Core Linked Data Interest Group

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Purpose: Provides a forum for discussion of issues related to Linked Library Data and the role of library metadata in the Semantic web. Goals include: raising awareness of Semantic Web technologies, such as the Resource Description Framework (RDF) and the use of URIs as identifiers within bibliographic descriptions; promoting research on linked data challenges, such as domain modeling and vocabulary selection and design; and informing the ongoing development of existing metadata standards for Libraries, Archives and Cultural Heritage Institutions.

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This group is part of Core's Technology Section.

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Core IG Week: Metadata IG Program Announcement

  • 1.  Core IG Week: Metadata IG Program Announcement

    Posted Jul 19, 2021 10:25 AM

    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:

    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!

    Anne Washington
    Product Analyst