Year: 2025
Type: conference-paper
Abstract: This paper presents a systematic evaluation and prototypical implementation of an information system for historical vocational education and training (VET) regulations in Germany.The focus of this study is on integrating structured outputs with the German Labor Market Ontology (GLMO) and a broader labor market data warehouse.A corpus of VET and CVET regulations, as published in the Federal Gazette from 1969 to 2022, was used to assess the functional and semantic requirements of the archival process.This analysis was complemented by a review of existing software frameworks, culminating in the proposal of a combined architecture utilizing Omeka S and TEI Publisher.In addition, the necessary transformations, metadata enrichment, and ETL processes required to integrate the resulting TEI XML documents into a semantically linked data environment are detailed.This work provides a concrete roadmap for the sustainable digitization and semantic integration of regulatory texts into modern labor market intelligence infrastructures.
DOI: 10.15439/2025f0064
Authors: Thomas Reiser, Petra Steiner, Kristine Hein
Language: English
Topic: Semantic Web and Ontologies
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4415421748