Python, Google Sheets, and the Thesaurus for Graphic Materials for Efficient Metadata Project Workflows

In 2017, the University of Virginia (U.Va.) will launch a two year initiative to celebrate the bicentennial anniversary of the University’s founding in 1819. The U.Va. Library is participating in this event by digitizing some 20,000 photographs and negatives that document student life on the U.Va. grounds in the 1960s and 1970s. Metadata librarians and archivists are well-versed in the challenges associated with generating digital content and accompanying description within the context of limited resources. This paper describes how technology and new approaches to metadata design have enabled the University of Virginia’s Metadata Analysis and Design Department to rapidly and successfully generate accurate description for these digital objects. Python’s pandas module improves efficiency by cleaning and repurposing data recorded at digitization, while the lxml module builds MODS XML programmatically from CSV tables. A simplified technique for subject heading selection and assignment in Google Sheets provides a collaborative environment for streamlined metadata creation and data quality control

Emulation in the Archives Workshop

The UVA Library Fostering a Community of Practice (FCOP) grant project team (supported by IMLS grant RE-95-17-0058-17) held a free workshop on software preservation and emulation in archival environments in July 2019. Resources from the event include project team and featured speaker presentations, as well as open community notes that contain references and links to further documentation, including UVA project team drafts of descriptive, curatorial, and technical workflows for software preservation and emulation in archives