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

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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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Situated at the intersection of people, technology, and information, the College of Information's faculty, staff and students invest in innovative research, collaborative partnerships, and student-centered education to serve a global information society. The college offers programs of study in information science, learning technologies, and linguistics.

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

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.

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

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  • April 6, 2012, 2:30 p.m.

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  • Dec. 4, 2023, 1:29 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; (https://digital.library.unt.edu/ark:/67531/metadc81387/: accessed May 30, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Information.

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