An AI-Assisted Framework for Rapid Conversion of Descriptive Photo Metadata into Linked Data

Abstract

This paper proposes, tests, and evaluates an innovative Computational Archival Science (CAS) framework to enhance the ability to link people, places, and events depicted in historical photography collections. The protocol combines elements of computer vision with natural language processing, entity extraction, and metadata linking techniques to transform and connect existing archival metadata. Development of the framework is built upon a case study based on the Spelman College Archives Photograph Collection and provides background information, reports on the text processing, image analysis, semantic linking, and evaluation aspects associated with the design and use of the AI-supported framework.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 5 citations exist upstream.