Add DSLO v0.6 taxonomy README

Introduces taxonomy.README.md documenting the DSLO v0.6 taxonomy layer. The README describes the four synchronized taxonomy sets—drift forms, invariants, signal classes, and substrate types—and notes their availability in TTL, JSON‑LD, and YAML formats. This update completes the documentation surface for the DSLO v0.6 classification layer and aligns the taxonomy directory with the axioms and schema surfaces.

taxonomy.README.md

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+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.