Logistics Domain Ontology

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

PURPOSE:
Represent logistics operations as typed, traceable flows of goods, information, resources and decisions across locations and time.

ENTITY_TYPES:
  LogisticsNetwork: {id, name, geographic_scope}
  Organisation: {id, name, role}
  Supplier: Organisation
  Carrier: Organisation
  Customer: Organisation
  Shipment: {id, origin, destination, status, priority}
  Consignment: {id, shipment_id, contents, quantity, unit}
  Product: {id, description, handling_requirements}
  InventoryLot: {id, product_id, quantity, location, batch_id}
  Warehouse: {id, location, capacity}
  DistributionCentre: Warehouse
  TransportVehicle: {id, mode, capacity, availability}
  Route: {id, origin, destination, legs}
  RouteLeg: {id, start, end, mode, planned_departure, planned_arrival}
  Order: {id, customer_id, line_items, requested_delivery}
  Delivery: {id, shipment_id, delivered_at, recipient_confirmation}
  TrackingEvent: {id, shipment_id, event_type, location, timestamp, source}
  Constraint: {id, type, value, scope}
  Risk: {id, description, likelihood, impact}
  Metric: {id, name, value, unit, observation_period}

RELATIONSHIP_TYPES:
  PLACED_BY(Order, Customer)
  FULFILLED_BY(Order, Shipment)
  CONTAINS(Shipment, Consignment)
  REFERENCES_PRODUCT(Consignment, Product)
  STORED_AT(InventoryLot, Warehouse)
  OPERATED_BY(Warehouse, Organisation)
  CARRIED_BY(Shipment, Carrier)
  ASSIGNED_TO(Shipment, TransportVehicle)
  FOLLOWS(Shipment, Route)
  HAS_LEG(Route, RouteLeg)
  ORIGINATES_AT(Shipment, Location)
  DESTINED_FOR(Shipment, Location)
  RECORDED_FOR(TrackingEvent, Shipment)
  SUBJECT_TO(Shipment, Constraint)
  EXPOSED_TO(Shipment, Risk)
  COMPLETES(Delivery, Shipment)
  MEASURED_BY(LogisticsNetwork, Metric)

FLOW:
  Order -> DemandValidation -> InventoryAllocation -> Picking -> Packing
  -> Dispatch -> Transportation -> Tracking -> DeliveryConfirmation
  -> Reconciliation -> PerformanceReview

INVARIANTS:
  I1: Inventory quantity must not be negative unless explicitly modelled as backorder.
  I2: Every shipment has a traceable origin and destination.
  I3: Tracking events are ordered by timestamp; late-arriving events retain original event time.
  I4: Delivery confirmation must be supported by a recorded event or evidence.
  I5: Units, currencies, time zones and jurisdictions must be explicit when relevant.
  I6: Estimates and observations must be distinguished.

INFERENCE_RULES:
  R1: IF allocated_stock < requested_quantity THEN flag FulfilmentShortfall.
  R2: IF actual_arrival > committed_delivery_time THEN classify DeliveryLate.
  R3: IF shipment_tracking_event indicates damaged goods THEN open DamageException.
  R4: IF route_leg unavailable THEN trigger RouteReplanningCandidate.
  R5: IF shipment lacks valid delivery evidence THEN delivery_status = Unverified.
  R6: IF inventory_lot expiry precedes planned_dispatch THEN flag StockSuitabilityReview.
  R7: IF capacity_demand > available_capacity THEN flag CapacityConstraint.
  R8: IF tracking timestamps conflict THEN flag TemporalConsistencyReview.

CONFIDENCE:
  confidence(assertion) in [0,1]
  Inputs: evidence_quality, source_reliability, timeliness, consistency, completeness.
  Never interpret confidence as proof or a guaranteed probability without calibration.

SEMANTIC_EQUIVALENCE:
  shipment ~= consignment ONLY under declared mapping and context.
  warehouse ~= distribution_centre ONLY when operational functions align.
  delivery_time != dispatch_time.
  planned_arrival != actual_arrival.
  equivalence requires entity type, scope, unit and temporal compatibility.

PROVENANCE:
  Every material assertion records {source_id, observed_at, recorded_at, method, version}.
  Preserve conflicting source assertions rather than silently overwriting them.

FLOW_HASH:
  canonical_payload = canonicalise(entity_types, relationships, rules, version, source)
  flow_hash = SHA256(UTF8(canonical_payload))
  Hash value computed by implementation; no fabricated digest supplied.

UPDATE_MODEL:
  versioning: semantic_versioning
  on_change: validate_schema -> compare_versions -> record_provenance -> recalculate_hash -> publish
  retain_history: true
  invalidation: dependent inferences and affected route/stock states

AI_CONSUMPTION:
  output: typed_graph + rules + confidence + provenance + exceptions
  validation: enforce_types, temporal_order, units, referential_integrity
  safeguards: do_not_invent_tracking_events; distinguish_forecast_from_observation
  interoperability: map to relevant logistics and supply-chain vocabularies when verified

END FLOW ALGEBRA