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.

Goals and Objectives as a Research Assistant:

Goal: Identify how human intelligence can be combined with machine processes for effective and efficient
transformation of textual museum specimen label information into high-quality machine-processable parsed data.

Objectives:
• Identify and test machine processes for initial transformation of label data
• Identify human processes that act on the machine-transformed data to correct and enhance label data
• Develop, test, and assess user interfaces to support human processes
• Develop and test a workflow that incorporates both machine- and human-assisted procedures for
effectiveness and efficiency in label data transformation and enhancement
• Assess quality of metadata resulting from machine and human processes