comes from the collaboration of people with diverse talents and perspectives and developing expertise. We need individuals who can or want to learn how to wrangle and analyze data in R and to visualize data effectively; but we also need people who can help teams work better and keep projects moving, who can ask probing questions and think creatively, who can dig into a new substantive area and synthesize information, who can communicate about results and write effectively. That doesn’t mean everyone won’t be responsible for learning about and contributing to each step of the project, but you may find that at some points you are more of a learner and at other points you are more of a leader.

Throughout the project you’ll be working in smaller teams (of about 3) to complete assigned tasks for the fuller project. We’ll need to quickly develop a better understanding of the foster care system and processes. We’ll have to figure out what data we have, consider its provenance, and evaluate it’s limitations. In fact, we’re still waiting on the data from the Virginia DSS, so this is truly a case where we’ll be encountering the data for the first time together; it’s likely to be messy, possibly less than we’ve asked for, there are no “right answers,” and I don’t have any pre-determined outcome. In other words, it will be very representative of data science work in real life!

Expectations and Evaluation

Grades will depend on your contribution to the project, which will be assessed by:

• Lab/class contributions and participation (20%) - Since we are working as a team and completing a real project for a real client, attending class fully engaged and prepared will help you to get the most out of the experience, and to give the most to the effort. Come prepared, chime in with ideas, ask questions, help develop solutions, complete work you’ve been assigned. Once teams have been formed, I expect teams to meet each week between class to work together. Lab members will have a chance to evaluate the contributions of one another as well.
• Team assignments (30%) - We’ll divide up work among teams - whether that’s reviewing different parts of the literature, exploring different parts of the data set, analyzing different subsets of questions - and each team will have a chance to report on their progress. Based on that progress, we’ll determine the next steps that should be completed for the following class. While I have an outline in my head of where I hope we’ll be from week to week, applied research and data analysis often does not conform to planned timelines. In part, that’s what makes it exciting, but I know that can be uncomfortable for some, so I want to be upfront that the project will require some flexibility on all our parts.
• Weekly updates (20%) - Everyone will submit a weekly update briefly describing your individual contribution to the team’s progress for the week.
• Final report (30%) - Each group will be responsible for part of the final report, including some piece of the pre-analysis sections (overview, literature, and description of the data), as well as the communication of the processes and results around the research questions on which you took the lead.