Knowledge Graph Engineering: A Comprehensive Guide to Knowledge Representation, Graph Architecture, Ontologies, and Semantic Data (en Inglés)
Reseña del libro "Knowledge Graph Engineering: A Comprehensive Guide to Knowledge Representation, Graph Architecture, Ontologies, and Semantic Data (en Inglés)"
Knowledge Graph Engineering A Comprehensive Guide to Knowledge Representation, Graph Architecture, Ontologies, and Semantic Data Modern organizations have more data than ever, but disconnected data is difficult to understand, query, and use effectively. Knowledge graphs provide a way to connect information, represent relationships, and give data meaningful context. Knowledge Graph Engineering is a practical and comprehensive guide to designing, building, querying, and managing modern knowledge graph systems. Inside this book, you will explore: Graph theory and knowledge representation RDF, triples, and Semantic Web technologies Ontology engineering and OWL Knowledge graph schemas and domain modeling RDF triplestores and property graph databases SPARQL query design and optimization Data integration and automated graph construction Entity resolution and knowledge extraction Semantic reasoning, inference, and validation SHACL, provenance, governance, and graph quality Scalable architecture and production operations The book goes beyond basic definitions to examine the engineering decisions behind reliable knowledge graph platforms, including architecture, performance, scalability, data quality, security, maintainability, and real-world implementation challenges. Whether you are a knowledge graph engineer, data engineer, software developer, AI/ML practitioner, ontology engineer, graph database developer, or enterprise architect, this book provides the foundation needed to turn fragmented data into connected, semantic, and machine-readable knowledge. Learn the principles. Model the knowledge. Connect the data. Engineer the graph.