The CDH is delighted to announce our first Freshman Seminar!
Weird Data, FRS 154 will be taught in Spring 2019 by Research Director, Jean Bauer.
What is the relationship between a medieval scriptorium and the popular software versioning site Github? Who determines how many people in America are killed by police each year? How can Princeton Dining Services reduce food waste and increase its purchase of local, sustainable ingredients?
These questions are questions about data: What data exists, where it can be found, and how it can be deployed to solve questions. The data required for each question differs, but many of the methods and tools required are the same.
This seminar invites students to take a deep dive into the nature of data. From the materials that have stored data over the millennia, to how data sets embody the real world objects or concepts they describe, data is always used in affective ways that involve labor and are highly situational. Raw data is an oxymoron. All datasets are arguments, once you know how to read them. Data is socially and physically constructed and that opens it to critique and unexpected readings. Data is feminist. Data is queer. And in today’s data driven world, data is power. It is only by putting datasets in context and bringing our full experiences to bear on data creation, curation, and analysis that we can move from data to information and from there to knowledge and into wisdom.
Weird data is data that is highly relational, embedded in particular contexts, and makes unstated assumptions about the world. All data is weird, but some data is weirder than others. This class will focus on the process of reimagining the human record as data, and how datasets themselves are becoming the record of our lives in the 21st century—for better and for worse.
So come and explore the wild and wacky world of data and its place on the Princeton Campus—from Rare Books and Special Collections to the Forrestal Data Center. Learn to read datasets as a text, first with examples drawn from historical and literary datasets and then by creating your own datasets with classmates. Learn the foundational skills of data science while reflecting critically on those methods and tools through the lenses of race, class, gender, and power structures. By Deans' Date you will officially join the community of data researchers as the author of a published dataset. Data is everywhere and every when. Shape it for yourself.