Transforming digital archives management through artificial intelligence
Abstract
This paper discusses the integration of artificial intelligence (AI) in managing and preserving digital archives at the Oklahoma State University Library. This project employs advanced deep-learning techniques to manage increasing volumes of digitised cultural heritage materials. The primary objectives include developing a robust model for photograph retrieval using facial recognition technologies, creating a dynamic user interface, annotating photograph records to fill metadata gaps, and validating the work. The project details how the implementation of a facial recognition pipeline is transforming the management and preservation of digital archives as it derives sustainable long-term value from the institutional archival corpus. It examines the impact of the project and key results, while also outlining new computational transformations to continuously improve digital archival practices, balancing innovation with ethical responsibility to ensure the long-term preservation and accessibility of cultural heritage materials. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/
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Author's Biography
Patrice-Andre Prud’Homme Patrice-Andre (Max) Prud’homme is an associate professor and Director of Digital Curation at the Oklahoma State University Library. He provides leadership and management in the areas of digital curation, preservation and discovery of digital resources, incorporating the application of computational methods and resources to augment the value of digital archival materials.
Jeevithesh Cattamanchi Venu is a graduate research assistant, pursuing a master’s in computer science at Oklahoma State University. He is working in the Digital Archives Library on developing machine learning models for digital image processing with the aim of enhancing metadata.
Arundeep Bandaru is a data analyst. He holds a master’s degree in computer science from Oklahoma State University. Previously, he contributed to the Digital Archives Library project at Oklahoma State University Library, where he developed machine-learning models to enhance metadata and improve the accessibility and discoverability of digital archival materials. Arundeep is particularly interested in data science, data engineering and analytics.
