SGER: Digital Access and Data Mining of a Non-traditional Collection

Cornell Univ - State: Awds Made Prior May 2010, Ithaca NY

Investigators

Abstract

This project will innovate digital access and data mining tools for specimen-based collections of animal sounds. A team of programmers will design the tools and implement them for use on the world's largest such sound collection at Cornell University's Laboratory of Ornithology. The conversion of this collection to digital storage has made specimen-based research on sounds a reality for the first time. No other facility has developed the tools required for using this non-traditional type of collection. Specific tasks will include structuring the sound database to be compatible with inter-institution searches, designing search tools that allow searches using both contextual data on the recordings and extracted measures of the sounds, incorporating GIS tools and maps into the search interface, providing "thumb-nail" images for selection of subsets of archived recordings, providing easy access to sound analysis and comparison tools, and devising a method for uploading sounds by remote recordists over the internet. These tools will permit for the first time rigorous remote use of sound collections by scientists, conservation managers, educators, and the media.