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Please join us  or in-person in Room 3.72 of the RSSS Building for a guest seminar at POLIS@ANU, from  from the University of Illinois and the  Research Center. 

 

The HathiTrust Research Center (HTRC) provides analytic access to 18.7 million volumes found in the HathiTrust Digital Library (HTDL). Roughly 10 million of the volumes in the collection are under copyright restrictions, and cannot be freely shared with scholars. In order to provide more open access to HathiTrust’s materials, the HTRC has released its Extracted Features 2.5 Dataset which contains over 3.3 trillion unigram tokens found on each of the 6.9 billion pages in the corpus. This talk provides a briefing update on the HTRC’s ongoing “Tools for Open Research and Computation with HathiTrust: Leveraging Intelligent Text Extraction” (TORCHLITE) project. Funded by the National Endowment for Humanities (NEH), TORCHLITE strives to create easy-to-use text analysis tools, dashboards and application programming interfaces (APIs) to facilitate open cultural analytics research using the uniquely valuable HTDL data. The talk will highlight motivations, challenges, and accomplishments of the TORCHLITE to date, along with its upcoming next steps that envision the creation of an international consortium of similar groups, tentatively called the “Consortium for Open Data Exchange in the Humanities (“CODEx Humanities+AI”),” which is designed to encourage the creation of novel extracted feature data to create access to otherwise closed collections.
 

J. Stephen Downie is a Professor and the Interim Executive Associate Dean and the Associate Dean for Research at the School of Information Sciences, University of Illinois.  He is also the Illinois Co-Director of the HathiTrust Research Center. Professor Downie conducts work in Digital Libraries, Digital Humanities and Music Information Retrieval. He holds degrees from the University of Western Ontario including BA (Music Theory and Composition), Master’s of Library and Information Science (MLIS), and a PhD in Library and Information Science.

 

Webinar ID: 864 7039 8684

Passcode: 758628