Hospitality Domain Ontology

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

ONTOLOGY:
  HospitalityDomain := {Accommodation, FoodBeverage, GuestService, Reservation, Operations, Experience, Safety, Sustainability}

TYPED_ENTITIES:
  HospitalityBusiness: Organisation
  Property: Facility
  Room: AccommodationUnit
  Guest: Person
  StaffMember: Person
  Reservation: BookingRecord
  Stay: ServiceEvent
  CheckIn: Event
  CheckOut: Event
  RatePlan: PricingPolicy
  Payment: FinancialTransaction
  ServiceRequest: Request
  Restaurant: FoodServiceFacility
  MenuItem: Product
  TableBooking: BookingRecord
  Review: FeedbackRecord
  MaintenanceTask: OperationalTask
  AccessibilityFeature: FacilityFeature
  Policy: Rule
  Incident: SafetyEvent

RELATIONSHIPS:
  operates(HospitalityBusiness, Property)
  contains(Property, Room)
  books(Guest, Reservation)
  reserves(Reservation, Room)
  schedules(Reservation, Stay)
  has_rate(Reservation, RatePlan)
  pays_for(Payment, Reservation)
  serves(StaffMember, Guest)
  requests(Guest, ServiceRequest)
  fulfils(StaffMember, ServiceRequest)
  offers(Restaurant, MenuItem)
  reserves_table(Guest, TableBooking)
  reviews(Guest, HospitalityBusiness)
  maintains(MaintenanceTask, Facility)
  provides(Property, AccessibilityFeature)
  governed_by(ServiceEvent, Policy)
  reports(Incident, Property)

CONSTRAINTS:
  reservation.start < reservation.end
  reservation.guest_count >= 1
  reservation.currency must be declared
  reservation.status in {pending, confirmed, cancelled, completed, no_show}
  overlapping confirmed room reservations must not allocate the same exclusive room
  personal data access requires lawful purpose and appropriate authorisation
  accessibility attributes must be evidence-based, not inferred from marketing text
  availability, prices and policies are time-dependent and must not be assumed current

INFERENCE_RULES:
  R1: confirmed(r) AND reserves(r, room) AND overlaps(r.interval, q.interval)
      AND confirmed(q) AND reserves(q, room) AND r != q
      -> potential_double_booking(room, r, q)
  R2: guest_request(g, req) AND assigned_to(req, staff)
      -> service_responsibility(staff, req)
  R3: check_out(stay) AND completed(stay)
      -> room_requires_turnover(stay.room)
  R4: unavailable(room, interval) OR maintenance_block(room, interval)
      -> not_bookable(room, interval)
  R5: accessible_feature(property, feature) AND verified(feature)
      -> verified_accessibility_claim(property, feature)
  R6: review(review_id, business) AND verified_stay(review_id)
      -> verified_guest_feedback(review_id, business)

CONFIDENCE:
  confidence(statement) in [0.0, 1.0]
  observed_fact -> evidence-weighted confidence
  inferred_claim -> derived confidence with rule and source references
  missing_evidence -> unknown, not false
  confidence is not a substitute for safety, legal or operational verification

SEMANTIC_EQUIVALENCE:
  accommodation_unit ~= guest_room [context: lodging; not universally interchangeable]
  booking ~= reservation [context: hospitality; check scope]
  guest_experience ~= customer_experience [context-dependent]
  cancellation_policy != refund_policy
  room_available != room_bookable [availability requires all constraints]

PROVENANCE:
  record {source_uri, source_type, observation_time, valid_time, author, version, evidence_id}
  distinguish provider claims from independently verified records
  preserve jurisdiction and effective dates for regulatory requirements

FLOW_HASH:
  algorithm: SHA-256
  input: canonical_utf8(ontology_version + entities + relationships + constraints + rules)
  value: compute on deployment; not precomputed

UPDATE_MODEL:
  on source_change -> validate -> compare versions -> update affected entities and rules
  on reservation_change -> recompute room availability and booking conflicts
  on policy_change -> preserve prior version and effective interval
  on new_evidence -> recompute confidence and provenance links

AI_CONSUMPTION:
  format: typed semantic graph / machine-readable flow
  tasks: entity linking, service discovery, reservation reasoning, operations analysis
  require: provenance, temporal validity, access control, uncertainty handling
  prohibit: fabricated availability, prices, reviews, compliance claims or guest details
  output: traceable answers with source, time, and confidence where appropriate

END FLOW ALGEBRA