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

One of 6 papers in the series: Apiary Project available on this site.

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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.

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18 p.

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Moen, William E.; Best, Jason H. & Neill, Amanda K. 2008.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Information to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 344 times , with 23 in the last month . More information about this paper can be viewed below.

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The UNT College of Information educates students and advances domains of knowledge in information science, library science, computing and technology systems, learning and cognition, and human performance.

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  • Main Title: High-Throughput Workflow for Computer-Assisted Human Parsing of Biological Specimen Label Data
  • Series Title: Apiary Project

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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.

Physical Description

18 p.

Notes

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.

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  • Institute of Museum and Library Services National Leadership Grant # 06-08-0079-08

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UNT Scholarly Works

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  • 2008

Added to The UNT Digital Library

  • April 6, 2012, 2:30 p.m.

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  • April 28, 2014, 3:27 p.m.

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Moen, William E.; Best, Jason H. & Neill, Amanda K. High-Throughput Workflow for Computer-Assisted Human Parsing of Biological Specimen Label Data, paper, 2008; (digital.library.unt.edu/ark:/67531/metadc81387/: accessed November 18, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Information.