Automating Transcription of Museum Specimen Labels with U-M Maizey

LSA - U-M Herbarium

Problem

Transcribing museum specimen labels is a critical yet time-consuming task at the U-M Herbarium. The research group faced challenges in efficiently managing and processing the vast amount of data from specimen labels, which required meticulous transcription and significant manual effort.

Audience

Research group working with the U-M Herbarium.

Outcome/Impact

Stephen A Smith in LSA developed a U-M Maizey bot for the research group at the U-M Herbarium to automate the transcription of museum specimen labels. This innovative Maizey bot leveraged AI to accurately and efficiently transcribe label information, significantly reducing the time and effort required for this task.

The implementation of the Maizey bot led to a streamlined transcription process, allowing the research group to handle large volumes of specimen labels with greater accuracy and speed. This automation improved data management and freed up valuable time for researchers to focus on more complex tasks and analyses.