Machine learning in the library: Developing an inter-departmental core solution to manage data

Patrice-Andre Prud'Homme, Kay K. Bjornen and Phillip Doehle
Additional contact information
Patrice-Andre Prud'Homme: University Archives, Oklahoma State University Library, Stillwater, OK 74078, USA
Kay K. Bjornen: Oklahoma State University Library, USA
Phillip Doehle: Oklahoma State University Library, USA

Journal of Digital Media Management, 2021, vol. 9, issue 2, 127-140

Abstract: The Oklahoma State University Archives identified the need for an updated, comprehensive inventory of its digital assets to guide the development of digital preservation priorities. Creating it was complicated by sparse records, limited manpower and dependence on fading institutional memory as well as poor data management. A strategic planning process was launched to address these deficiencies. Machine learning (ML) was identified as a promising tool to minimise the labour-intensive process of sorting artefacts and identifying records that needed to be augmented, cleaned or eliminated from the collection. A pilot project to explore the effectiveness of using ML to curate a high-value archival collection was implemented. This paper describes the nature of ML, its promise and limitations for use in archives, and the outcomes of the pilot project. In particular, the pilot project showed promising results in the application of facial recognition techniques. Collaboration with interested colleagues in other departments suggests that ML can be widely applied to projects throughout the library.

Keywords: archives; automation; data management; digital curation; face recognition; library; machine learning (search for similar items in EconPapers)
JEL-codes: M11 M15 (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://hstalks.com/article/6097/download/ (application/pdf)
https://hstalks.com/article/6097/ (text/html)
Requires a paid subscription for full access.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aza:jdmm00:y:2021:v:9:i:2:p:127-140

Access Statistics for this article

More articles in Journal of Digital Media Management from Henry Stewart Publications
Bibliographic data for series maintained by Henry Stewart Talks ().