https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU/Head https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU/assertion https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU/provenance https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU/pubinfo https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RAGFeCZbpHYxSsZp8sgFIWFQe8yaTrfMusXrmYn33xdmU/assertion https://w3id.org/spaces/iswc/2026/wop http://purl.org/dc/terms/description The Workshop on Ontology Design and Patterns (WOP) is an established venue for discussing best practices, reusable solutions, and methodological advances in ontology engineering. Now in its 17th edition, WOP continues to bring together researchers and practitioners interested in improving the quality, usability, and maintainability of ontologies through the use of design patterns and structured modeling approaches. Ontology Design Patterns (ODPs) capture reusable modeling solutions to recurring ontology engineering problems. They support ontology developers by providing guidance on modeling decisions, facilitating reuse, improving interoperability, and enabling more systematic knowledge representation. Over the years, WOP has served as a forum for presenting new patterns, methodologies for pattern discovery and application, tools supporting pattern-based ontology engineering, and empirical evaluations of their effectiveness. WOP 2026 aims to foster discussion around emerging challenges and opportunities in pattern-based ontology development, including applications in knowledge graphs, semantic technologies, and AI-driven knowledge engineering. 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