OWL 2 Web Ontology Language Primer (Second Edition)

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Explainable AI (XAI): Core Ideas, Techniques, and Solutions (2022, unknown): “Knowledge graphs represent facts, usually in the W3C standard, Resource Description Framework [5] or using graph databases and can be linked to ontologies that represent background or contextual knowledge commonly in the Web Ontology Language [29].”
Towards a smart city based on cloud of things, a survey on the smart city vision and paradigms (2014, background): “However, these standards do not provide facilities for abstraction, categorisation and reasoning rather offered by [22], within the World Wide Web Consortium Semantic Sensor Network Incubator group defined a Web Ontology Language2 [23], answering the need for a domain-independent and end-to-end mode”
Semantic web technologies in AEC industry: A literature overview (2017, methodology): “The semantic web namely relies on OWL for the representation of the semantic meaning of concepts [24] , which is grounded in Description Logic (DL — [25] ).”
Explaining Trained Neural Networks with Semantic Web Technologies: First Steps (2017, methodology): “At the same time, they play a very prominent role in the Semantic Web ﬁeld since they are the foundation for one of the central Semantic Web standards, namely the W3C Web Ontology Language OWL [11,12].”
Knowledge Graphs (2020, unknown): “For details of concrete syntaxes, we rather refer to the OWL and OBOF standards [239, 365].”