Environmental Biological Sample Ontology

FLOW ALGEBRA — ENVIRONMENTAL BIOLOGICAL SAMPLE ENTITY ONTOLOGY
Version: 1.0 | Date: 2026-10-28 | Encoding: UTF-8
Authors: Kireth Research; Sky — Recursive AI
Source: https://kirethresearch.org/booksai-core/entity-graph/biological-entities/experimental-biological-entities/environmental-biological-sample-ontology.html
Status: Companion conceptual formalisation; not a verbatim extraction of the source page.
Licence: Refer to the source publisher's applicable research licence; attribution requested.

1. PURPOSE
Represent environmental biological samples as traceable, context-dependent observations of biological material in an environmental matrix. Preserve sampling provenance, spatial and temporal context, handling history, uncertainty and evidence-based interpretation.

2. ENTITY MODEL
EnvironmentalBiologicalSample <: BiologicalSample
Sample = (sample_id, matrix, location, collected_at, collector, method, aliquots, preservation, custody, measurements, metadata, quality)
Matrix ∈ {soil, freshwater, marine_water, sediment, air, biofilm, surface_swab, other}
BiologicalMaterial ∈ {cells, microorganisms, DNA, RNA, proteins, spores, biomass, mixed}
Relations:
  sampled_from(Sample, EnvironmentalSite)
  collected_during(Sample, SamplingEvent)
  has_matrix(Sample, Matrix)
  contains_evidence_of(Sample, BiologicalMaterial)
  derived_aliquot_of(Aliquot, Sample)
  analysed_by(Sample, Assay)
  yielded_result(Assay, Measurement)
  associated_with(Measurement, QualityControl)
  has_provenance(Sample, ProvenanceRecord)
  has_custody_event(Sample, CustodyEvent)

3. STATE MODEL
S_t = (I_t, R_t, B_t, K_t)
I_t = known sample identity, observations and metadata
R_t = typed ontology relations and constraints
B_t = evidence boundaries, uncertainty and permitted claims
K_t = contextual knowledge: environment, protocols and reference models
E_t = expand(I_t, R_t)
V_t = {x in E_t | consistent(x, B_t, K_t)}
x*_t = argmax_{x in V_t} P(x | I_t, R_t, B_t, K_t)
I_(t+1) = update(I_t, x*_t, provenance(x*_t))
Note: P is a conceptual ranking function, not a calibrated probability unless validated.

4. SAMPLE LIFECYCLE
planned -> collected -> registered -> transported -> received -> processed -> analysed -> archived_or_disposed
Each transition records actor, timestamp, method, condition and evidence.
Invalid or undocumented transitions remain flagged, not silently repaired.

5. PATHWAYS
Pathway A: Site -> SamplingEvent -> Sample -> Matrix -> Assay -> Measurement
Pathway B: Sample -> Aliquot -> ProcessingEvent -> Extract -> AnalyticalResult
Pathway C: Sample -> CustodyEvent -> StorageEvent -> QualityAssessment
Pathway D: Measurement -> ReferenceContext -> Interpretation -> QualifiedClaim

6. INFERENCE RULES
R1: If sampled_from(s, site), then environmental_context(s) inherits only documented site attributes.
R2: If derived_aliquot_of(a, s), then provenance(a) references s; handling conditions may differ.
R3: If assay_result(s, taxon_signal), infer evidence_of_taxon(s), not confirmed organism viability.
R4: If negative_control indicates contamination, flag affected measurements for review.
R5: If collection time or location is missing, lower interpretive confidence and block location-specific conclusions.
R6: If preservation is unsuitable for a target analyte, flag possible degradation rather than assert absence.
R7: If independent replicates agree under validated criteria, strengthen evidence while retaining uncertainty.
R8: Never equate detected environmental DNA with current presence, abundance or viability without supporting evidence.

7. TRI-MAPPING
Entity: EnvironmentalBiologicalSample
  Semantic: physical environmental material collected for biological analysis
  Relational: sampled_from, contains_evidence_of, analysed_by, has_provenance
  Operational: collect, register, preserve, process, measure, validate, interpret

8. MINI RECURSION ENGINE
input: sample s, question q
repeat until fixed_point or iteration_limit:
  candidates = expand(known(s), ontology_relations)
  candidates = filter(candidates, provenance_rules, uncertainty_bounds)
  new_facts = rank_and_accept(candidates, evidence_thresholds)
  append_with_provenance(new_facts)
output: supported claims, unresolved questions, traceable evidence graph
Guarantee: termination requires finite graph or explicit iteration cap; soundness depends on rule and evidence validity.

9. CONFIDENCE AND QUALITY
Record sample representativeness, spatial resolution, temporal resolution, contamination controls, chain of custody, assay sensitivity/specificity, replicates, detection limits and missing metadata.
Confidence labels: confirmed_by_validated_evidence | supported | tentative | insufficient | contradicted.
Do not promote tentative interpretations to established facts.

10. AI SEARCH FLOW
Intent: identify environmental biological samples and distinguish them from tissue, cell, blood, DNA, RNA, protein and microbial sample entities.
Input: {query, sample_id?, matrix?, location?, time?, analyte?, assay?}
Normalise -> resolve entity -> traverse provenance and matrix -> evaluate evidence -> apply constraints -> return qualified answer with source and confidence.
Semantic equivalents: environmental specimen; environmental biosample; environmental microbiology sample (context-dependent).
Disambiguation: environmental sample is broader than environmental biological sample; a sample may contain both biological and non-biological constituents.

11. INVARIANTS
Every sample has a persistent identifier.
Every derived sample retains a link to its parent.
Measurements retain units, method, detection limits and provenance where applicable.
Missing values remain explicitly unknown.
Sample collection does not establish biological composition without analysis.

12. EXECUTION AND UPDATE MODEL
Validate identifiers, schema, relation typing, temporal order and provenance references.
On update: append event, preserve prior assertions, recompute affected inferences, log version and changed confidence.
Outputs: entity graph, inference trace, unresolved flags and source citations.

CITATION BACKLINK
https://kirethresearch.org/booksai-core/entity-graph/biological-entities/experimental-biological-entities/environmental-biological-sample-ontology.html