docs: RDF / OWL ↔ OGAR alignment — Morris triad + brutal-upgrade vision#30
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New doc `docs/RDF-OWL-ALIGNMENT.md` (820 lines). The OGAR-side pin for
how OGAR composes with the existing W3C / OMG / Foundry ontology stack
+ the architectural map for the next phase: OGAR as an ontology-aware
ingestion substrate (not "just Neo4j").
Six headline claims (§0 TL;DR):
1. The Morris triad (syntax / semantics / pragmatics) cuts ACROSS
the existing L1-L5 ontology stack. OGAR HHTL sits at the
consumer end (inner = compile-time HHTL; outer = adapter
pragmatic rebind; boundary = TTL serialization).
2. OGAR is the runtime application-schema producer for L5 — the
AR-pattern lift (Rails / Odoo / Django / Ecto / SurrealQL)
into a unified Class/Attribute/Association/EnumDecl/ActionDef
IR. vocab/ogar.ttl (168 OWL/RDFS declarations) makes OGAR a
first-class OWL participant.
3. THE BRUTAL UPGRADE (§4): OGAR grows an OWL/RDF/TTL DDL adapter
(ogar-adapter-ttl) + per-element syntax/semantics/pragmatics
auto-detection + pattern-AST recognition (FMA-Pattern-D,
FIBO-FND-shape, schema.org-shape, SKR03/04-shape, PROV-O-audit
-shape) + confidence scoring + actionable-item extraction
(lifecycle → ActionDef + KausalSpec) + VART radix-trie cache +
Claude Code session as the validation harness.
4. The architectural litmus is FMA bones-rendering (§6) — ~75K
static anatomy classes, ~2.1M relationships, perfect fit for
compile-time HHTL. Bones → muscles → vasculature → innervation,
each rebound at the per-deployment Adapter for 3D mesh / locale
label / rendering material.
5. Adjacent multi-hop alignment ontologies (§8) — odoo-to-fibo,
GoBD ↔ PROV-O, FIBO-FND ↔ ogit:smb:Organization — are
low-effort inputs (cross-vocab semantic work already done).
6. Statistical confidence calibration (§4.10) — a one-time
calibration against a 4096-dim Deep-NSM encoder
(Wierzbicka's semantic primes as the substrate) upgrades the
confidence surface from hand-coded heuristics to statistically
grounded scores. Same encoder maps text + OWL into the same
4096-dim space; calibrated heads emit per-axis confidence (SPO
/ TeKaMoLo / Morris-layer / DOLCE-slot / Action-likelihood).
Trained once; const-table inference per subsequent import.
Cites and does not re-derive (§1):
- Woa-rs/.claude/reference/erp_foundry_hhtl_ontology_distillation.md
(686 lines, L1-L5 architecture)
- Woa-rs/.claude/reference/four_way_alignment_seam.md (441 lines,
odoo ↔ OWL/DOLCE/FIBO ↔ OGIT ↔ lance-graph)
- Woa-rs/docs/LANCE-GRAPH-HYDRATORS-AVAILABLE.md (lance-graph #407,
11 hydrators wired)
- lance-graph/.grok/GLUE_LAYER_OGIT_TO_OWL_SPEC.md
- lance-graph/.claude/knowledge/ogit-owl-dolce-ontology-compartments.md
- Pillar-14 partial-order axioms (ndarray #188 + OntologySchema::
is_ancestor #189)
- bardioc PR #17 (Rubicon Phases 1-5), PR #18 (BindSpace
dissolution handover), lance-graph PR #470
Direct OGAR ↔ OWL correspondences pinned (§5):
Class.identity ↔ rdf:about URI
Class.inheritance ↔ rdfs:subClassOf (Pillar-14 partial-order guard)
Attribute ↔ owl:DatatypeProperty
Association::BelongsTo ↔ owl:ObjectProperty + owl:FunctionalProperty
EnumDecl::Static(items) ↔ owl:oneOf
EnumDecl::Add { parent_selection } ↔ owl:unionOf
EnumDecl::Computed ↔ runtime-computed; outside OWL DL
KausalSpec::StateGuard ↔ SHACL sh:NodeShape (OGAR extension past OWL)
KausalSpec::LifecycleTrigger ↔ pure OGAR extension
TeKaMoLo ↔ DOLCE DnS role binding + Fillmore case grammar
Adapter HHTL leaf-rename ↔ skos:prefLabel@locale rebind
OntologyDto::project(…, locale) ↔ canonical Morris-pragmatic
projection in code
Sequencing (§10): phase 1 = this doc; phases 2-9 = ogar-adapter-ttl
scaffold, vart-backend feature, ogar-pattern, ogar-actionable, Claude
Code validation harness, ImportSchemaSource trait, FMA hydrator,
Deep-NSM calibration. Each phase ships as a PR with green CI.
PII abort-guard scan: CLEAN (zero German PII tokens; FHIR resource
names used only as W3C / HL7 public-spec terms).
https://claude.ai/code/session_01PBTGaPCSnnt6u3pjXpbLwY
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| | `Class.identity` (NiblePath) | `rdf:about` URI | Identity is the contract; labels are pragmatic | | ||
| | `Class.inheritance` | `rdfs:subClassOf` | Direct; Pillar-14 partial-order axiom (`ndarray` #188) guarantees no cycles | |
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Class API in the OWL mapping
The current OGAR IR does not expose Class.identity or Class.inheritance: crates/ogar-vocab/src/lib.rs defines Class with name and parent, while canonical identities are produced separately by ogar_ontology::class_identity(...). Since §4.1 is meant to guide the TTL adapter implementation, this table can send implementers toward non-existent fields or encourage adding a parallel inheritance/identity representation instead of lowering rdfs:subClassOf into Class::parent and deriving the NiblePath identity via ogar-ontology.
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Jun 5, 2026
Cross-session companion to the lance-graph splat-native-ultrasound-v1 canonical plan. Names splat-native ultrasound as the explicit downstream customer of OGAR PR #30 §6 FMA bones-rendering litmus + Phase 8 FMA hydration. The §6 litmus transitions from "demo target" to "load path" — splat-native is the contemporary customer of the FMA atlas substrate at the sub-millisecond HHTL traversal claim. The SaMD Class IIa certification track uses ADR-022 (The Firewall) + KnowableFromStore (PR #25/#31) + commit_event audit (callcenter PR #467) as the audit-controls evidence base — no new OGAR architecture for SaMD; only documentation that names what's already true. No code. Spec/narrative only.
This was referenced Jun 5, 2026
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Summary
New doc
docs/RDF-OWL-ALIGNMENT.md(820 lines). Pins OGAR's position in the existing W3C / OMG / Foundry ontology stack + the architectural map for the brutal-upgrade phase: OGAR as an ontology-aware ingestion substrate, not "just Neo4j".Six headline claims (§0 TL;DR)
Morris triad (syntax / semantics / pragmatics) cuts ACROSS L1-L5. OGAR HHTL is the consumer-end terminal: inner = compile-time HHTL (semantics resolved), outer = adapter (pragmatics rebound per deployment), boundary = TTL serialization (syntax). The triad framing names what's already implicit in the L1-L5 layering.
OGAR is the runtime application-schema producer for L5 — the AR-pattern lift (Rails / Odoo / Django / Ecto / SurrealQL DDL) into a unified IR.
vocab/ogar.ttl(168 OWL/RDFS declarations) +ogar-emitter(129 RDF predicates) make OGAR a first-class OWL participant.The brutal upgrade (§4, ten sub-sections): OWL/RDF/TTL DDL adapter (
ogar-adapter-ttl) + syntax/semantics/pragmatics auto-detection + SPO+TeKaMoLo+Morris representation + pattern-AST recognition + actionable-item extraction (lifecycle →ActionDef+KausalSpec) + confidence scoring + VART radix-trie cache + Claude Code session as the validation harness + multi-domain overlay + §4.10 statistical confidence calibration via 4096-dim Deep-NSM encoder.FMA bones-rendering as the architectural litmus (§6) — ~75K static anatomy classes, ~2.1M relationships, perfect fit for compile-time HHTL. The 3D mesh + locale labels live at the per-deployment Adapter (pragmatic-layer rebind). If HHTL can traverse "what nerves innervate the left biceps brachii" in sub-millisecond without heap allocation, the architecture works.
Multi-hop alignment ontologies as low-effort inputs (§8) —
odoo-to-fibo.ttl,GoBD ↔ PROV-O, etc. The cross-vocab semantic work is already done; OGAR just consumes the alignment axioms.Statistical confidence calibration (§4.10) — 4096-dim Deep-NSM encoder (Wierzbicka's ~65 semantic primes as substrate); same encoder maps text and OWL into the same space; calibrated heads emit per-axis confidence (SPO / TeKaMoLo / Morris / DOLCE-slot / Action-likelihood); trained once; const-table inference per subsequent import (fits inside the firewall's inner-loop budget).
Doesn't re-derive what's already built
§1 cites the existing harvest as authoritative:
Woa-rs/.claude/reference/erp_foundry_hhtl_ontology_distillation.mdWoa-rs/.claude/reference/four_way_alignment_seam.mdWoa-rs/docs/LANCE-GRAPH-HYDRATORS-AVAILABLE.mdlance-graph/.grok/GLUE_LAYER_OGIT_TO_OWL_SPEC.mdogit_to_owl_glue::MapperAPI contractndarrayPR #188 +OntologySchema::is_ancestorPR #189Direct OGAR ↔ OWL correspondences pinned (§5)
Class.identity(NiblePath)rdf:aboutURIClass.inheritancerdfs:subClassOfAssociationKind::BelongsToowl:ObjectProperty+owl:FunctionalPropertyEnumDecl::Static(items)owl:oneOfEnumDecl::Add { parent_selection }owl:unionOfKausalSpec::StateGuardsh:NodeShape(OGAR extension past OWL DL)KausalSpec::LifecycleTriggerskos:prefLabel@localerebindOntologyDto::project(…, locale)Sequencing (§10) — phase 1 (this PR) → phase 9
ogar-adapter-ttlcrate scaffoldogar-knowable-from::vart-backendfeatureogar-patterncrate — recognition library + confidence scoringogar-actionablecrate — lifecycle extraction →ActionDefImportSchemaSourcetrait (reverse OGAR ↔ registry direction)hydrate_fmaon the registry side — bones-rendering litmusCompatibility
This is the doc the substrate has been wanting since the OWL harvest started landing. Captures the vision before it dilutes — per the standing autoattend mandate.
https://claude.ai/code/session_01PBTGaPCSnnt6u3pjXpbLwY