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

该项目将创新基于标本的动物声音收集的数字访问和数据挖掘工具。一个程序员团队将设计这些工具，并将其用于康奈尔大学鸟类学实验室世界上最大的声音收集。将这些收藏转换为数字存储，使基于样本的声音研究首次成为现实。没有其他设施开发出使用这种非传统类型的收集所需的工具。具体任务将包括构建声音数据库，使之与机构间的搜索相兼容；设计搜索工具，允许使用录音的上下文数据和提取的声音度量进行搜索；将地理信息系统工具和地图纳入搜索界面；为选择存档录音的子集提供“缩略图”图像；提供方便的声音分析和比较工具；并设计了一种通过互联网远程录音上传声音的方法。这些工具将首次允许科学家、保护管理人员、教育工作者和媒体严格地远程使用声音收集。

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.