Work

Enabling Local Multimodal AI for Metadata Generation in Archival Collections

Year: 2025

Type: conference-paper

Abstract: . Large-scale digitisation has transformed access to archives, but generating reliable metadata remains a bottleneck. This short study explores whether locally deployed open-source multimodal models can assist archivists by generating descriptive metadata based on the “Four Ws” (Who, What, Where, When). We implement a proof-of-concept using Qwen, supported by GPT-assisted curation of Winston Churchill images, and evaluate its potential for integration into digital catalogues.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17800315

Authors: Nanang, Minsak, Fleeting, Karyn, Mustafa, Armin

Institution: University of Surrey

Language: English

Topic: Digital and Traditional Archives Management

Subfield: Conservation

Field: Arts and Humanities

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W7108610748

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