@prefix rdf: . @prefix rdfs: . @prefix xsd: . @prefix schema: . @prefix void: . @prefix dcterms: . @prefix foaf: . @prefix bibo: . @prefix fabio: . a fabio:ConferencePaper ; rdfs:label "Dormant Digital Collections, AI Triage: Lessons from the Islam West Africa Collection and Beyond" ; dcterms:subject , , , ; dcterms:title "Dormant Digital Collections, AI Triage: Lessons from the Islam West Africa Collection and Beyond" ; dcterms:date "2026-05-06"^^xsd:date ; bibo:abstract "Recent advances in large language models (LLMs) have significantly improved AI capabilities for non-Western languages and scripts. Drawing on my experience building and curating the Islam West Africa Collection (IWAC), a digital repository of over 14,500 newspaper articles and archival documents in French, English, Arabic, Hausa, and Ewe, I present a practical walkthrough of an AI-assisted research pipeline: from raw scans to interactive visualisation. The challenges I encountered with West African sources have direct parallels for scholars working with Asian languages and scripts. I outline three stages of a \"datafication\" workflow: (1) text extraction through OCR and HTR, where multimodal LLMs increasingly outperform traditional engines on degraded documents in non-Western scripts; (2) data enrichment, including named entity recognition; and (3) data visualisation, where scholars without programming expertise can use AI-assisted coding to build interactive dashboards and explore their data. I demonstrate this workflow through a sentiment analysis dashboard analysing how 12,000+ IWAC newspaper articles portray Islam across five West African countries. Featuring temporal trends, cross-country comparisons, and multi-model agreement metrics, the dashboard was developed without writing manually a single line of code, through iterative dialogue with AI assistants. I also introduce Google's NotebookLM for source analysis and synthesis. Where Arlette Farge (2013) located the \"allure\" of the archive in the slow, tactile encounter with the document, AI offers a pragmatic complement: rapid triage of the ever-growing personal collections of scans that scholars accumulate, serving as an intuition pump for thinking with sources rather than automating their consumption. Rather than a theoretical discussion, this talk is an invitation to experiment, turning dormant digital collections into active research instruments."@en ; dcterms:language ; dcterms:identifier "eref-98903" ; bibo:uri ; dcterms:type ; bibo:status ; dcterms:relation ; bibo:presentedAt "Roundtable 2: Digital Humanities und Künstliche Intelligenz in den Regionalwissenschaften, Leibniz-Zentrum Moderner Orient (ZMO), 6.5.2026" ; bibo:authorList ; dcterms:creator ; schema:isPartOf ; foaf:isPrimaryTopicOf . rdf:first ; rdf:rest rdf:nil . dcterms:modified "2026-10-19T10:24:38Z"^^xsd:dateTime . foaf:primaryTopic ; void:inDataset ; dcterms:modified "2026-10-19T10:24:38Z"^^xsd:dateTime ; dcterms:license .