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Apiary Project
Extracting and Parsing of Herbarium Specimen Data: Exploring the Use of the Dublin Core Application Profile Framework
Date: February 2010
Creator: Moen, William E.; Huang, Jane Q.; McCotter, Melody; Neill, Amanda K. & Best, Jason H.
Description: This paper discusses extraction and parsing of herbarium specimen data. Abstract: Herbaria around the world house millions of plant specimens; botanists and other researchers value these resources as ingredients in biodiversity research. Even when the specimen sheets are digitized and made available online, the critical information about the specimen stored on the sheet are not in a usable (i.e., machine-processible) form. This paper describes a current research and development project that is designing and testing high-throughput workflows that combine machine- and human-processes to extract and parse the specimen label data. The primary focus of the paper is the metadata needs for the workflow and the creation of the structured metadata records describing the plant specimen. In the project, the authors are exploring the use of the new Dublin Core Metadata Initiative framework for application profiles. First articulated as the Singapore Framework for Dublin Core Application Profiles in 2007, the use of this framework is in its infancy. The promises of this framework for maximum interoperability and for documenting the use of metadata for maximum reusability, and for supporting metadata applications that are in conformance with Web architectural principles provide the incentive to explore and add implementation experience regarding this new ...
Contributing Partner: UNT College of Information
Permallink:digital.library.unt.edu/ark:/67531/metadc81386/
An Event Model for Herbarium Specimen Data in XML
Date: 2010
Creator: Moen, William E.; Neill, Amanda K.; Best, Jason H.; McCotter, Melody; Xu, Hong & Huang, Jane Q.
Description: This poster discusses the Apiary Project. The Apiary Project, a collaboration of the Texas Center for Digital Knowledge at the University of North Texas and the Botanical Research Institute of Texas, is building a framework and web-based workflow for the extraction and parsing of herbarium specimen data. The workflow will support the transformation of written or printed specimen data into a high-quality machine-processable XML format. This poster describes an event model that informed the development of the Apiary XML Application Schema
Contributing Partner: UNT College of Information
Permallink:digital.library.unt.edu/ark:/67531/metadc81369/
An Event Model for Herbarium Specimen Data in XML Poster Abstract
Date: 2010
Creator: Moen, William E.; Neill, Amanda K.; Best, Jason H.; McCotter, Melody; Xu, Hong & Huang, Jane Q.
Description: This abstract describes a poster about the Apiary Project. The Apiary Project, a collaboration of the Texas Center for Digital Knowledge at the University of North Texas and the Botanical Research Institute of Texas, is building a framework and web-based workflow for the extraction and parsing of herbarium specimen data. The workflow will support the transformation of written or printed specimen data into a high-quality machine-processable XML format. This poster describes an event model that informed the development of the Apiary XML Application Schema
Contributing Partner: UNT College of Information
Permallink:digital.library.unt.edu/ark:/67531/metadc81384/
An Application Profile Using Darwin Core Rendered in the New Dublin Core Application Profile Framework
Date: November 2009
Creator: Moen, William E.; Huang, Jane Q.; McCotter, Melody; Best, Jason H. & Neill, Amanda K.
Description: This poster discusses an application profile using Darwin Core rendered in the new Dublin Core application profile framework. This is part of the Apiary Project, a collaboration of the Texas Center for Digital Knowledge at the University of North Texas and the Botanical Research Institute of Texas.
Contributing Partner: UNT College of Information
Permallink:digital.library.unt.edu/ark:/67531/metadc81371/
The Apiary Project: High-Throughput Workflow for Computer-Assisted Human Parsing of Biological Specimen Label Data
Date: July 2009
Creator: Best, Jason H.; Neill, Amanda K. & Moen, William E.
Description: This presentation discusses research on high-throughput workflow for computer-assisted human parsing of biological specimen label data. This is part of the Apiary Project, a collaboration of the Texas Center for Digital Knowledge at the University of North Texas and the Botanical Research Institute of Texas.
Contributing Partner: UNT College of Information
Permallink:digital.library.unt.edu/ark:/67531/metadc81372/
High-Throughput Workflow for Computer-Assisted Human Parsing of Biological Specimen Label Data
Date: 2008
Creator: Moen, William E.; Best, Jason H. & Neill, Amanda K.
Description: This grant proposal is for the United States Institute of Museum and Library Services National Leadership Grant. 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.
Contributing Partner: UNT College of Information
Permallink:digital.library.unt.edu/ark:/67531/metadc81387/