2024, AI & LIBRARIANSHIP 

Journal of eScience Librarianship 

Objective: This project focuses on Artificial Intelligence (AI) supported enhancement of descriptive metadata for fashion collections (otherwise known as costume or dress and textile collections) through expanding costume-specific controlled terms. The authors use Natural Language Processing (NLP) techniques along with a human-in-the-loop process to support selection of descriptive terms for inclusion in the controlled terms of a metadata schema. This project seeks to expand upon existing domain-specific schema, Costume Core, by enhancing the schema with a comprehensive set of descriptors. This enhancement will allow for more accurate and detailed descriptions of costume artifacts. This article describes this process and the outcomes of AI approaches for providing this metadata expansion, who this process is for, ethical considerations, and lessons learned.Methods: We approached our problem with an investigation into using word embeddings to aid in supporting the suggesting of new metadata terms. Several word embedding models were applied with the more descriptive one chosen for final use in a human-in-the-loop selection process. This selection process provided domain experts to identify which terms chosen by the model are of relevant value. We then compare what was chosen by the domain experts and what the model produced to get an idea as to the value the model provides in the process of metadata expansion.Results: The metadata expansion process was a success. An AI supported process aided domain experts in choosing relevant terms to include in their metadata schema. Therefore, the results were a methodology for using identified AI models for the problem, an interactive system to aid the domain experts (software system), and how to evaluate the results.Conclusion: The application of AI technologies (word embeddings) provided a successful pipeline for supporting domain experts to expand the metadata schema with additional descriptors.  Enhancing the metadata schema with additional descriptors improves its usability for fashion collection managers and allows for a more precise description of the artifacts. As a result, many new terms that were expertly chosen were added to the metadata schema. 

Open Access 

McIrvin, C., Miller, C., Smith-Glaviana, D., & Ng, W. N. (2024). Automatic Expansion of Metadata Standards for Historic Costume Collections. Journal of eScience Librarianship, 13(1). https://doi.org/10.7191/jeslib.845