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Methods for Semantic Interoperability in AutomationML-based Engineering

Hua, Yingbing

Abstract (englisch):
Industrial engineering is an interdisciplinary activity that involves human experts from various technical backgrounds working with different engineering tools. In the era of digitization, the engineering process generates a vast amount of data. To store and exchange such data, dedicated international standards are developed, including the XML-based data format AutomationML (AML). While AML provides a harmonized syntax among engineering tools, the semantics of engineering data remains highly heterogeneous. More specifically, the AML models of the same domain or entity can vary dramatically among different tools that give rise to the so-called semantic interoperability problem. In practice, manual implementation is often required for the correct data interpretation, which is usually limited in reusability.

Efforts have been made for tackling the semantic interoperability problem. One mainstream research direction has been focused on the semantic lifting of engineering data using Semantic Web technologies. However, current results in this field lack the study of building complex domain knowledge that requires a profound understanding of the domain and sufficient skills in ontology building. ... mehr

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Volltext §
DOI: 10.5445/IR/1000129048
Veröffentlicht am 15.02.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Hochschulschrift
Publikationsdatum 15.02.2021
Sprache Englisch
Identifikator KITopen-ID: 1000129048
Verlag Karlsruher Institut für Technologie (KIT)
Umfang XI, 169 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Informatik (INFORMATIK)
Institut Institut für Anthropomatik und Robotik (IAR)
Prüfungsdatum 04.12.2020
Referent/Betreuer Prof. B. Hein
Schlagwörter Interoperability, AutomationML, Concept Learning, Query By Example
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