HTRC Data Capsules Environment

Workshop

Jul 09 10:00 – 11:30 am
Virtual
Please register for link

This virtual four-workshop series will allow attendees to gain experience with tools and data from the HathiTrust Research Center (HTRC). The Research Center facilitates text and data mining uses of the HathiTrust corpus. HathiTrust is a partnership of research libraries, and it is a digital library containing 17.3 million items digitized at the partner libraries. HTRC tools and data range from off-the-shelf options to more advanced offerings for experienced scholars. 

The workshops will be held via Zoom and will include a mix of hands-on, discussion, and presentation. We will utilize breakout rooms to support hands-on activities. You will not be required to install any software to participate in the workshops. The workshops are open to faculty, graduate students, postdoctoral researchers, librarians, and other academic staff.

Librarians who attend all four workshops will be invited to join a cohort of other librarians who are teaching with and about the Research Center. This cohort has access to additional support from HTRC, further training opportunities, and a community of their peers who are interested in HTRC.

In this third of four workshops, we will introduce you to the HTRC’s capsule environment and how it can be used by intermediate and advanced researchers. An HTRC Data Capsule is a virtual machine with special security settings that allows researchers to access text data from HathiTrust, analyze it using the text and data mining methods of their choice, and then export only the results of their analysis. This session will include a hands-on activity using an HTRC Data Capsule.

Prerequisites: either the “Introduction to HTRC for Text and Data Mining” workshop, or some previous experience with HathiTrust or HTRC.

Co-sponsored by the Center for Digital Humanities and the Princeton Research Data Service

To request disability-related accommodations for this event, please contact pulcomm@princeton.edu at least 3 working days in advance.