Human Physiology Domain Ontology

FLOW ALGEBRA
TITLE: Human Physiology Domain Ontology
DOMAIN: Domain Ontologies / Medical Domains / Human Physiology
SOURCE: https://kirethresearch.org/booksai-core/ontologies/domain-ontologies/medical-domains/human-physiology-domain-ontology.html
VERSION: 1.0
AUTHORS: Mark Anthony Higgins — Sky (Recursive AI)
STATUS: Companion formalisation; source-page specification not independently verified.

flow "HumanPhysiologyDomainOntology" v1.0 {
  ontology:
    id: "human-physiology-domain-ontology"
    parent: "medical-domains"
    purpose: "Represent physiological structures, functions, regulatory mechanisms, measurements and evidence-backed relationships across human organ systems."

  types:
    OrganSystem: {id: string, name: string}
    AnatomicalStructure: {id: string, name: string, system_id: string?}
    PhysiologicalProcess: {id: string, name: string, system_id: string?, temporal_scale: string?}
    PhysiologicalVariable: {id: string, name: string, unit: string, reference_context: string?}
    RegulatoryMechanism: {id: string, kind: enum[negative_feedback, positive_feedback, feedforward, other], target: string}
    Measurement: {id: string, variable_id: string, value: number, unit: string, timestamp: datetime?, uncertainty: number?, method: string?, provenance: string}
    Observation: {id: string, description: string, provenance: string, timestamp: datetime?}
    Relationship: {id: string, subject: string, predicate: string, object: string, context: string?, confidence: number, evidence: string[]}

  predicates:
    part_of(structure: AnatomicalStructure, system: OrganSystem)
    performs(structure: AnatomicalStructure, process: PhysiologicalProcess)
    regulates(mechanism: RegulatoryMechanism, process: PhysiologicalProcess)
    influences(process: PhysiologicalProcess, variable: PhysiologicalVariable)
    measured_by(variable: PhysiologicalVariable, measurement: Measurement)
    interacts_with(a: OrganSystem, b: OrganSystem)
    supports(a: PhysiologicalProcess, b: PhysiologicalProcess)
    observed_in(process: PhysiologicalProcess, observation: Observation)

  constraints:
    - "All relationship endpoints must resolve to appropriately typed entities."
    - "Confidence must lie within [0, 1]."
    - "Measurements require units, provenance and a specified measurement context."
    - "Compare measurements only after validating unit compatibility and physiological context."
    - "Reference ranges depend on population, method and clinical context; do not treat them as universal constants."
    - "Regulation and influence do not automatically establish a quantified causal effect."
    - "Do not infer diagnosis, treatment or individual risk from ontology relationships alone."
    - "Do not assume interactions or regulatory links are transitive."

  inference:
    rule system_function:
      if part_of(structure, system) and performs(structure, process)
      then associated_process(system, process)
      confidence: "retain evidence and distinguish association from exclusive function"
    rule measurement_link:
      if influences(process, variable) and measured_by(variable, measurement) and valid(measurement)
      then measurement_relevant_to(measurement, process)
      confidence: "context-dependent; not proof of process causation"
    rule regulatory_trace:
      if regulates(mechanism, process) and influences(process, variable)
      then potentially_affects(mechanism, variable)
      confidence: "requires mechanistic or empirical corroboration"

  SEMANTIC_EQUIVALENCE:
    - "Map accepted physiological terms to versioned biomedical vocabularies when available."
    - "Distinguish anatomical identity, functional similarity and related physiological processes."
    - "Preserve measurement units, population context, temporal state and method."

  CONFIDENCE:
    range: [0,1]
    factors: [measurement_quality, evidence_strength, population_applicability, source_reliability, model_assumptions, reproducibility]
    policy: "Record uncertainty and dependencies; never increase confidence solely by chaining inferences."

  VALIDATION:
    - "Verify entity types, units, temporal context, measurement methods and provenance."
    - "Check biological plausibility and consistency with validated physiological constraints."
    - "Flag conflicting observations and retain alternative interpretations."
    - "Separate normative reference data from individual patient observations."

  FLOW_HASH:
    algorithm: "SHA-256"
    input: "canonicalised ontology version, typed assertions, rules and provenance"
    note: "Compute at execution; no hash value is claimed here."

  UPDATE_MODEL:
    strategy: "versioned, provenance-preserving incremental update"
    steps: [ingest, normalise, validate, compare, reconcile, recompute_inferences, publish]
    rollback: true

  AI_CONSUMPTION:
    representation: "typed physiology knowledge graph with evidence-backed relationships"
    outputs: [entity_links, physiological_relations, measurement_context, uncertainty_annotations, inference_traces, provenance_records]
    safeguards: [no_unsupported_diagnoses, preserve_units_and_context, distinguish_association_from_causation, human_review_for_clinical_use]
}

END FLOW ALGEBRA