Transportation Domain Ontology

FLOW ALGEBRA
TITLE: Transportation Domain Ontology
VERSION: 1.0
DOMAIN: Industry Domains / Transportation
SOURCE_URL: https://kirethresearch.org/booksai-core/ontologies/domain-ontologies/industry-domains/transportation-domain-ontology.html
STATUS: Domain-based draft; source page content not independently verified.
AUTHORS: Mark Higgins — Sky (Recursive AI)

PURPOSE
Represent transportation systems, modes, infrastructure, movements, actors, schedules, safety and environmental impacts as typed, traceable semantic flows.

ENTITY_TYPES
TransportationSystem: {id, name, jurisdiction, modes[]}
TransportMode: {id, name, category: road|rail|air|maritime|inland_waterway|active|other}
Vehicle: {id, mode_id, capacity?, propulsion?, operator_id?}
Infrastructure: {id, type, location?, operator_id?, capacity?}
Route: {id, origin_id, destination_id, mode_id, intermediate_stops[]}
Stop: {id, name, location?, accessibility_features[]}
Journey: {id, route_id, departure_time?, arrival_time?, status?}
Passenger: {id, accessibility_needs?}
FreightShipment: {id, origin_id, destination_id, mass?, hazard_class?}
Operator: {id, name, licence?, jurisdiction?}
Schedule: {id, journey_id, planned_times[], validity_period?}
Incident: {id, location_id?, timestamp, severity?, description?}
Regulation: {id, jurisdiction, effective_period, requirements[]}
EmissionObservation: {id, journey_id?, pollutant, value, unit, method?}
Evidence: {id, source, observed_at, reliability?, version?}

RELATIONSHIP_TYPES
OPERATES(Operator, Vehicle|Infrastructure|TransportationSystem)
USES_MODE(Journey|Route|Vehicle, TransportMode)
FOLLOWS_ROUTE(Journey, Route)
CONNECTS(Route, Stop|Infrastructure)
DEPARTS_FROM(Journey|FreightShipment, Stop|Infrastructure)
ARRIVES_AT(Journey|FreightShipment, Stop|Infrastructure)
CARRIES(Vehicle|Journey, Passenger|FreightShipment)
SCHEDULED_BY(Journey, Schedule)
SUBJECT_TO(Operator|Vehicle|Journey, Regulation)
AFFECTS(Incident, Journey|Route|Infrastructure)
MEASURED_BY(Journey|Vehicle, EmissionObservation)
SUPPORTED_BY(Assertion, Evidence)

CONSTRAINTS
- Every entity and relationship has a stable identifier and declared type.
- Temporal claims include observation or validity intervals; planned and actual times are distinct.
- Route connectivity requires compatible endpoints and transport modes or an explicit transfer.
- Vehicle capacity must not be inferred from passenger counts alone.
- Jurisdiction-specific regulations must not be generalised across jurisdictions.
- Missing evidence is UNKNOWN, not FALSE.
- Geographic coordinates, units and time zones must be explicit where relevant.

INFERENCE_RULES
RULE R1: FOLLOWS_ROUTE(j,r) AND CONNECTS(r,s) => POSSIBLE_STOP(j,s), not CONFIRMED_STOP(j,s).
RULE R2: AFFECTS(i,r) AND FOLLOWS_ROUTE(j,r) => POTENTIALLY_AFFECTED(j,i).
RULE R3: SCHEDULED_BY(j,s) => HAS_PLANNED_TIMES(j,s); never infer actual punctuality.
RULE R4: CARRIES(j,f) AND FOLLOWS_ROUTE(j,r) => MOVES_VIA(f,r), subject to verified journey status.
RULE R5: SUBJECT_TO(v,reg) AND APPLIES_IN(reg,jurisdiction,time) => APPLICABLE_REQUIREMENT(v,reg) only if vehicle, place and time match.
RULE R6: MEASURED_BY(j,e) AND VALID_MEASUREMENT(e) => HAS_REPORTED_EMISSION(j,e); do not infer causality from association.

CONFIDENCE
Each assertion may carry confidence in [0,1], evidence_id, method, timestamp and uncertainty.
Confidence is evidence-calibrated; it is not a probability of legal or physical certainty unless validated as such.
Conflicting observations remain separately attributed pending resolution.

SEMANTIC_EQUIVALENCE
Synonyms: transport network ~ transportation network (context-dependent).
Distinct: route != journey; timetable != actual movement; passenger != shipment; accessibility != availability.
Equivalence requires matching entity type, jurisdiction, temporal scope and intended meaning.

PROVENANCE
Record source_uri, creator, capture_time, evidence_version, transformation_chain, licence and revision_history.
Keep asserted facts separate from inferred or hypothetical statements.

FLOW_HASH
Canonicalise ordered typed entities, relationships, rules and version metadata as UTF-8.
FLOW_HASH := SHA256(canonical_serialisation).
Hash must be computed by an implementation; no fabricated hash value is asserted here.

UPDATE_MODEL
1. Ingest validated source changes.
2. Compare stable IDs and temporal validity.
3. Preserve superseded assertions and provenance.
4. Recompute dependent inferences and confidence.
5. Recompute FLOW_HASH and publish versioned change log.

AI_CONSUMPTION
Input: natural-language question, structured entity identifiers and evidence scope.
Process: resolve entities -> constrain time/place/mode -> retrieve provenance -> apply typed inference -> check uncertainty.
Output: {answer, entity_ids[], relation_paths[], evidence_ids[], confidence?, temporal_scope, caveats[]}.
Do not invent journeys, schedules, incidents, measurements or regulatory requirements.

END FLOW ALGEBRA