experiments with sonification, transmediation, remix & glitching as new approaches to interpreting visual digital artifacts.
The ductility of artifacts when they become digital data (or are born digital) offers untapped potential for generating compelling, new historical knowledge. This is true not only for text or numbers handled at large scales as “big data,” but also for less well-studied digital materials such as visual artifacts. When images become digital data, they are pliable in new and surprising ways. We can transfer image data into sound, for instance, so that we can use our ears as well as our eyes to examine them. We can use computer algorithms to glitch images, letting the computer produce new versions that, in their randomized distortions, allow for fresh eyes on what the original artifacts represent about the past. Or we can remix images more strategically using collage tactics, shuffling their elements into new forms that help us better consider the historical content they contain. The goal is not to falsify the empirical record, but rather to use digital tactics of sonification, transmediation, glitching, and remix to notice new details, aspects, information, and meanings of the past that artifacts transmit. In these approaches, we read against the grain of the archive by actually changing the grain itself.
While much digital humanities scholarship embraces statistical, positivist approaches to the evidentiary record, particularly text and numbers, image sonification, transmediation, glitching, and remix take a different tack. They treat artifacts as representational, harnessing the capacity of computation to re-present their data in multiple ways in order to look and listen to them in various formations. Image sonification, transmediation, glitching, and remix defamiliarize visual materials in order to enable new perceptions of the original artifacts. New perceptions then enable fresh observations and analysis.
To pursue this work, I have started with what existing tools can do. More recently, I have begun to explore and build cross-disciplinary partnerships with computer scientists, artists, media studies scholars, visual studies specialists, and museum curators to create a suite of open-source applications that will allow for more effective pursuit of defamiliarization tactics.