Improving Access to Archival Collections with Automated Entity Extraction

Autor: Kyle Banerjee, Max Johnson
Jazyk: angličtina
Rok vydání: 2015
Předmět:
Zdroj: Code4Lib Journal, Iss 29 (2015)
Druh dokumentu: article
ISSN: 1940-5758
Popis: The complexity and diversity of archival resources make constructing rich metadata records time consuming and expensive, which in turn limits access to these valuable materials. However, significant automation of the metadata creation process would dramatically reduce the cost of providing access points, improve access to individual resources, and establish connections between resources that would otherwise remain unknown. Using a case study at Oregon Health & Science University as a lens to examine the conceptual and technical challenges associated with automated extraction of access points, we discuss using publically accessible API’s to extract entities (i.e. people, places, concepts, etc.) from digital and digitized objects. We describe why Linked Open Data is not well suited for a use case such as ours. We conclude with recommendations about how this method can be used in archives as well as for other library applications.
Databáze: Directory of Open Access Journals
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