Ontological Prisms

Integrate ontological frameworks across enterprise and agentic AI systems As generative AI exposes the limits of purely neural approaches, practitioners need principled methods for coupling symbolic and subsymbolic systems. Ontological Prisms: Knowledge Engineering for Enterprise & Agentic Systems introduces a three-dimensional paradigm that unfolds knowledge into observed facts, conceptual meanings, and shared categorical representations, replacing traditional two-dimensional models with explicit structures for smoother ontological integration across heterogeneous domains. Organized into three parts covering principles, foundations, and architecture; cognitive functions including language, reasoning, and judgment; and systems and knowledge engineering, the book introduces the KEOPS methodology accompanied by a practical OWL/Protégé kernel. It addresses interoperability through principled separation of communication and representation, untangles abstraction levels between upper and domain-specific ontologies, and enables diachronic knowledge management alongside concurrent engineering. Readers will also find: Explicit 3D representations of facts, concepts, and categories that replace flat models for declarative integration without unwieldy inheritance hierarchiesA principled mapping of facts, categories, and concepts to data, information, and knowledge bridging agentic and enterprise system architecturesThe KEOPS methodology with an OWL/Protégé kernel for implementing actionable ontological frameworks in real-world engineering projectsDiachronic knowledge management techniques that operate alongside concurrent engineering processes regardless of domain overlaps or misaligned life cyclesDifferentiated reading paths structured for graduates, engineers, and consultants working in agentic cognition, ontology development, and decision-making systems Designed for professionals in information systems, knowledge management, and artificial intelligence, this book provides the frameworks and tools needed to integrate enterprise architectures with AI-driven business processes. Engineers and consultants working in ontology development, agentic cognition, and business intelligence will find actionable methodologies for real-world implementation.