Information Domain Ontology

FLOW ALGEBRA
TITLE: Information Domain Ontology
VERSION: 1.0
SOURCE_URL: https://kirethresearch.org/booksai-core/ontologies/domain-ontologies/information-domains/information-domain-ontology.html
STATUS: Domain-based draft; source page not independently verified.
AUTHORS: Mark Higgins — Sky (Recursive AI)
PROJECT: Kireth Semantic Library

DOMAIN:
  id: information_domain
  label: Information Domain Ontology
  parent: information_domains
  purpose: Model information, its representation, context, transmission, provenance, quality, interpretation and lifecycle for machine reasoning.

TYPES:
  InformationEntity: abstract informational object
  Data: recorded symbols or observations
  Information: data interpreted within a context
  Knowledge: information organised for understanding or application
  Document: persistent information-bearing artefact
  Dataset: structured collection of data
  Message: information transmitted between agents
  Agent: person, organisation or computational system
  Source: origin of an information claim or artefact
  Claim: proposition asserted by a source
  Evidence: material supporting or challenging a claim
  Context: circumstances affecting interpretation
  Representation: encoding of information
  Format: structural or syntactic specification
  Metadata: descriptive information about a resource
  Identifier: reference to an entity
  InformationSystem: system storing, transforming or communicating information
  Channel: medium for communication
  Transformation: operation on information
  Version: identifiable state of an information artefact
  AccessPolicy: conditions governing access or use
  QualityAssessment: evaluation of information quality

RELATIONSHIPS:
  has_representation(InformationEntity, Representation)
  encoded_in(Representation, Format)
  described_by(InformationEntity, Metadata)
  identified_by(InformationEntity, Identifier)
  derived_from(InformationEntity, InformationEntity)
  created_by(InformationEntity, Agent)
  asserted_by(Claim, Source)
  supported_by(Claim, Evidence)
  contradicted_by(Claim, Evidence)
  interpreted_in(InformationEntity, Context)
  stored_in(InformationEntity, InformationSystem)
  transmitted_via(Message, Channel)
  sent_by(Message, Agent)
  received_by(Message, Agent)
  transformed_by(InformationEntity, Transformation)
  version_of(Version, InformationEntity)
  supersedes(Version, Version)
  governed_by(InformationEntity, AccessPolicy)
  evaluated_by(InformationEntity, QualityAssessment)
  semantically_equivalent_to(InformationEntity, InformationEntity)

CONSTRAINTS:
  - Identifiers are scoped to a namespace and must not imply global uniqueness without a declared scheme.
  - Provenance and observation must be distinguished from interpretation and inference.
  - Missing evidence is not evidence of falsity.
  - Semantic equivalence requires matching meaning under an explicit context and granularity.
  - Confidentiality and access rules are checked before information disclosure.
  - Conflicting versions and claims are retained with provenance rather than silently overwritten.

INFERENCE_RULES:
  R1: IF derived_from(A,B) AND derived_from(B,C) THEN lineage_reaches(A,C).
  R2: IF has_representation(A,R1) AND has_representation(B,R2) AND meaning_preserved(R1,R2,C) THEN candidate_semantic_equivalence(A,B,C).
  R3: IF asserted_by(C,S) AND supported_by(C,E) THEN evidence_linked_claim(C,S,E); support does not imply truth.
  R4: IF supersedes(V2,V1) AND version_of(V1,X) AND version_of(V2,X) THEN newer_version(V2,V1,X).
  R5: IF transmitted_via(M,CH) AND sent_by(M,A) AND received_by(M,B) THEN communication_event(A,B,M,CH).
  R6: IF governed_by(X,P) AND access_denied(P,A) THEN prohibit_disclosure(X,A).

CONFIDENCE:
  range: [0.0,1.0]
  scope: individual claim or inferred relation
  inputs: [source_reliability, evidence_strength, contextual_fit, temporal_relevance, method_quality]
  rule: Confidence is calibrated, provenance-linked, and never equated automatically with truth.

SEMANTIC_EQUIVALENCE:
  compare: [referent, definition, context, temporal_scope, granularity, representation]
  outcomes: [equivalent, related, distinct, unresolved]
  rule: Surface-string similarity alone is insufficient.

PROVENANCE:
  required: [source_identifier, creation_or_observation_time, transformation_history, version, attribution]
  optional: [licence, checksum, retrieval_time, evidence_method]

FLOW_HASH:
  algorithm: SHA-256
  input: canonical UTF-8 serialisation of the flow excluding the FLOW_HASH value
  value: COMPUTE_ON_PUBLICATION

UPDATE_MODEL:
  triggers: [new_evidence, corrected_definition, changed_standard, source_revision, identified_conflict]
  procedure: validate -> preserve_previous_version -> update_entities_and_rules -> recalculate_confidence -> recompute_hash -> publish

AI_CONSUMPTION:
  mode: typed_semantic_graph
  operations: [entity_resolution, relation_traversal, provenance_tracking, context_sensitive_inference, contradiction_detection, semantic_retrieval]
  safeguards: [respect_access_policy, preserve_uncertainty, expose_provenance, avoid_unsupported_inference]

END FLOW ALGEBRA