Visualizing the Invisible: Tools for Seeing Music
Abstract: Of all the subjects “visualized” by humanist scholars, most depend on texts. In the field of music, sources may integrally involve not only text but also illumination, illustration, schematic diagrams, and religious symbols—all of which contribute elements of meaning to the surrounding text. Somewhat to the side of that, most musical scholarship involves either notated scores or sound recordings and may rely on both. Most of the challenges encountered in efforts to develop big-data and summarization projects rely on either the notation or the sound domain. Currently, no off-the-shelf methodology for visualization in these areas exists. Existing efforts can be regarded as experimental, since they continue to grow and change.
Some of the challenges in music visualization spring from the diversity and complexity of music itself. In the best instances, music visualizations portray elaborate processes of construction and realization in ways that are easily comprehensible to the viewer. Visualization methods can also reveal commonalities between pieces that otherwise seem mutually exclusive. Sounding music exists in real time and therefore requires special treatment. Both static and dynamic examples will be shown in this lecture.
Eleanor Selfridge-Field has been involved in pioneering efforts to create digital repositories and tools for the past 35 years. She has taught at Stanford University since 1992 and additionally works for the Packard Humanities Institute. She is the author of 16 books in digital musicology and 7 in historical musicology. Among the latter, she was the recipient of a book award by the Modern Language Association in 2008.
Counting, Collaborating, and Coexisting: Visualization and the Digital Humanities
Visualization is often portrayed as the fundamental transformative techne for the digital humanities. The challenge of interdisciplinary DH work is therefore often framed as how to integrate visualization into existing DH projects and use visualizations to address DH research questions. I find this angle disquieting because of how visualization forces information into "chartable" and "countable" shapes, with potentially disastrous effects. Drawing on prior critiques from DH and visualization, and prior work in the emerging field of critical data science, I argue for a more humane collaborations with visualization, and call on our interdisciplinary group to "humanize visualization" instead of just "visualizing the humanities.”
Michael Correll is a research scientist at Tableau Software. He received his PhD. in Computer Sciences from the University of Wisconsin-Madison in 2015. His research focuses on information visualization, and more specifically on ways to present statistical information to general audiences. His other interests include graphical perception, visual rhetoric, and the digital humanities.