This semester I’ve had the pleasure of taking a course on Issues in Scholarly Communication with Dr. Maria Bonn at the University of Illinois iSchool. While we’ve touched on a number of fascinating issues in this course, I’ve been particularly interested in JSTOR Labs’ Reimagining the Monograph Project.
This project was inspired by the observation that, while scholarly journal articles have been available in digital form for some time now, scholarly books are now just beginning to become available in this format. Nevertheless, the nature of long form arguments, that is, the kinds of arguments you find in books, differs in some important ways from the sorts of materials you’ll find in journal articles. Moreover, the ways that scholars and researchers engage with books are often different from the ways in which they interact with papers. In light of this, JSTOR Labs has spearheaded an effort to better understand the different ways that scholarly books are used, with an eye towards developing digital monographs that better suit these uses.
In pursuit of this project, the JSTOR Labs team created Topicgraph, a tool that allows researchers to see, at a glance, what topics are covered within a monograph. Users can also navigate directly to pages that cover the topics in which they are interested. While Topicgraph is presented as a beta level tool, it provides us with a clear example of the untapped potential of digital books.
Topicgraph uses a method called topic modeling, which is used in natural language processing. Topic modeling will examine text, and then create different topics that are discussed in that text based on the terms being used. Terms that are used in proximity to one another at a frequent rate are thought to serve as an indicator that various topics are being discussed.
Users can explore Topicgraph by using JSTOR Labs’ small collection of open access scholarly books that span a number of different disciplines, or by by uploading their own PDFs for Topicgraph to analyze.
If you would like to learn how to incorporate topic modeling or other forms of text analysis into your research, contact the Scholarly Commons or visit us in the Main Library, room 306.