Designing Semantic Knowledge Graphs - DeBellis, Michael
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Semantic Web technologies such as OWL, RDF/RDFS, SPARQL, SHACL, and SWRL offer powerful tools for managing data in more flexible, meaningful, and scalable ways. As organizations increasingly adopt modern data architectures like Data Mesh, Data Fabric, and Data Lakes, Semantic Knowledge Graphs can serve as a unifying layer making data easier to integrate, validate, and reason over.
Yet many teams hesitate to adopt these technologies, often viewing them as overly complex or academic. This book aims to change that perception by showing how these tools can be used practically and effectively in…mehr

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Produktbeschreibung
Semantic Web technologies such as OWL, RDF/RDFS, SPARQL, SHACL, and SWRL offer powerful tools for managing data in more flexible, meaningful, and scalable ways. As organizations increasingly adopt modern data architectures like Data Mesh, Data Fabric, and Data Lakes, Semantic Knowledge Graphs can serve as a unifying layer making data easier to integrate, validate, and reason over.

Yet many teams hesitate to adopt these technologies, often viewing them as overly complex or academic. This book aims to change that perception by showing how these tools can be used practically and effectively in real-world systems. From constraint validation to domain modeling to query and inference, you'll learn how Semantic Web standards can help you work with messy, evolving, and interconnected data.

Designing Semantic Knowledge Graphs is a hands-on guide for software engineers, architects, and data professionals who want to design and build semantic models that align with modern enterprise needs. You'll learn how to bridge domain models with real data, create agile ontologies that evolve with your systems, and automate the transformation of existing data sources into knowledge graph form. Along the way, you ll explore ontology design patterns, leverage validation rules with SHACL, and integrate your knowledge graph with tools like LLMs and SPARQL for powerful query and reasoning capabilities.

All techniques are illustrated using free and widely used tools like Protégé and the community edition of AllegroGraph.

You Will:
Learn how Semantic Web standards like OWL, RDF, SPARQL, SHACL, and SWRL fit into modern data architectureUnderstand techniques for modeling domains that balance top-down structure with bottom-up data realities
Autorenporträt
Michael DeBellis is a Semantic Web and AI consultant and researcher with over 40 years of experience in industry and academia. He began designing ontologies in the early 1980s while building expert systems for Accenture and later worked as a researcher at USC’s Information Sciences Institute (ISI), where he used Loom — a direct predecessor to the Web Ontology Language (OWL). Throughout his career at firms including Deloitte, Accenture, and ThoughtWorks, he has focused on applying advanced technology to real-world enterprise challenges. His work emphasizes the practical integration of Semantic Knowledge Graphs into complex systems, highlighting the importance of user requirements, legacy data, and enterprise architecture over purely theoretical modeling. He has published and presented internationally on a broad range of topics across multiple domains.