High-Throughput Workflow for Computer-Assisted Human Parsing of Biological Specimen Label Data

Description:

This two-year project will advance understanding of the workflow and processes best able to increase access to and use of digitized biological collection metadata within the stakeholder communities comprised of biologists, natural history museum collections managers, biodiversity standards groups, and the library and information science community.

Creator(s):
Creation Date: 2008  
Partner(s):
UNT College of Information
Collection(s):
UNT Scholarly Works
Usage:
Total Uses: 143
Past 30 days: 14
Yesterday: 0
Creator (Author):
Moen, William E.

University of North Texas

Creator (Author):
Best, Jason H.

Botanical Research Institute of Texas

Creator (Author):
Neill, Amanda K.

Botanical Research Institute of Texas

Date(s):
  • Creation: 2008
Description:

This two-year project will advance understanding of the workflow and processes best able to increase access to and use of digitized biological collection metadata within the stakeholder communities comprised of biologists, natural history museum collections managers, biodiversity standards groups, and the library and information science community.

Degree:
Note:

Abstract: The University of North Texas's Texas Center for Digital Knowledge (TxCDK) and the Botanical Research Institute of Texas (BRIT) will conduct fundamental research with the goal of identifying how human intelligence can be combined with machine processes for effective and efficient transformation of textual museum specimen label information into high-quality machine-processible parsed data. This two-year project will advance understanding of the workflow and processes best able to increase access to and use of digitized biological collection metadata within the stakeholder communities comprised of biologists, natural history museum collections managers, biodiversity standards groups, and the library and information science community. A key challenge faced by all natural history collections is determining a transformation process that yields high-quality results in a cost- and time-efficient manner. The results of this research will yield a new workflow model for effective and efficient label data transformation, correction, and enhancement that can be replicated, adapted, and transferred to herbaria and other natural history collections.

Physical Description:

18 p.

Language(s):
Subject(s):
Keyword(s): workflows | metadata | parsing | specimens
Source: Institute of Museum and Library Services National Leadership Grant # 06-08-0079-08
Contributor(s):
Series Title: Apiary Project
Partner:
UNT College of Information
Collection:
UNT Scholarly Works
Identifier:
  • GRANTNO: 06-08-0079-08
  • ARK: ark:/67531/metadc81387
Resource Type: Paper
Format: Text
Rights:
Access: Public