Linking Big Data to Fine Analysis: Textual Methods in the Digital Humanities

Linking big data to fine analysis: the challenge of textual methods in the digital humanities. Keynote talk. Digital Humanities Forum: Return to the Material. September 13, 2013: http://idrh.ku.edu/dhforum2013 Colin Allen is a Provost Professor of Cognitive Science and History & Philosophy of Science; Director of the Cognitive Science Program at Indiana University, Bloomington.In this talk I will illustrate and explain some of the guiding principles behind our efforts with the Indiana Philosophy Ontology (InPhO) and its partner projects. Although the term “ontology” in the realm of computer science has come to mean a formal structure primarily designed around the requirements of computers, our mantra is that ontologies are for people too. In the digital humanities, especially, this means a focus on representational flexibility and human interpretation should remain at the core of what we do. Furthermore, large-scale analysis alone is insufficient for the needs of humanities scholars: They (both scholars and algorithmic analyses) need to be connected to the primary texts in ways that help support scholarly interpretation. I will illustrate these principles through the “Digging by Debating” joint project between InPhO and other partners in the U.S. and U.K., which has been funded by NEH and JISC through the Digging Into Data challenge. In this project we seek to connect a high level views of large quantities of digitized text (such as selections from the HathiTrust/Google Books collection) to close analyses of specific pages containing philosophical arguments that are of significance to the history and philosophy of science