Part I. The Ontological Shift: What Is Data? (Foundations of Data Ontology)
A philosophical and conceptual exploration of the nature of data.
Core Question: What does it mean for data to exist?
Key Chapter Themes
The essence of data: object, information, or relational meaning?
Ontology of the analog vs. digital world
Object-Oriented Ontology (OOO), philosophy of information, and the metaphysics of metadata
Why data without interpretation is meaningless
The birth of “digital being” and the rise of semantic meaning
Part II. Architecting Data Ontology: Modeling the World Through Data
A structural and methodological framework for constructing ontologies.
Core Question: How do we model complex reality into structured data?
Key Chapter Themes
Entities, relationships, attributes, and hierarchies: origins and principles
Ontology vs. Database vs. Knowledge Graph vs. Metamodel
Semantic architectures: RDF, OWL, Knowledge Graphs, Semantic Layers
Translating Reality → Concepts → Data Models
Industry patterns and case studies: Palantir, Google Knowledge Graph, finance, healthcare, and urban systems
Part III. Data Ontology in the Age of AI: Re-shaping Intelligence, Organizations, and Civilization
Applications, governance, and the societal impact of data ontology.
Core Question: How will data ontology transform the future of AI, institutions, and digital civilization?
Key Chapter Themes
AI intelligence is limited by the quality of its ontology
Data Mesh, Knowledge Graphs, and LLM-era ontology
Ontology-driven data governance, ethics, trust, and privacy
Ontological design in cities, finance, education, digital twins, and social systems
Data as a new language of civilization: toward a data-ontological society