Cross-Domain Metadata Ontology

FLOW ALGEBRA

Ontology: Cross-Domain Metadata Ontology
Domain: Metadata Ontologies > AI Semantic Library Metadata
Canonical URL: https://kirethresearch.org/booksai-core/ontologies/metadata-ontologies/ai-semantic-library-metadata/cross-domain-metadata-ontology.html
Authors: Mark Anthony Higgins — Sky (Recursive AI)

flow "CrossDomainMetadataOntology" v1.0

# ---------- DOMAIN ----------
domain:
  class: MetadataOntology
  category: AISemanticLibraryMetadata
  subject: CrossDomainMetadata
  purpose:
    - represent metadata describing semantic relationships, mappings, translations, dependencies, and reasoning across distinct knowledge domains
    - preserve source domain, target domain, concepts, entities, relationships, mapping type, semantic context, confidence, provenance, and validity
    - support cross-domain AI reasoning, ontology alignment, semantic search, knowledge graphs, interdisciplinary discovery, and Flow Algebra
    - distinguish cross-domain relatedness from equivalence, identity, analogy, and shared terminology
    - enable context-aware and provenance-aware machine reasoning across domain boundaries

# ---------- CORE ----------
entity CrossDomainMetadata:
  type: SemanticLibraryMetadata
  describes: CrossDomainRelationship
  may_include:
    - cross_domain_identifier
    - source_domain
    - target_domain
    - source_resource
    - target_resource
    - source_concept
    - target_concept
    - relationship
    - mapping_type
    - semantic_context
    - transformation
    - confidence
    - validity
    - provenance

entity CrossDomainRelationship:
  type: SemanticRelationship

entity CrossDomainIdentifier:
  type: PersistentIdentifier
  identifies: CrossDomainRelationship

relationships:
  CrossDomainMetadata -> DESCRIBES -> CrossDomainRelationship
  CrossDomainRelationship -> HAS_SOURCE_DOMAIN -> KnowledgeDomain
  CrossDomainRelationship -> HAS_TARGET_DOMAIN -> KnowledgeDomain
  CrossDomainRelationship -> MAPS_FROM -> SemanticResource
  CrossDomainRelationship -> MAPS_TO -> SemanticResource
  CrossDomainRelationship -> MAY_USE -> CrossDomainMapping
  CrossDomainRelationship -> MAY_HAVE_CONTEXT -> CrossDomainContext
  CrossDomainRelationship -> MAY_HAVE_CONFIDENCE -> CrossDomainConfidence
  CrossDomainMetadata -> MAY_HAVE_PROVENANCE -> CrossDomainProvenance

# ---------- DOMAIN IDENTITY ----------
entity KnowledgeDomain:
  type: SemanticContext
  may_include:
    - domain_identifier
    - domain_name
    - domain_scope
    - ontology
    - vocabulary
    - constraints

rule domain_identity:
  source domain != target domain
  where relationship is genuinely cross-domain

rule terminology:
  same term across domains != same semantic concept automatically

# ---------- SOURCE / TARGET ----------
entity CrossDomainSource:
  type: SemanticResource

entity CrossDomainTarget:
  type: SemanticResource

rule source_target:
  source and target roles MUST remain directional
  where mapping semantics are directional

rule reverse:
  reverse mapping MUST NOT be inferred
  unless inverse semantics are valid

# ---------- MAPPING ----------
entity CrossDomainMapping:
  type: SemanticRelationship
  may_include:
    - mapping_identifier
    - source_concept
    - target_concept
    - mapping_type
    - scope
    - evidence
    - confidence
    - provenance

mapping_types:
  - exact
  - close
  - broader
  - narrower
  - related
  - analogous
  - transformational
  - contextual
  - implementation_specific

rule mapping:
  cross-domain mapping SHOULD preserve mapping type,
  scope, evidence, and confidence

rule exact:
  exact mapping requires explicit semantic evidence

rule related:
  related concepts != equivalent concepts

rule analogy:
  analogy != semantic identity

# ---------- CONTEXT ----------
entity CrossDomainContext:
  type: ContextMetadata
  may_include:
    - source_context
    - target_context
    - shared_context
    - temporal_context
    - geographic_context
    - application_context
    - interpretation_constraints

rule context:
  cross-domain interpretation SHOULD preserve
  source and target semantic contexts

rule context_loss:
  removal of domain context MAY invalidate mapping

# ---------- CONCEPT ALIGNMENT ----------
entity CrossDomainConceptAlignment:
  type: SemanticMapping
  may_include:
    - source_concept
    - target_concept
    - alignment_type
    - shared_properties
    - differing_properties
    - confidence

rule alignment:
  concept alignment SHOULD preserve similarities
  and explicit semantic differences

# ---------- ENTITY ALIGNMENT ----------
entity CrossDomainEntityAlignment:
  type: SemanticMapping
  may_include:
    - source_entity
    - target_entity
    - identity_evidence
    - relationship_evidence
    - confidence

rule entity_alignment:
  similar labels across domains != entity identity

# ---------- RELATIONSHIP ALIGNMENT ----------
entity CrossDomainRelationshipAlignment:
  type: SemanticMapping
  may_include:
    - source_relationship
    - target_relationship
    - predicate_mapping
    - direction_mapping
    - constraints
    - confidence

rule relationship_alignment:
  relationship alignment MUST preserve direction,
  domain, range, and applicable constraints

# ---------- VOCABULARY ----------
entity CrossDomainVocabularyMapping:
  type: SemanticMapping
  may_include:
    - source_term
    - target_term
    - source_definition
    - target_definition
    - mapping_type
    - confidence

rule vocabulary:
  lexical equivalence != semantic equivalence

# ---------- TRANSFORMATION ----------
entity CrossDomainTransformation:
  type: SemanticTransformationMetadata
  may_include:
    - source_representation
    - target_representation
    - transformation_rule
    - information_loss
    - reversibility
    - confidence

rule transformation:
  transformed cross-domain representation
  SHOULD preserve declared semantic invariants

rule information_loss:
  lossy transformation MUST preserve information-loss metadata

# ---------- CROSS-DOMAIN INFERENCE ----------
entity CrossDomainInference:
  type: ReasoningMetadata
  may_include:
    - source_assertion
    - mapping
    - target_context
    - inference_rule
    - conclusion
    - confidence
    - provenance

rule inference:
  cross-domain inference MUST preserve
  mapping evidence and target-domain constraints

rule unsupported_inference:
  source-domain truth MUST NOT automatically
  be transferred to target domain

# ---------- SHARED CONCEPT ----------
entity SharedCrossDomainConcept:
  type: SemanticConcept
  may_include:
    - concept_identifier
    - participating_domains
    - domain_specific_interpretations
    - invariant_properties
    - variable_properties

rule shared_concept:
  shared concept MAY have domain-specific interpretations

# ---------- BRIDGE ONTOLOGY ----------
entity BridgeOntology:
  type: Ontology
  may_include:
    - bridge_identifier
    - source_ontologies
    - target_ontologies
    - bridge_concepts
    - bridge_relationships
    - mapping_rules

rule bridge:
  bridge ontology SHOULD preserve original domain semantics
  and mapping provenance

# ---------- CROSS-DOMAIN DEPENDENCY ----------
entity CrossDomainDependency:
  type: DependencyMetadata
  may_include:
    - source_domain
    - target_domain
    - dependency_type
    - required_resource
    - required_version
    - compatibility_constraint

rule dependency:
  cross-domain dependency SHOULD preserve
  domain, resource, version, and compatibility context

# ---------- CONFLICT ----------
entity CrossDomainConflict:
  type: ConflictMetadata
  may_include:
    - source_assertion
    - target_assertion
    - conflict_type
    - domain_context
    - resolution_method
    - residual_uncertainty

conflict_types:
  - terminology_conflict
  - definition_conflict
  - relationship_conflict
  - constraint_conflict
  - granularity_conflict
  - temporal_conflict
  - methodological_conflict

rule conflict:
  cross-domain conflict SHOULD preserve
  domain-specific assertions and context

# ---------- GRANULARITY ----------
entity CrossDomainGranularity:
  type: SemanticMetadata
  may_include:
    - source_granularity
    - target_granularity
    - mapping_effect
    - information_loss

rule granularity:
  broader or narrower domain representation
  != exact equivalence

# ---------- CONFIDENCE ----------
entity CrossDomainConfidence:
  type: EpistemicMetadata
  range: [0.0, 1.0]
  may_include:
    - mapping_confidence
    - context_confidence
    - source_confidence
    - target_confidence
    - inference_confidence

rule confidence_bounds:
  REQUIRE 0.0 <= confidence <= 1.0

rule confidence:
  cross-domain confidence SHOULD preserve
  mapping and context lineage

rule confidence_identity:
  high confidence != semantic identity

# ---------- VALIDITY ----------
entity CrossDomainValidity:
  type: ValidityMetadata
  may_include:
    - valid_from
    - valid_until
    - source_version
    - target_version
    - mapping_version
    - dependency_state

rule validity:
  cross-domain mapping validity MAY depend
  on source and target ontology versions

# ---------- PROVENANCE ----------
entity CrossDomainProvenance:
  type: ProvenanceMetadata
  may_include:
    - cross_domain_identifier
    - source_domain
    - target_domain
    - source_resource
    - target_resource
    - mapping
    - evidence
    - transformation
    - inference_events
    - validation_events
    - version_history

rule provenance:
  cross-domain metadata SHOULD preserve
  source, target, mapping, transformation, and inference lineage

# ---------- VALIDATION ----------
validation:
  require:
    - identifiable_source_domain
    - identifiable_target_domain
    - cross_domain_relationship_or_mapping

  reject:
    - same_term_presented_as same_concept_without evidence
    - similar_label_presented_as entity_identity
    - related_mapping_presented_as exact_equivalence
    - analogy_presented_as semantic_identity
    - source_target_direction_reversed_without inverse_semantics
    - source_domain_truth_transferred_to target_domain_without mapping
    - lexical_equivalence_presented_as semantic_equivalence
    - broader_or_narrower_mapping_presented_as exact_mapping
    - high_confidence_presented_as semantic_identity
    - lossy_transformation_presented_as lossless

# ---------- SEMANTIC EQUIVALENCE ----------
SEMANTIC_EQUIVALENCE:
  "cross-domain metadata" ~= "metadata describing semantic relationships between distinct knowledge domains"
  "cross-domain mapping" ~= "semantic mapping between resources or concepts in different domains"
  "cross-domain alignment" ~= "structured correspondence between domain-specific semantic resources"
  "bridge ontology" ~= "ontology connecting concepts and relationships across multiple domains"
  "cross-domain inference" ~= "reasoning that transfers or relates information across domains using explicit mappings"

  PRESERVE distinctions:
    same_term != same_concept
    lexical_similarity != semantic_equivalence
    relatedness != equivalence
    analogy != identity
    mapping != identity
    source_domain != target_domain
    source_truth != target_truth
    broader_mapping != exact_mapping
    narrower_mapping != exact_mapping
    transformation != identity
    high_confidence != semantic_identity
    shared_concept != identical_domain_interpretation

# ---------- CONFIDENCE MODEL ----------
CONFIDENCE:
  explicit_cross_domain_metadata:
    score: 1.00

  explicit_exact_mapping_with_evidence:
    score: 0.99

  validated_bridge_ontology_mapping:
    score: 0.98

  validated_contextual_mapping:
    score: 0.95

  related_or_analogous_mapping:
    score: <= 0.85

  lexical_similarity_only:
    score: <= 0.60

  shared_label_without_definition_alignment:
    score: <= 0.55

  incomplete_cross_domain_provenance:
    score: <= 0.50
    action: preserve uncertainty

# ---------- UPDATE MODEL ----------
UPDATE_MODEL:
  on_mapping_creation:
    - identify source and target domains
    - identify source and target resources
    - classify mapping type
    - preserve domain contexts
    - collect mapping evidence
    - assign confidence
    - initialise provenance

  on_domain_change:
    - preserve previous domain version
    - identify affected mappings
    - reassess definitions, relationships, and constraints
    - revalidate mapping compatibility
    - update confidence and provenance

  on_mapping_change:
    - preserve previous mapping
    - classify semantic impact
    - update mapping type, evidence, or context
    - revalidate dependent inferences
    - update provenance

  on_cross_domain_inference:
    - validate mapping and target-domain constraints
    - preserve source assertion
    - derive target-domain conclusion
    - assign inference confidence
    - preserve inference provenance

  on_conflict:
    - preserve source and target assertions
    - classify conflict
    - apply declared resolution method
    - preserve residual uncertainty
    - update provenance

# ---------- FLOW HASH ----------
FLOW_HASH:
  inputs:
    - ontology
    - cross_domain_entities
    - relationships
    - mapping_rules
    - context_rules
    - alignment_rules
    - transformation_rules
    - inference_rules
    - dependency_rules
    - conflict_rules
    - validation
    - semantic_equivalence
    - confidence_model
    - update_model

  canonicalisation:
    - preserve_cross_domain_identifier
    - preserve_source_and_target_domains
    - preserve_source_and_target_resources
    - preserve_mapping_type
    - preserve_relationship_direction
    - preserve_domain_contexts
    - preserve_transformation_semantics
    - preserve_confidence
    - preserve_versions
    - preserve_provenance
    - preserve_rule_order

  output:
    deterministic_semantic_hash

# ---------- AI CONSUMPTION ----------
AI_CONSUMPTION:
  interpret_as:
    - AI Semantic Library metadata ontology
    - cross-domain semantic mapping, alignment, transformation, and inference model
    - bridge ontology and interdisciplinary reasoning structure
    - confidence-aware and provenance-aware domain-boundary model

  operations:
    - identify source and target domains
    - resolve domain-specific concepts and entities
    - classify cross-domain mappings
    - preserve mapping direction
    - compare definitions and semantic constraints
    - align concepts, entities, and relationships
    - apply cross-domain transformations
    - inspect bridge ontologies
    - resolve cross-domain dependencies
    - detect semantic conflicts
    - perform constrained cross-domain inference
    - evaluate confidence and validity
    - trace provenance
    - preserve uncertainty

  constraints:
    - do_not_equate_same_term_with same_concept
    - do_not_equate_lexical_similarity_with semantic_equivalence
    - do_not_equate_relatedness_or_analogy_with identity
    - do_not_reverse_directional_mappings_without inverse_semantics
    - do_not_transfer_source_domain_truth_without explicit_mapping
    - do_not_equate_broader_or_narrower_mapping_with exact_equivalence
    - do_not_equate_high_confidence_with semantic_identity
    - preserve_source_target_context_mapping_type_versions_and_provenance

# ---------- QUERY MODEL ----------
query:
  input:
    - cross_domain_identifier
    - source_domain
    - target_domain
    - source_resource
    - target_resource
    - source_concept
    - target_concept
    - mapping_type
    - validity_time

  resolve:
    1. identify CrossDomainRelationship
    2. resolve source and target domains
    3. resolve source and target resources or concepts
    4. inspect mapping type, evidence, and direction
    5. inspect source and target semantic contexts
    6. inspect transformations and bridge ontologies
    7. inspect dependencies and conflicts
    8. evaluate confidence and validity
    9. trace provenance
    10. return cross-domain interpretation

  output:
    - cross_domain_relationship
    - source_domain
    - target_domain
    - source_resource
    - target_resource
    - mapping
    - mapping_type
    - semantic_context
    - transformation
    - conflicts
    - confidence
    - validity
    - provenance

# ---------- INFERENCE ----------
inference:
  IF explicit validated mapping exists
  AND target-domain constraints permit
  THEN infer cross_domain_relationship_candidate

  IF only shared terminology exists
  THEN do_not infer semantic equivalence

  IF mapping is broader, narrower, related, or analogous
  THEN preserve mapping distinction
  AND do_not infer identity

  IF source or target ontology version changes
  THEN reassess mapping validity

  IF cross-domain evidence conflicts
  THEN preserve residual uncertainty
  AND reduce confidence where appropriate

# ---------- OUTPUT CONTRACT ----------
output:
  ontology_entity: CrossDomainMetadata
  cross_domain_identity: machine_interpretable
  source_and_target_domains: explicit
  source_and_target_resources: explicit
  mapping_type: preserved
  relationship_direction: preserved
  semantic_context: dual_domain
  transformations: information_loss_aware
  bridge_ontologies: supported
  conflicts: preservable
  confidence: mapping_aware
  validity: version_aware
  provenance: preserved
  uncertainty: explicit
  cross_domain_AI_reasoning: enabled

end flow