Introduction to Digital Humanities - HUM 346 / AMS 348 / LAS 385 / COM 336

T/Th: 1:30 - 2:50 PM

This course will introduce students to debates and approaches in the Digital Humanities from a global perspective. We will consider the foundations of DH while also discussing concerns involving access, maintenance, and care for projects over time in regions with physical restraints such as connectivity restrictions. On seminar days, we will work through theoretical concerns and explore the possibilities and limits of existing tools. On studio days, we work in small teams to gather data from primary sources in RBSC, which we will then use with software and platforms to build skills in computational analysis, data collection, and DH research.

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What insights, avenues for research, or new tools might we discover by experimenting with computational methods on material from library collections? In partnership with Princeton University Library, the CDH invites research software engineers and programmers for a one-day hackathon on the Latin America Ephemera collection, which includes around 12.2k published items. The library will provide dirty OCR text for the content, in addition to IIIF metadata and images that are already available. Exploration possibilities include named entity recognition, classification, automated image processing, machine learning, topic modeling, and data visualization/sonification/physicalization. High-performance computing resources will be available for use by participants, with assistance from Research Computing. Light breakfast, lunch, and afternoon refreshments will be provided.

RSVP is required for this event. Interested parties should contact CDH developer Nick Budak (nbudak@princeton.edu) for more information.

Information may want to be free but institutional researchers, including those at universities, operate under certain constraints having to do with privacy, copyright, and intellectual property. Who owns data generated under sponsored research? Under what conditions can it be shared? What are best practices for managing sensitive data, particularly that involving living people? How does Princeton manage data security? When should data not be open and how does this apply to decisions about licensing and publishing datasets? How does one obtain and work with existing datasets that are themselves under strictures including, but not limited to, copyright? Reprensentatives from Princeton’s Office of General Counsel will join us to consider questions related to these concerns and offer practical advice for managing legal aspects of data.