Abstract
Ontologies are key Semantic Web technologies (SWTs) that provide means to formally and explicitly represent domain knowledge in terms of key domain concepts and their relations. Therefore, the creation of intelligent engineering applications (IEAs) that rely on SWTs depends on the creation of a suitable ontology that semantically models engineering knowledge and the representation of engineering data in terms of this ontology (i.e., through a knowledge acquisition process). The tasks of semantic modelling and acquisition of engineering knowledge are, however, complex tasks that rely on specialized skills provided by a knowledge engineer and can therefore be daunting for those SWT adopters that do not possess this skill set. This chapter aims to support these SWT adopters by summing up essential knowledge for creating and populating ontologies including: ontology engineering methodologies and methods for assessing the quality of the created ontologies. The chapter provides examples of concrete engineering ontologies, and classifies these engineering ontologies in a framework based on the Product-Process-Resource abstraction. The chapter also contains examples of best practices for modelling common situations in the engineering domain using ontology design patterns, and gives an overview of the current tools that engineers ca use to lift engineering data stored in legacy formats (such as, spreadsheets, XML files, and databases, etc.) to a semantic representation.
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This work was supported by the Christian Doppler Forschungsgesellschaft, the Federal Ministry of Economy, Family and Youth, and the National Foundation for Research, Technology and Development in Austria.
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Sabou, M., Kovalenko, O., Novák, P. (2016). Semantic Modelling and Acquisition of Engineering Knowledge. In: Biffl, S., Sabou, M. (eds) Semantic Web Technologies for Intelligent Engineering Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-41490-4_5
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