The Rubenstein Rare Book and Manuscript Library currently holds more than 90 years of forestry data that has not been evaluated by contemporary researchers. The collection, largely focused on Duke Forest, includes historical data encompassing every measurement available to researchers of the past including but not limited to forest, soil, and undergrowth composition, land plats and photographs, light intensity data, as well as schedules and outcomes of forest management practices. This project seeks to create a sound work drawn from this orphaned data so we may hear the sound of the forest. This work is “aural” storytelling, as it seeks to describe a narrative about renewal by listening to the data of the trees. Specifically, we will be collecting data in the archives and formatting it for use with an audio synthesis program called SuperCollider. Using this program, we will create algorithmic audio compositions, meaning, we will write code that will manipulate the data for sound output according to the patterns we find through our research. Our end goal is to have an audio story of the forest that uses similar patterns and structures found within the forest itself.

Skills undergrad:

Music composition is certainly a huge asset. Coding experience is also a plus, however, a healthy curiosity is adequate as we will be learning SuperCollider together through experimentation. Proficiency and/or interest in archival data collection.