Please join us in the ALA Core Virtual Interest Group (IG) Week Metadata IG
Session, held on July 28th, 1 pm CST, 2021.

Registration is free and open to all. Register for the session at:

This program will include two presentations and a business meeting, where
we will hold elections for new officers (interested in being an officer?
Nominate yourself!


Representation and data collection:  The ethics of using Linked Open Data
for Oklahoma Native artists



   Madison Chartier, Metadata Librarian, Oklahoma State University

   Megan Macken, Digital Scholarship Librarian, Oklahoma State University

This presentation features Oklahoma State University (OSU) Library’s
ongoing case study on implementing Linked Open Data (LOD) to broaden
Oklahoma Native artists’ online representation.  In 2010, the Oklahoma Oral
History Research Program of OSU Library began recording and archiving
interviews about Native art with tribal nation citizens throughout
Oklahoma. The Oklahoma Native Artists (ONA) collection features
first-person accounts from self-identified Native artists, Native art
gallery owners, festival organizers, and collectors. The complex history of
Indian Territory, the passage of the 1990 Indian Arts and Crafts Act, and
current state legislation regulating who may market their work as a Native
American artist are part of this story.

This case study documents an initiative to create LOD from the ONA project
using Wikidata. When a Native artist’s recently published Wikipedia article
was rejected for “lack of notability,” we began researching and increasing
documentation of artists’ exhibition histories, awards, and published
bibliographies to establish notability within the Wiki-community. This
information is scattered throughout oral history interviews, regional and
Native American newspapers, and legacy exhibition catalogues. A linked
dataset based on this research would provide a rich foundation for
visualizing connections between artists and their representation in museums.

But while LOD may help improve artists’ notability, LOD also raises the
ethical concern of balancing more inclusive data with care for the rights
of the people who are part of a linked dataset.  Who are the real
beneficiaries of this data collection?  How might individuals maintain
agency over their representation?  How we choose to address these issues
with sensitivity, and how we work with artists to make decisions regarding
data sharing, will be documented in this case study.

Looking for ‘Trouble’: Descriptive Audit Toolkit for Archival Metadata



   Meghan Lyon, Head of Technical Services, David M. Rubenstein Rare Book
   and Manuscript Library, Duke University

   Noah Huffman, Archivist for Metadata, Systems, and Digital Records,
   David M. Rubenstein Rare Book and Manuscript Library, Duke University

An important component of EDI work at the David M. Rubenstein Rare Book and
Manuscript Library (Duke) has been to analyze, contextualize, and remediate
racist or biased language in archival description. More than just finding
harmful terms, however, Librarians see auditing the metadata as a strategy
to identify which collections need better processing and new description
altogether. Some of the oldest archival collections are centered around the
records of white male protagonists, and often feature library descriptions
that marginalizes or de-emphasizes any BIPOC participants. Librarians are
seeking to address that program by auditing the description to look for
both harmful language, and helpful clues.

To help sort through about 12,000 MARC XML files and 4000 EAD XML files,
Librarians built an auditing tool with Python scripts, generously shared by
other institutions doing similar work, and then hired a Duke computer
science student who used Python and SpaCy to build a full-fledged
application with a GUI.

This presentation will showcase the workflow, challenges, and the next step
of the metadata auditing.

Register for the session at:

We look forward to seeing you in our session!