Chapter 10: Talking to the Outside World

*The email from the Regional Veterinary Board was blunt:

Please submit your animal health records using the National Animal Health Ontology (NAHO) vocabulary. All concepts must use IRIs from http://naho.gov/ontology/. All species must reference the FAO species classification at http://fao.org/species/.

Dr. Portbridge looked at her Dolfin file. Her concepts were called Animal and Dog. The board expected http://naho.gov/ontology/Animal and http://fao.org/species/CanineDomestic. She needed a way to map her clean, readable names to the bureaucratic world of IRIs.

The problem

Dolfin ontologies live in a clean, human-readable world. The semantic web lives in a world of IRIs (Internationalized Resource Identifiers), long URLs that uniquely identify every concept, property, and individual. To interoperate, we need to connect the two.

Prefixes

A prefix declares a short alias for an IRI namespace:

prefix naho as <http://naho.gov/ontology/>
prefix fao as <http://fao.org/species/>

Now you can reference external concepts using the prefix:

prefix naho as <http://naho.gov/ontology/>

concept Animal:
  has name: one string

When compiled to OWL, Animal will be mapped to the naho namespace, producing http://naho.gov/ontology/Animal.

Using prefixed references

Prefixes let you reference concepts from other ontologies:

prefix schema as <http://schema.org/>

concept Owner:
  has first_name: one string
  has last_name: one string
  has phone_numbers: at least 1 string
  has email: optional string
  has address: optional schema.PostalAddress

schema.PostalAddress refers to http://schema.org/PostalAddress, Schema.org’s definition of a postal address. You’re linking your clinic ontology to a globally recognized vocabulary.

The @iri_name annotation

Sometimes the external name for a concept differs from the name you want in your code. The @iri_name annotation lets you control the exact IRI segment:

@iri_name
concept DomesticDog:
  sub Animal
  has breed: optional string
  has neutered: one boolean

This is useful when external systems expect a specific IRI fragment that doesn’t match your preferred concept name.

Multiple prefixes

A real-world ontology often bridges multiple external vocabularies:

prefix naho as <http://naho.gov/ontology/>
prefix fao as <http://fao.org/species/>
prefix schema as <http://schema.org/>
prefix dc as <http://purl.org/dc/elements/1.1/>

Each prefix is independent. You can use as many as needed.

The complete clinic with prefixes

prefix naho as <http://naho.gov/ontology/>
prefix fao as <http://fao.org/species/>
prefix schema as <http://schema.org/>

package <http://happypaws.com/clinic>:
  dolfin_version "1"
  version "1.0.0"
  author "Dr. Helen Portbridge"
  description "The Happy Paws veterinary clinic data model"

concept Species:
  only values:
    Dog
    Cat
    Bird
    Rabbit
    Reptile
    Other

concept Urgency:
  only values:
    Routine
    Urgent
    Emergency

concept AppointmentStatus:
  only values:
    Scheduled
    InProgress
    Completed
    Cancelled

concept Owner:
  has first_name: one string
  has last_name: one string
  has phone_numbers: at least 1 string
  has email: optional string
  has address: optional string
  has preferred_vet: optional Veterinarian

concept Veterinarian:
  has name: one string
  has license_number: one string
  has specialization: optional string

concept Surgeon:
  sub Veterinarian
  has surgery_count: one int
  has certified_procedures: at least 1 string

concept Dentist:
  sub Veterinarian
  has dental_certification: one string

concept Intern:
  sub Veterinarian
  has university: one string
  has year: one int

concept Vaccination:
  has vaccine_name: one string
  has date_administered: one string
  has batch_number: optional string

concept Animal:
  has name: one string
  has species: one Species
  has age: optional int
  has weight: optional float
  has owner: optional Owner
  has vaccinations: Vaccination
  has allergies: string

concept Dog:
  sub Animal
  has breed: optional string
  has neutered: one boolean

concept Cat:
  sub Animal
  has indoor: one boolean

concept Bird:
  sub Animal
  has wingspan: optional float
  has can_fly: one boolean

concept Appointment:
  has animal: one Animal
  has date: one string
  has reason: one string
  has urgency: one Urgency
  has status: one AppointmentStatus
  has diagnosis: optional string
  has treatments: string
  has notes: optional string

property treatedBy:
  Animal -> Veterinarian

# Flag concepts
concept UnvaccinatedAnimal
concept UnsafeAssignment
concept OverweightAnimal
concept SeniorCat
concept InvalidSurgery
concept UnderVaccinatedDog
concept AtRiskAnimal

# Inference rules
rule flag_unvaccinated:
  match:
    ?animal a Animal
    ?animal vaccinations 0
  then:
    ?animal a UnvaccinatedAnimal

rule flag_intern_emergency:
  match:
    ?appt a Appointment
    ?appt urgency Emergency
    ?appt animal [ treatedBy [ a Intern ] ]
  then:
    ?appt a UnsafeAssignment

rule flag_overweight_dog:
  match:
    ?dog a Dog
    ?dog weight [ > 40.0 ]
  then:
    ?dog a OverweightAnimal

rule flag_senior_cat:
  match:
    ?cat a Cat
    ?cat age [ >= 10 ]
  then:
    ?cat a SeniorCat

rule assign_primary_vet:
  match:
    ?animal a Animal
    ?animal owner [ preferred_vet ?vet ]
  then:
    ?animal treatedBy ?vet

rule validate_surgery_staff:
  match:
    ?appt a Appointment
    ?appt reason "surgery"
    among:
      ?appt animal [ treatedBy ?vet ]
    none:
      ?vet a Surgeon
  then:
    ?appt a InvalidSurgery

rule check_dog_vaccines:
  match:
    ?dog a Dog
    ?dog vaccinations 0
  then:
    ?dog a UnderVaccinatedDog

rule flag_at_risk:
  match:
    ?animal a Animal
    ?animal age [ > 15 ]
    ?animal weight [ < 2.0 ]
    ?animal vaccinations 0
  then:
    ?animal a AtRiskAnimal

Try it

Add a prefix for Dublin Core (http://purl.org/dc/elements/1.1/) and FOAF (http://xmlns.com/foaf/0.1/):

prefix naho as <http://naho.gov/ontology/>

# Add Dublin Core and FOAF prefixes here

Dr. Portbridge submitted the data export. The board’s system accepted it without complaint, her concepts mapped cleanly to NAHO’s IRIs, and the species references aligned with FAO’s vocabulary. Her little clinic was speaking the same language as the national registry.

She leaned back in her chair and looked at the screen. What had started as a napkin sketch was now a complete data model: concepts with inheritance, cardinality constraints, enums for controlled vocabularies, rules for automated reasoning, constraints for validation, and prefixes for interoperability. Biscuit dozed at her feet. Pixel purred on the printer.