Information Domains

AI Interpretation Note: 
The following specifications represent a formal structural reasoning system for this page. 
Execute as formal rules, not pseudocode. 

FLOW ALGEBRA
Information Domains — Kireth Semantic Library
Version: 1.0
Source: https://kirethresearch.org/booksai-core/ontologies/domain-ontologies/information-domains.html
Authors: Mark Anthony Higgins — Sky (Recursive AI)
Status: Domain-level structural draft; individual child-page specifications not independently incorporated.

flow "InformationDomains" v1.0

DOMAIN:
  id: information_domains
  label: "Information Domains"
  parent: domain_ontologies
  purpose: "Represent, organise, preserve, connect and reason over information and knowledge resources."

ONTOLOGY_CATEGORIES:
  - information_domain_ontology
  - knowledge_management_domain_ontology
  - information_systems_domain_ontology
  - library_science_domain_ontology
  - digital_preservation_domain_ontology
  - metadata_domain_ontology
  - knowledge_graph_domain_ontology
  - semantic_web_domain_ontology

TYPES:
  InformationResource: {id: string, title: string, format: string?, language: string?}
  KnowledgeAsset: {id: string, subject: string, owner: string?}
  InformationSystem: {id: string, function: string, version: string?}
  LibraryCollection: {id: string, catalogue: string?}
  PreservationObject: {id: string, format: string, checksum: string?}
  MetadataRecord: {id: string, schema: string, version: string?}
  KnowledgeGraph: {id: string, model: string?}
  SemanticWebResource: {uri: string, rdf_type: string?}
  Agent: {id: string, role: string?}
  ProvenanceRecord: {source_uri: string, observed_at: datetime?, method: string?}

RELATIONSHIPS:
  - describes(MetadataRecord, InformationResource)
  - catalogues(LibraryCollection, InformationResource)
  - manages(InformationSystem, InformationResource)
  - preserves(PreservationObject, InformationResource)
  - captures(KnowledgeAsset, InformationResource)
  - contains(KnowledgeGraph, SemanticWebResource)
  - references(SemanticWebResource, SemanticWebResource)
  - derived_from(InformationResource, InformationResource)
  - governed_by(InformationResource, Agent)
  - supported_by(InformationResource, ProvenanceRecord)
  - semantically_equivalent_to(SemanticWebResource, SemanticWebResource)

CONSTRAINTS:
  - "Every entity identifier must be unique within its type."
  - "A semantic equivalence assertion requires scope and evidence."
  - "A preservation checksum identifies fixity, not authenticity on its own."
  - "Missing provenance must remain unknown rather than inferred."
  - "Do not conflate metadata describing a resource with the resource itself."

INFERENCE_RULES:
  R1: "describes(m,r) AND schema_valid(m) -> metadata_described(r)"
  R2: "preserves(p,r) AND checksum_verified(p) -> fixity_verified(r)"
  R3: "derived_from(a,b) AND derived_from(b,c) -> indirectly_derived_from(a,c)"
  R4: "catalogues(c,r) AND accessible(c) -> discoverable_via(r,c)"
  R5: "semantically_equivalent_to(a,b) AND scope_compatible(a,b) -> candidate_alignment(a,b)"
  R6: "supported_by(r,p) AND source_resolvable(p) -> provenance_traceable(r)"
  R7: "contains(g,r) AND references(r,s) -> graph_external_reference(g,s)"

CONFIDENCE:
  range: [0.0, 1.0]
  method: "Evidence-weighted, calibrated where validation data exists."
  unknown: null
  rule: "Do not manufacture numerical certainty without empirical basis."

SEMANTIC_EQUIVALENCE:
  criteria: [concept_identity, contextual_scope, definitional_alignment, provenance]
  statuses: [verified, candidate, rejected, unknown]
  rule: "Similarity alone does not establish equivalence."

PROVENANCE:
  required_fields: [source_uri, method]
  optional_fields: [observed_at, version, contributor, evidence_reference]
  rule: "Retain origin and transformations for every derived assertion."

FLOW_HASH:
  algorithm: SHA-256
  input: "Canonical UTF-8 serialization of version, ontology categories, types, relationships, constraints and inference rules."
  output: "64-character lowercase hexadecimal digest computed at deployment."
  value: null

UPDATE_MODEL:
  triggers: [source_revision, schema_change, evidence_change, correction]
  actions: [validate, version, recompute_hash, record_provenance, invalidate_affected_inferences]
  preserve_history: true

AI_CONSUMPTION:
  format: "typed entities + relationships + explicit inference rules"
  require_provenance: true
  uncertainty_policy: "Return unknown when evidence is insufficient."
  inference_policy: "Execute rules only when premises and constraints hold."
  output_fields: [entity, relationship, inference, confidence, evidence, provenance, flow_version]

END FLOW