Data science - History, philosophy, sociology

History 280S.003

Spring 2015
Day & Time: 
W 12-2P
This is a graduate reading seminar querying the intellectual,  institutional, and social bases of the rise of "data science,"  understood as a platform drawing from computer science, statistics, and  research domain questions around working with new or large sets and  streams of data. The seminar is directed to graduate students in the 
humanities and social sciences. It is open to advanced undergraduates  and to graduate students outside the humanities and social sciences with permission of the instructor. The seminar focuses on data science within the research university, though there will be space to discuss data  science in other settings (industry, public/civic uses, open source communities, etc.).

Course Books

Close to the machine: Technophilia and its discontents by Ellen Ullman Picador. ISBN: 978-1-250-00248-8 Required
Geek sublime: The beauty of code, the code of beauty by Vikram Chandra Graywolf Press. ISBN: 978-1-55597-865-9 Required
E. Gabriella Coleman by Coding freedom: The ethics and aesthetics of hacking Princeton University Press. ISBN: 978-0-691-14461-0 Required
The success of open source by Steven Weber Harvard University Press. ISBN: 978-0-674-01858-3 Required
Two bits: The cultural significance of free software by Christopher M. Kelty Duke University Press. ISBN: 978-0-8223-4264-9 Required
Privacy, big data, and the public good. by Julia Lane, Victoria Stodden, Stefan Bender, and Helen Nissenbaum, ed. Cambridge University Press. ISBN: 978-1-107-63768-9 Required
Raw data” is an oxymoron. by Lisa Gitelman, ed. MIT Press. ISBN: 978-0262518284 Required
A vast machine: Computer models, climate data, and the politics of global warming by Paul N. Edwards MIT Press. ISBN: 978-0-262-51863-5 Required
Life out of sequence: A data-driven history of bioinformatics by Hallam Stevens University of Chicago Press. ISBN: 978-0-226-08020-8 Required
Systematics as cyberscience: Computers, change, and continuity in science by Christine Hine MIT Press. ISBN: 978-0262083713 Required
Doing data science: Straight talk from the frontline by Cathy O’Neil and Rachel Schutt Sebastopol. ISBN: 978-1-449-35865-5 Required
The data revolution: Big data, open data, data infrastructures and their consequences by Rob Kitchin Thousand Oaks: Sage. ISBN: 978-1-4462-8778-4 Required