The injustices embedded in the collecting and descriptive practices of libraries, museums, and archives are now widely recognized and have prompted many cultural institutions to pursue inclusive and reparative initiatives, such as harmful language statements and content warnings. Remediating outdated and offensive language in metadata is, however, a far more daunting task, especially at scale. While resources like the Inclusive Metadata Toolkit support informed reparative decision-making, identifying problematic terms remains a tedious and emotionally taxing process dependent on individual keyword searching. Consequently, many institutions either lack the time and resources to engage in this work or are constrained by the sheer volume of potentially harmful language present in metadata records. With the support of an internal library seed grant program, the J. Willard Marriott Library at the University of Utah developed the Marriott Reparative Metadata Assessment Tool (MaRMAT), an open source, schema-agnostic, Python-based application for bulk metadata assessment. MaRMAT assesses tabular metadata against pre-curated and custom lexicons, generating a report flagging potentially harmful terminology by field, category, and context. By making large-scale assessment more accessible, MaRMAT empowers cultural heritage organizations to circumvent individual bias and advance equity in digital collections. MaRMAT's successful development also demonstrates the impact of small seed grant programs.
https://www.marmatproject.org/https://github.com/marriott-library/MaRMAT
