Collaborative Research: Rapid Digital Specimen Image and Data Capture: A Web Services Solution

提案# DBI-BDI: 0345225 PI：纽约植物园与耶鲁大学和伊利诺伊大学合作建立了一个系统，对自然历史藏品中的标本（本例中为植物标本）进行成像，使用光学字符识别（OCR）、自然手写识别（NHR）和自然语言处理（NLP）读取标本上的标签，并将标签数据解析为其组成字段，然后将数据输入数据库。模块化、可配置、开源的web服务将在镜像、分布式环境中提供互操作性和可伸缩性。该项目将使自然历史藏品的数据采集更加高效，并降低每个标本数字化的相关时间和成本。

Proposal # DBI-BDI: 0345225 PI: Thiers AbstractThe New York Botanical Garden has been awarded a grant in collaboration with Yale University and the University of Illinois to create a system to image specimens in natural history collections (plant specimens in this case), use Optical Character Recognition (OCR), Natural Handwriting Recognition (NHR) and Natural Language Processing (NLP) to read the labels on the specimens and parse the label data into its component fields, then enter the data into a database. Modular, configurable, open source web services will provide interoperability and scalability in mirrored, distributed environments. This project will make the data capture of natural history collections much more efficient and lower the associated time and costs per specimen digitized.