The Map of Being: Understanding Ontology

For our latest installment in the Metaphysics series on iversonsoftware.com, we move from general existence to the specific architecture of reality: Ontology. In the world of information science and philosophy alike, ontology is the discipline of defining what “entities” exist and how they are categorized.

At Iverson Software, we build databases, and every database requires a schema. In philosophy, Ontology is the “master schema” of the universe. It is the branch of metaphysics that studies the nature of being, existence, and reality. It asks the most fundamental structural questions: What categories of things exist? and How do these categories relate to one another?

1. The Inventory of Reality: What’s on the Disk?

The primary task of an ontologist is to create an inventory of everything that is “real.” This is harder than it sounds.

  • Concrete Entities: Physical objects like trees, servers, and human bodies.

  • Abstract Entities: Things that don’t take up space but still “exist” in some sense, such as numbers, sets, and the laws of logic.

  • Properties: Does “Redness” exist as a thing itself, or are there just red objects?

2. Universalism vs. Nominalism

One of the oldest “debugging” sessions in philosophy concerns the status of Universals.

  • Universalism: The belief that general properties (like “circularity”) are real things that exist independently of any specific circle.

  • Nominalism: The belief that only individual, specific objects exist. “Circularity” is just a name (a nomen) we use to group similar things together—it has no existence of its own.

3. Applied Ontology in Information Science

In the 21st century, ontology has moved from abstract philosophy to the core of the Semantic Web and Artificial Intelligence.

  • Knowledge Representation: In computer science, an “ontology” is a formal way of representing properties and relationships between concepts in a specific domain.

  • Interoperability: By creating a shared ontology (like the “Gene Ontology” in biology), different software systems can “understand” each other because they are using the same definitions for the same entities.

4. Mereology: The Logic of Parts and Wholes

A critical sub-field of ontology is Mereology—the study of parts and the wholes they form.

  • The Sum of Parts: Is a “computer” just a collection of silicon and plastic, or is it a new entity that emerges when those parts are assembled?

  • Identity Over Time: If you replace the hard drive, RAM, and screen of a laptop over five years, is it still the same “object” in your inventory?


Why Ontology Matters to Our Readers

  • Structured Thinking: Learning ontology helps you build better mental models, allowing you to categorize complex information more efficiently.

  • Data Architecture: For developers and architects, philosophical ontology provides the theoretical background for creating robust class hierarchies and database schemas.

  • AI Clarity: As we move toward more advanced AI, the ability to define clear, unambiguous ontologies is what prevents machines from making “category errors” that lead to logical failures.

The Backend of Reality: Understanding Metaphysics

At Iverson Software, we specialize in the systems that organize human knowledge. But what is the nature of the things we are organizing? Metaphysics is the branch of philosophy that looks behind the physical world to ask about the fundamental nature of reality. If physics tells us how a ball falls, metaphysics asks what it means for the ball to “exist” in the first place.

1. Ontology: The Study of Being

Ontology is the sub-branch of metaphysics that deals with the nature of being. In computer science, an “ontology” is a formal naming and definition of the types, properties, and interrelationships of entities. Philosophical ontology asks similar questions:

  • What is an Entity? Does a “software program” exist in the same way a “mountain” does?

  • Abstract vs. Concrete: Are numbers and logical laws real things, or are they just tools we invented to describe the world?

  • Identity and Change: If you update every line of code in a program, is it still the same program? This mirrors the classic “Ship of Theseus” paradox.

2. Cosmology: The Grand Design

While modern astronomy uses telescopes to see the stars, Metaphysical Cosmology uses reason to understand the structure of the universe as a whole.

  • Determinism vs. Free Will: Is the universe a “pre-compiled” script where every event is inevitable, or is it an open-world environment where users have true agency?

  • Causality: The “Input/Output” relationship of the universe. Metaphysics investigates the “Prime Mover” or the first cause that set the entire system in motion.

3. The Mind-Body Problem

Perhaps the most famous metaphysical question is the relationship between the physical brain (hardware) and the conscious mind (software).

  • Dualism: The belief that the mind and body are two distinct substances.

  • Physicalism: The belief that everything about the mind can be explained by physical processes in the brain.

  • Artificial Intelligence: Metaphysics asks: if we perfectly simulate a human brain in silicon, would it possess “being” and “consciousness,” or would it just be a sophisticated Chinese Room?

4. Space and Time: The Global Variables

Metaphysics questions the very fabric in which our lives take place.

  • Presentism vs. Eternalism: Is only the “now” real (like a single frame of data), or do the past and future exist simultaneously as part of a four-dimensional “block universe”?

  • Relational Space: Is space a “container” that things sit in, or is it simply a set of relationships between objects?


Why Metaphysics Matters to Our Readers

  • Foundational Thinking: Metaphysics trains you to look for the “root cause” and the underlying assumptions in any system or argument.

  • Bridging Science and Mystery: It provides a language for discussing things that science cannot yet measure, such as purpose, value, and the nature of the self.

  • System Design: Understanding ontology helps developers and architects create better data models by forcing them to define exactly what their objects are and how they relate.