“Nowhere in our history of the humanities did we come across an acute divide between the humanities and science. Both humanists and scientists search for underlying patterns, which they try to express in logical, procedural or mathematical formalizations. There is, moreover, a continuity between humanistic and scientific disciplines as regards the ‘nature’ of the patterns.”

– Rens Bod, A New History of the Humanities (2013)

Course web site with schedule, assignments, and bibliography.

This course explores today’s quickening mutation of the “liberal arts” into “data science,” a new universal mode of knowledge touching all fields. The course focuses on the join, but also split, between how the humanities and data science find meaning (scientific, epistemological, sociopolitical, and cultural) in patterns. Topics to be probed include: the history and present state of the humanities, the concept of “data science” (including the shape of today’s new programs and majors in the field), the idea and structures of “data,” the idea and infrastructures of “big data,” humanities corpora and datasets (including the social and ethical problem of “representative” datasets), narrativizing data, visualizing data, and interpreting data. The course includes but is not limited to approaches related to the digital humanities.

Assignments in the course include:

• Writing a short prospectus for a research topic and project related to the humanities and data science.
• Writing a full-scale research proposal for the project in the form of a mock grant proposal that also includes a bibliography, “miniature big-dataset” (a sample of an envisioned dataset), and early experiments in researching and analyzing the dataset. (The proposed project does not need to be fully enacted during the course.)
• Writing two research blog posts.

Course web site with schedule, assignments, and bibliography.