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Linking Vocational Archive Data Using an Occupations and Educations Centric Ontology
University of Koblenz, Germany.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). University of Koblenz, Germany;Federal Institute for Vocational Education and Training (BIBB), Germany.ORCID iD: 0000-0003-0245-7752
Federal Institute for Vocational Education and Training (BIBB), Germany.
Universität Koblenz, Germany;Federal Institute for Vocational Education and Training (BIBB), Germany.
2025 (English)In: Proceedings of the Joint Workshop on Humanities-Centred Artificial Intelligence and Formal & Cognitive Reasoning, CEUR-WS , 2025, Vol. 4058, p. 6-15Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, an approach is presented for semantically enriching and linking historical vocational education and training (VET) documents using an ontology-centric method grounded in occupations and educational programs. The present study draws on a digitized corpus of archival documents from various political regimes in Germany—including the German Empire, the German Democratic Republic (GDR), and the Federal Republic Germany (FRG) — in order to explore strategies for annotating job titles and aligning them with standardized taxonomies such as KldB and ISCO. The proposed methodology integrates phrase matching, classification models, and ontology-based linking via the German Labor Market Ontology (GLMO), thereby enabling cross-referencing of documents by occupation and educational structure. The proposed workflow is designed to support longitudinal studies and promote interoperability across fragmented archival collections. This offers a scalable solution for labor market and education research.

Place, publisher, year, edition, pages
CEUR-WS , 2025. Vol. 4058, p. 6-15
Series
CEUR Workshop Proceedings
Keywords [en]
computational social sciences, data linking, NER, Text analysis
National Category
Information Systems
Identifiers
URN: urn:nbn:se:lnu:diva-142935Scopus ID: 2-s2.0-105019307610OAI: oai:DiVA.org:lnu-142935DiVA, id: diva2:2024044
Conference
CHAI+FCR 2025: Humanities-Centred Artificial Intelligence 2025 and Formal & Cognitive Reasoning
Available from: 2025-12-23 Created: 2025-12-23 Last updated: 2026-01-08Bibliographically approved

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Dörpinghaus, Jens

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CiteExportLink to record
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Citation style
  • apa
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Output format
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