Ontology Pipeline: A Framework for Knowledge Engineering, by Jessica Talisman
Build semantic knowledge systems with trusted and AI-ready taxonomies, ontologies, and knowledge graphs.
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Ontology Pipeline gives data leaders, semantic engineers, ontologists, taxonomists, knowledge managers, librarians, AI architects, and enterprise data teams a practical framework for turning messy organizational language into structured, machine-readable knowledge. Instead of treating ontology development or knowledge graph construction as a black box, this book provides a clear sequence: controlled vocabularies, metadata schemas, taxonomies, thesauri, ontologies, and knowledge graphs.
Analyze how language, definitions, labels, synonyms, metadata, and relationships shape the performance of artificial intelligence systems. The book explains why large language models, retrieval-augmented generation, semantic search, entity resolution, and information retrieval all depend on clean, governed, semantically enriched data. It also shows how library and information science methods can help organizations build scalable semantic knowledge management systems that support both human understanding and machine reasoning.
Design each stage of the Ontology Pipeline with practical guidance, examples, standards, and implementation patterns. Readers will explore controlled vocabulary development, SKOS taxonomies, thesaurus relationships, RDF, OWL, SHACL, SPARQL, competency questions, ontology governance, semantic validation, and knowledge graph architecture. The book connects these concepts to real enterprise needs, including data quality, semantic layers, AI governance, domain modeling, knowledge management, and production AI infrastructure.
Evaluate what it really takes to build and maintain a knowledge graph as architecture, not just as a product or database. Learn why we build, govern, and maintain a knowledge graph with attention to semantic debt, staffing, operational funding, ontology change management, validation workflows, and long-term trust. For teams investing in AI, data governance, data catalogs, metadata management, enterprise architecture, or semantic technology, this book provides the missing roadmap.
Apply the Ontology Pipeline to create a formal, explicit, shared model of what your organization knows. Whether you are building a semantic layer, improving RAG accuracy, designing a domain ontology, creating an enterprise knowledge graph, or trying to make AI outputs more reliable, Ontology Pipeline provides the vocabulary, structure, and processes to move from disconnected data to governed organizational knowledge.
Jessica Talisman is a Semantic Engineer, Information Architect, and knowledge infrastructure strategist with more than 25 years of experience spanning enterprise architecture, e-commerce content systems, digital libraries, and knowledge management.
She is the creator of the Ontology Pipeline™, a structured framework for building semantic knowledge infrastructure from first principles, moving progressively from controlled vocabularies to taxonomies, thesauri, ontologies, and fully realized knowledge graphs. She has led semantic architecture initiatives at Adobe, where she architected an RDF-based knowledge graph supporting the Digital Experience ecosystem, and at Amazon, where she worked in information architecture and taxonomy.
She is the founder of Contextually LLC, a consulting and coaching practice specializing in ontology modeling, NLP integration, knowledge graphs, and knowledge infrastructure design, and of The Knowledge Graph Academy, a cohort-based program that trains future semantic engineers and ontologists through a balance of theory and practice. She writes regularly on her Substack newsletter, Intentional Arrangement, where her work explores the relationship between semantic systems and AI.
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