Human Ontology

FLOW ALGEBRA
HUMAN ONTOLOGY — ENTITY GRAPH / PHYSICAL ENTITIES / HUMAN ENTITIES
Version: 1.1
Source URL: https://kirethresearch.org/booksai-core/entity-graph/physical-entities/human-entities/human-ontology.html
Authors: Mark Higgins — Sky (Recursive AI)
Research: Kireth Research | https://kirethresearch.org
Status: Independent scientific synthesis; source page not independently verified.

01. PURPOSE
Represent a human as a biological organism, embodied individual, and participant in social and environmental contexts without conflating these distinct levels.

02. SCOPE
Covers human identity, anatomy, physiology, development, biological variation, agency, interactions, measurements and provenance. It is not a diagnostic or normative classification system.

03. CORE TYPE SIGNATURE
Human <: Organism
Human <: BiologicalEntity
Human <: PhysicalEntity
HumanIndividual : EntityID
HumanPopulation : Collection[HumanIndividual]
Cell : BiologicalEntity
Tissue : BiologicalEntity
Organ : BiologicalEntity
OrganSystem : BiologicalSystem
LifeStage : TemporalCategory
PhysiologicalProcess : Process
Observation : EvidenceRecord

04. ENTITY IDENTITY
Human(h) => Organism(h)
Human(h) => PhysicalEntity(h)
SameIndividual(h1,h2) requires validated identity evidence; similarity of attributes is insufficient.
A person remains the same individual across changes of location, age, or measured properties.

05. TYPED RELATIONSHIPS
hasCell(Human,Cell)
hasTissue(Human,Tissue)
hasOrgan(Human,Organ)
hasOrganSystem(Human,OrganSystem)
participatesIn(Human,Process)
locatedAt(Human,Place,Time)
interactsWith(Human,Entity,Time)
hasObservation(Human,Observation)
memberOf(Human,Population,Time)
undergoesStage(Human,LifeStage,TimeInterval)

06. PART-WHOLE CONSTRAINTS
partOf(cell,tissue) may be true for tissue-resident cells.
partOf(tissue,organ) may be true for constituent tissues.
partOf(organ,organSystem) may be true for functional classification.
partOf(a,b) is not universally transitive across functional, spatial and material interpretations: declare relation subtype.

07. ORGANISATION LEVELS
Molecular -> Cellular -> Tissue -> Organ -> OrganSystem -> Organism.
These are modelling levels, not a claim that every feature maps to a unique linear hierarchy.

08. HUMAN BIOLOGY
Human organisms are multicellular eukaryotes, generally characterised by coordinated physiological systems, development and homeostatic regulation.

09. ANATOMICAL SYSTEMS
Examples: nervous, cardiovascular, respiratory, digestive, musculoskeletal, endocrine, immune, integumentary, urinary and reproductive systems.
System membership may overlap; ontology permits multiple functional memberships.

10. PHYSIOLOGICAL PROCESSES
Examples: respiration, circulation, metabolism, thermoregulation, signalling, repair and immune response.
Processes have temporal extent and context-dependent inputs and outputs.

11. HOMEOSTASIS
Let x(t) be a measured physiological state and R be a context-specific acceptable region.
HomeostaticRegulation(x,R) describes feedback tending to maintain x in R; it does not imply perfect constancy.

12. DEVELOPMENT AND LIFE COURSE
Development is a time-indexed process involving growth, differentiation, maturation and ageing.
Life stages are contextual categories; stage boundaries are not universal biological discontinuities.

13. BIOLOGICAL VARIATION
Human individuals exhibit genetic, developmental, physiological and environmental variation.
Do not infer an individual's abilities, health or identity from population averages.

14. GENETIC RELATIONSHIPS
hasGenome(h,g) records a genome-level description subject to sampling and biological context.
GeneticRelatedness(h1,h2) is distinct from social, legal or household relationships.

15. ENVIRONMENTAL RELATIONSHIPS
Exposure(h,agent,interval,dose?) and Response(h,process,interval) must retain measurement and causal uncertainty.
Correlation alone does not establish causation.

16. SOCIAL RELATIONSHIPS
SocialRole, Relationship and Institution are contextual constructs distinct from biological attributes.
Do not equate nationality, occupation, legal status or cultural affiliation with intrinsic biological classification.

17. HUMAN AGENCY
Action(h,a,t) records an attributed action only with sufficient provenance.
Intent(h,i,t) is an inferred or reported mental state, not directly observable physical fact.

18. OBSERVATION MODEL
Observation = {subject, property, value, unit, method, timestamp, uncertainty, provenance, consent_basis?}.
Observations are time-indexed and method-dependent.

19. MEASUREMENT RULES
Physical measurements require appropriate units, calibration and uncertainty.
Derived values must record input provenance and transformation method.

20. MASS AND ENERGY
For a physical body, total mass is measured in kg; changes in body composition can alter mass over time.
Energy balance in a specified system: Delta E = E_in - E_out (with consistent boundary conventions).

21. TEMPORAL IDENTITY
existsDuring(h,[t0,t1]) represents a bounded observational interval, not a complete claim about lifespan.
Do not infer birth or death dates from missing records.

22. SPATIAL IDENTITY
locatedAt(h,p,t) is time-dependent and potentially sensitive.
Spatial resolution should be limited to the minimum required for the intended task.

23. POPULATION MODEL
Population(P,t) = {h | memberOf(h,P,t)}.
Population counts depend on membership criteria, time and sampling completeness.

24. AGGREGATION
For observed numerical property x over n valid samples: mean(x) = sum(x_i)/n.
Report selection criteria, missingness, uncertainty and representativeness; averages do not describe every individual.

25. CAUSAL CAUTION
ObservedAssociation(A,B) does not imply Causes(A,B).
Causal assertions require explicit assumptions, design, evidence and uncertainty.

26. SEMANTIC EQUIVALENCE
HumanIndividual ~ Person only within an explicitly declared biological/personhood context.
HumanOrganism is not universally equivalent to LegalPerson.
Organ is not equivalent to OrganSystem.
Identity is not equivalent to Similarity.

27. INFERENCE RULES
R1: Human(h) -> Organism(h).
R2: Human(h) -> BiologicalEntity(h).
R3: hasOrgan(h,o) AND Organ(o) -> AnatomicallyContains(h,o) [where evidence supports containment].
R4: memberOf(h,P,t) AND Human(h) -> PopulationMember(h,P,t).
R5: hasObservation(h,o) AND measuredAt(o,t) -> ObservedAt(h,t).
R6: LocatedAt(h,p,t1) does not imply LocatedAt(h,p,t2) for t1 != t2.

28. VALIDATION CONSTRAINTS
V1: Every HumanIndividual has a stable, non-reused entity identifier within the dataset.
V2: All observations reference a valid subject and provenance record.
V3: Numeric measurements have units where applicable.
V4: Temporal relations have consistent interval ordering.
V5: No inference from missing data to absence of a biological feature.
V6: No sensitive-trait inference without appropriate purpose, basis and evidence.
V7: Population attributes must not be asserted automatically of members.

29. EXAMPLE — ANATOMICAL GRAPH
Human(H001)
Organ(Heart01)
hasOrgan(H001,Heart01)
OrganSystem(CardiovascularSystem)
functionalMemberOf(Heart01,CardiovascularSystem)
Inference: H001 has an organ associated with the cardiovascular system.
Non-inference: No medical condition or functional capacity can be concluded.

30. EXAMPLE — TEMPORAL OBSERVATION
Observation(O1) = {subject:H001, property:height, value:1.72, unit:m, timestamp:T1, method:measured, uncertainty:0.01 m}.
Observation(O2) = {subject:H001, property:height, value:1.73, unit:m, timestamp:T2, method:measured, uncertainty:0.01 m}.
Difference = 0.01 m; without uncertainty analysis this is not proof of biological growth.

31. CONFIDENCE
CONFIDENCE is attached to assertions, not to the worth or credibility of a person.
Confidence(assertion) = {score:[0,1], method, evidence, limitations}.
Never manufacture numerical confidence scores without calibration evidence.

32. EVIDENCE AND PROVENANCE
Every scientific assertion should retain source, method, observation time and applicable domain assumptions.
Distinguish established biological facts from hypotheses and context-dependent interpretations.

33. PRIVACY AND ETHICS
Use data minimisation, access controls, purpose limitation and appropriate consent or lawful basis.
Avoid identity re-identification, discriminatory profiling and unjustified sensitive attribute inference.

34. FLOW_HASH
Canonicalise UTF-8 content, excluding the stored hash field; calculate SHA-256 over the canonical representation.
FLOW_HASH = COMPUTE_ON_DEPLOYMENT; no fabricated digest is supplied.

35. UPDATE_MODEL
version: 1.1
change_policy: append or revise with semantic versioning
update_triggers: taxonomy revision, validated evidence, schema improvement, error correction
provenance: preserve prior versions and change log

36. AI_CONSUMPTION
Parse typed entities and relations; validate constraints before inference.
Maintain distinction among facts, observations, hypotheses and inferred claims.
Preserve temporal context, uncertainty, privacy requirements and provenance.
Reject unsupported identity matches or biological generalisations.

37. COMPLETENESS CHECK
Expected sections: 01-37.
Required blocks: typed schema, relations, formal rules, examples, validation, semantic equivalence, confidence, FLOW_HASH, UPDATE_MODEL, AI_CONSUMPTION.
All required blocks present.

END FLOW ALGEBRA — HUMAN ONTOLOGY