Mastering Ontology Engineering Handbook: From Conceptual Modeling and Knowledge Representation to Semantic Validation and Enterprise Knowledge Graph Development - Softcover

GRANT, JAMES S.

Softcover

ISBN 13: 9798167988248

Publisher: Independently published, 2026

Synopsis

Mastering Ontology Engineering Handbook

How can you transform scattered information into structured, meaningful, and interconnected knowledge? How do you design ontologies that help different systems understand the same concepts, connect related data, and support intelligent applications?

If you want to understand how modern organizations build reliable semantic knowledge systems, Mastering Ontology Engineering Handbook provides the practical knowledge and technical foundation you need.

Developing an ontology involves much more than defining concepts and creating relationships. It requires a clear understanding of terminology, metadata, classification, knowledge representation, semantic standards, data integration, and governance. Without a well-designed approach, organizations can struggle with inconsistent definitions, disconnected information, duplicated records, poor data quality, and systems that cannot interpret shared information correctly.

This handbook takes you through the complete ontology engineering process, from foundational knowledge organization to enterprise-level semantic implementation.

Inside, you will learn how to:

• Understand the foundations of semantic knowledge systems and enterprise knowledge engineering.
• Develop controlled vocabularies and manage terminology consistently.
• Design metadata schemas, taxonomies, and thesauri for effective knowledge organization.
• Build ontologies using classes, individuals, properties, relationships, and logical axioms.
• Represent structured knowledge using RDF, RDFS, OWL, SKOS, and JSON-LD.
• Apply SHACL constraints to validate semantic data and improve knowledge quality.
• Write SPARQL queries to retrieve, analyze, and manipulate RDF data.
• Design and construct enterprise knowledge graphs from multiple information sources.
• Perform entity recognition, entity resolution, record linkage, and semantic data integration.
• Develop semantic search and hybrid retrieval systems using knowledge graphs and vector embeddings.
• Understand how ontologies and knowledge graphs support large language models and retrieval-augmented generation.
• Establish semantic governance, version control, provenance, security, and production deployment practices.

What makes this book particularly valuable is its end-to-end approach. Rather than treating ontologies, metadata, taxonomies, knowledge graphs, and semantic technologies as isolated subjects, it explains how they fit together within a coordinated engineering pipeline.

Whether you are a student learning knowledge representation, a developer building semantic applications, a data engineer integrating enterprise information, or a professional responsible for knowledge management, you will gain a clearer understanding of the principles and technologies behind modern ontology systems.

You will also discover how semantic knowledge infrastructure can improve information discovery, support data interoperability, establish consistent business definitions, and provide more reliable context for AI-powered applications.

You do not need to be an experienced ontologist to begin. The material introduces foundational concepts before progressing into technical standards, practical implementation considerations, and enterprise architecture.

Are you ready to move beyond disconnected data and understand how meaningful, machine-readable knowledge is engineered?

Get your copy of Mastering Ontology Engineering Handbook today and start developing the knowledge and skills needed to design, build, validate, and manage modern semantic knowledge systems.

Edition details

• Publisher: Independently published
• Publication date: 2026
• Language: English
• ISBN 13: 9798167988248
• Binding: Paperback
• Number of pages: 497