Ontological axes capture what something is in the world. They are factual, structural, and measurable, never evaluative. The catalogue in the specs defines 0–255 as ontology and names each axis; this page summarises the main blocks so you know what is preconfigured before you extend or mask them.

Preconfigured Ontology Blocks

• Physical reality (0–8) – physicality, solidity, mass/weight, size/scale, temperature (for example, the axis activated by Water BOILS_AT Celsius100), pressure, density, phase, and spatial extent.
• Space and time (9–46) – location specificity, temporality and duration, frequency/periodicity, sequence position, recency and projections, concurrency, latency/response time, spatial relation strength, distance scale, elevation/depth, navigation and path constraints, reference frames and coordinate systems.
• Biology and agency (48–79) – living flag, species/taxonomy, life stage, health and metabolism, reproduction, sensory capability, biological mobility, growth/decay, disease tags, cognition and agency baselines, sociality and territoriality, adaptability, ecosystem role, identity persistence, intentionality, communication, memory, learning, planning, tool use, emotion expressivity, ownership/stewardship, obligation capacity, authority, reputation, cooperation/competition and roles.
• Artifacts and systems (80–95) – artifact/device flags, power source, interface type, computation and storage capability, network connectivity, autonomy level, safety mechanisms, certification/compliance, maintainability, modularity, version tags, lifecycle phase, reliability, throughput capacity and precision.
• Legal and entity structure (96–125) – legal entity flag, jurisdiction, contractual capacity, liability exposure, ownership status, registration/ID, licenses/permits, regulation class, and financial entity descriptors (asset flags, value, liquidity, volatility, risk anchors, transactional history, collateral and taxation classes, insurance coverage, investment horizon, counterparty risk).
• Evidence and knowledge (128–143) – knowledge/claim flags, evidence strength, source credibility, recency, consistency with theory, falsifiability, uncertainty bands, measurement methods, model/assumption dependency, approximation levels, error bounds, curation and provenance status, update cadence and conflict counts.
• Mathematical and physical structure (144–159) – mathematical object flags, discreteness/continuity, deterministic mappings, algebraic and geometric structure tags, logical operator embedding, constraint presence, optimisation objectives, state-space size, symmetry and conservation tags, boundary and initial conditions, invariance and dimensional analysis validity.
• Processes and control (160–183) – process dynamics, inputs/outputs, control points, feedback loops, stability, throughput/latency balance, queues/buffers, resource constraints, failure modes, recovery and restart capabilities, observability/controllability, interoperability and synchronisation requirements, transition determinism, triggers and termination clarity, environmental and human-in-the-loop dependencies.
• Risk, safety, environmental and governance (184–223) – security controls, data retention and privacy requirements, availability/integrity/confidentiality tiers, compliance flags, export control sensitivity, risk category anchors, hazard presence, exposure, severity, likelihood, detectability, mitigation and residual risk, safety margins and tolerance bands, out-of-distribution and adversarial susceptibility, robustness, redundancy and diversity of evidence, escalation likelihood, social and cultural impact, ethical relevance, equity/accessibility relevance, human rights relevance, environmental and sustainability impact, resource consumption, emissions, waste, remediation, lifecycle footprint, supply-chain transparency, labour practices, community impact and governance/stewardship.

Extensions and Empirical Axes

The final slice of the ontology range, roughly 224–255, is reserved for domain-specific ontology extensions. When you add an axis here, define its meaning precisely, its expected range, and how relevance masks should treat it. Update the catalogue and `dimensions.json` so that every new fact can set it explicitly; overloading existing axes erodes interpretability.

Axes beyond 383 belong to empirical space and are not part of the fixed ontology partition. They can be used for latent or learned features, as described in the Dimensions Overview and the dimension catalogue spec.

Role in Concept Geometry and Ingestion

Ontology axes shape the box and centre of each concept's diamond. Theory layers may override them for counterfactual scenarios—such as altered physics—but such overrides are explicit and recorded. When BiasController masks axiology for audits, ontology remains intact so factual reasoning stays stable. A Sys2DSL statement like @f ASSERT Water BOILS_AT Celsius100 uses the BOILS_AT relation to connect the concept Water to the value concept Celsius100: at encoding time, the relation permutation and value concept contribute to the Temperature axis (and possibly neighbouring physical axes) according to the rules in the encoder specification, tightening the diamond around that region. A counterfactual layer can temporarily shift that bound (for example, using CF with Water BOILS_AT Celsius50) without mutating the base concept.

For the high-level partitioning and the role of empirical dimensions, see Dimensions Overview. For how these axes are populated during ingestion, see the Data Ingestion guide and the Conceptual Spaces and Ontology wiki pages.