Tiemann, MichaelDörpinghaus, JensShivashankar, Venkatesh HariharapuraKlein, MaikeKrupka, DanielWinter, CorneliaGergeleit, MartinMartin, Ludger2024-10-212024-10-212024978-3-88579-746-3https://dl.gi.de/handle/20.500.12116/45156Increasing globalization of the Internet has led to a growing need for the processing of data in multiple languages. This has resulted in a significant increase in the amount of multilingual data available on the web, presenting a significant challenge for accessing, processing, and integrating data from different language sources. An ontology provides a shared and precise source for system interoperability and the reuse of knowledge bases. The objective of this study is to develop an efficient approach for mapping and enriching cross-domain, dual-lingual ontologies. In this case, we will combine the Computer Science Ontology (CSO) and DBpedia. The resulting taxonomy will be analyzed using a German online job advertisement dataset of 3,567,240 records to identify trends in the development and/or requirement of tools in the Computer Science domain. In order to achieve this, we employ a comparative analysis of two distinct approaches: a holistic, hierarchical approach and a precision-driven approach. The former considers the child-parent relation of the ontology, whereas the latter solely identifies those tools directly associated with a topic in the CSO.enOntology MappingDual-lingual OntologiesLabor Market ResearchOJAsText/Conference Paper10.18420/inf2024_1781617-5468