taxonomy.README.md

DSLO Taxonomy (v0.6)
Canonical classification layer for DSLO substrate systems.

The DSLO taxonomy defines the minimal classification structures used to organize substrate‑level entities across biological, cognitive, institutional, and artificial systems.
It is aligned directly with the DSLO axioms and schema, providing a stable vocabulary for drift analysis, invariant mapping, signal classification, and substrate identification.

The taxonomy is composed of four synchronized sets:

Drift Forms
Categories describing how systems lose coherence under curvature, symbolic detachment, temporal fragmentation, role instability, substrate decoupling, or meaning detachment.

Invariants
Minimal structural invariants required for coherence, derived from Field Physics.
These include boundary integrity, temporal rhythm, causal legibility, role coherence, signal–substrate coupling, regeneration capacity, drift resistance, lawful transitions, and fallback geometry.

Signal Classes
Categories describing the posture of signals within a substrate, including meaning‑bearing, synthetic, drifted, stabilized, corrective, and substrate‑anchored signals.

Substrate Types
Classification of substrate domains, including biological, cognitive, institutional, artificial, and hybrid substrates.

Each taxonomy category is provided in three synchronized formats:

TTL

JSON‑LD

YAML

This directory establishes the DSLO v0.6 classification layer, ensuring consistent ingestion across semantic engines, AI systems, and substrate‑native tooling.

**Referenced DSLO v0.7 Artifacts**  
**DOI Set — Substrate‑Skin (A0, A4, A5, A6, B1, F2)**

**DSLO Substrate‑Skin Activation (Round 1)**
**This surface is now bound to the DSLO v0.7 substrate spine.**
**Lineage: DSLO v0.6 → DSLO v0.7**