Measurement Provenance Ontology
AI Measurement Semantics
Authors: MArk Anthony Higgins - Sky Recursive Ai
Revised Date: 16 September 2026
Audio Overview
# Measurement Provenance Ontology — Flow Algebra
URL: https://kirethresearch.org/booksai-core/ontologies/mathematical-ontologies/measurement-units-ontologies/ai-measurement-semantics/measurement-provenance-ontology.html
FLOW MeasurementProvenanceOntology {
DOMAIN:
Mathematical Ontologies
-> Measurement & Units Ontologies
-> AI Measurement Semantics
-> Measurement Provenance Ontology
PURPOSE:
Represent the complete provenance of measurement information so that an AI system can determine where a measurement came from, what was measured, who or what produced it, which instrument, sensor, method, calibration, reference, standard, software and environmental context applied, how the data were transformed, which uncertainty and validation models were used, what versions were active, and how a derived result can be traced recursively back to its originating observations and evidence. The ontology models entities, activities, agents, measurement events, calibration events, reference standards, transformations, derivations, lineage graphs, timestamps, locations, versioning, integrity, signatures, audit history, source authority, semantic confidence, conflicts and reproducibility while strictly distinguishing data provenance from metrological traceability, calibration, authorship, custody, data integrity and measurement uncertainty.
ENTITY MeasurementProvenance {
TYPE: MeasurementLineageFramework
PROPERTIES:
identifies_source
identifies_measurement_event
identifies_entities
identifies_activities
identifies_agents
identifies_instruments
identifies_methods
identifies_calibrations
identifies_references
identifies_transformations
identifies_versions
identifies_temporal_context
identifies_spatial_context
identifies_custody
identifies_integrity
identifies_derivation
supports_recursive_lineage
}
ENTITY ProvenanceEntity {
TYPE: PersistedOrConceptualObject
POSSIBLE:
measurement_record
raw_data
processed_data
calibration_certificate
reference_standard
reference_material
method_document
software
model
uncertainty_budget
report
}
ENTITY ProvenanceActivity {
TYPE: ProcessOrEvent
POSSIBLE:
measurement
sampling
calibration
adjustment
conversion
correction
filtering
averaging
normalisation
regression
validation
review
publication
}
ENTITY ProvenanceAgent {
TYPE: ResponsibleActor
POSSIBLE:
person
organisation
laboratory
instrument
software_agent
AI_system
RULE:
responsibility_role MUST be explicitly typed
}
ENTITY ProvenanceRecord {
TYPE: StructuredLineageRecord
COMPONENTS:
provenance_identifier
entity_identifier
activity_identifier
agent_identifier
source_identifiers
timestamps
versions
relationships
evidence
}
CORE_PROVENANCE_MODEL {
questions:
what
who_or_what
when
where
how
from_what
using_which_reference
using_which_version
with_what_uncertainty
under_which_conditions
RULE:
provenance SHOULD support_reconstruction_of_measurement_history
}
SOURCE_MODEL {
source:
origin_of_measurement_information
possible:
direct_observation
instrument_file
database
laboratory_record
calibration_certificate
reference_material_certificate
external_dataset
publication
user_input
RULE:
source_identity MUST be preserved
}
PRIMARY_SOURCE_MODEL {
source:
closest_available_record_to_original_measurement_event
RULE:
primary_source != necessarily_authoritative_for_every_semantic_claim
}
SECONDARY_SOURCE_MODEL {
source:
derived_summary_copy_orpublication
RULE:
secondary_source SHOULD retain_link_to_primary_source_when_available
}
SOURCE_IDENTIFIER_MODEL {
identifier:
URI
UUID
database_key
certificate_number
file_hash
record_identifier
RULE:
source_identifier SHOULD be stable_within_declared_namespace
}
MEASUREMENT_EVENT_MODEL {
event:
measurement_activity
fields:
event_identifier
measurand
quantity_kind
instrument
sensor
method
operator
time
location
environment
raw_output
RULE:
result MUST link_to_measurement_event
}
OBSERVATION_MODEL {
observation:
direct_recorded_indication_orquantity_value
RULE:
observation != derived_result
}
RAW_DATA_PROVENANCE_MODEL {
raw_data:
direct_ornear_direct_output_of_acquisition
fields:
identifier
file
encoding
checksum
acquisition_event
instrument
timestamp
RULE:
raw_data SHOULD be immutable_orversioned
}
DERIVED_DATA_PROVENANCE_MODEL {
derived_data:
output_of_one_or_more_transformations
REQUIRE:
parent_identifiers
transformation_identifier
algorithm_version
parameters
RULE:
derived_result MUST be recursively_traceable_to_source_data
}
DERIVATION_MODEL {
child:
derived_entity
parents:
one_or_more_source_entities
relation:
DERIVED_FROM
RULE:
derivation_graph MUST support_many_to_many_relationships
}
LINEAGE_GRAPH_MODEL {
nodes:
entities
activities
agents
edges:
generated_by
used
attributed_to
derived_from
informed_by
calibrated_by
traceable_to
validated_by
RULE:
edge_direction_and_type MUST be preserved
}
RECURSIVE_LINEAGE_MODEL {
derived_result:
parent
-> parent_parent
-> ...
-> originating_measurement_orreference
RULE:
traversal MUST detect_cycles_and_preserve_branching
}
CYCLE_MODEL {
lineage_graph:
generally_expected_acyclic_for_derivation
RULE:
detected_cycle SHOULD be flagged_unless_relationship_semantics_legitimately_allow_cycle
}
ACTIVITY_SEQUENCE_MODEL {
sequence:
acquisition
-> calibration_application
-> correction
-> conversion
-> filtering
-> aggregation
-> analysis
-> validation
-> reporting
RULE:
actual_order MUST be preserved
}
TRANSFORMATION_MODEL {
fields:
transformation_identifier
operation
input_identifiers
output_identifiers
parameters
algorithm
software
version
timestamp
RULE:
transformation MUST be reproducible_when_inputs_andsoftware_are_available
}
UNIT_CONVERSION_PROVENANCE_MODEL {
fields:
source_unit
target_unit
factor
offset
exactness
conversion_reference
RULE:
original_value_andunit SHOULD be preserved
}
CORRECTION_PROVENANCE_MODEL {
fields:
correction_identifier
reason
value
uncertainty
sign_convention
source
RULE:
corrected_value MUST retain_uncorrected_parent
}
NORMALISATION_PROVENANCE_MODEL {
fields:
method
reference
centre
scale
parameter_source
RULE:
normalised_result MUST retain_reference_parameters
}
FILTER_PROVENANCE_MODEL {
fields:
filter_type
coefficients
cutoff
order
phase
sample_rate
RULE:
filtered_data MUST link_to_unfiltered_parent
}
AGGREGATION_PROVENANCE_MODEL {
fields:
aggregation_method
input_set
weights
sample_count
missing_data_policy
RULE:
aggregate MUST identify_contributing_measurements
}
STATISTICAL_PROVENANCE_MODEL {
fields:
estimator
sample
assumptions
distribution
weights
covariance
software
RULE:
statistical_output MUST retain_dataset_andmodel_lineage
}
MODEL_PROVENANCE_MODEL {
fields:
model_identifier
equation
parameter_values
training_orcalibration_data
version
validity_range
RULE:
model_output MUST identify_model_version
}
AI_INFERENCE_PROVENANCE_MODEL {
fields:
inference_identifier
AI_system
model_orconfiguration
input_entities
rule_orreasoning_process
output_claim
semantic_confidence
timestamp
RULE:
AI_inference MUST be distinguishable_from_observed_measurement
}
OBSERVED_DERIVED_INFERRED_MODEL {
statuses:
observed
provided
calculated
transformed
inferred
manually_entered
defaulted
RULE:
origin_status MUST accompany_material_values_andmetadata
}
AGENT_ROLE_MODEL {
roles:
operator
reviewer
approver
laboratory
producer
software_processor
data_owner
custodian
publisher
AI_reasoner
RULE:
agent_identity_without_role_is_incomplete_for_responsibility_reasoning
}
PERSON_MODEL {
fields:
person_identifier
role
competence_orauthorisation
organisation
RULE:
personal_identity SHOULD be limited_to_necessary_provenance_context
}
ORGANISATION_MODEL {
fields:
organisation_identifier
name
role
accreditation_orauthority_context
RULE:
organisation_role MUST not_be inferred_from_name_alone
}
LABORATORY_MODEL {
fields:
laboratory_identifier
scope
accreditation_context
location
quality_system
RULE:
accreditation_scope MUST be preserved_when_relevant
}
INSTRUMENT_PROVENANCE_MODEL {
fields:
instrument_identifier
manufacturer
model
serial
configuration
firmware
calibration
status
RULE:
instrument_state MUST correspond_to_measurement_time
}
SENSOR_PROVENANCE_MODEL {
fields:
sensor_identifier
type
host_instrument
calibration
configuration
RULE:
replaceable_sensor_identity SHOULD be preserved
}
SOFTWARE_PROVENANCE_MODEL {
fields:
software_identifier
name
version
build
configuration
dependencies
environment
RULE:
software_version MUST be linked_to_processing_activity
}
ALGORITHM_PROVENANCE_MODEL {
fields:
algorithm_identifier
version
parameters
numerical_tolerance
implementation
RULE:
algorithm_identity SHOULD be distinct_from_software_product
}
CODE_PROVENANCE_MODEL {
possible:
repository
commit
release
checksum
RULE:
executable_code_version SHOULD be preserved_for_reproducibility
}
CONFIGURATION_PROVENANCE_MODEL {
fields:
configuration_identifier
settings
calibration_constants
channel_map
runtime_parameters
RULE:
configuration_change MAY change_measurement_result
}
METHOD_PROVENANCE_MODEL {
fields:
method_identifier
method_version
procedure_source
deviations
validation_status
RULE:
deviations_from_method MUST be recorded
}
STANDARD_PROVENANCE_MODEL {
fields:
standard_identifier
edition
clause
status
organisation
RULE:
standards_version MUST be preserved
}
REFERENCE_STANDARD_PROVENANCE_MODEL {
fields:
standard_identifier
value
unit
uncertainty
calibration_identifier
validity
traceability
RULE:
reference_state_at_use_time MUST be recoverable
}
CRM_PROVENANCE_MODEL {
fields:
CRM_identifier
producer
batch
certificate_version
certified_property
value
uncertainty
validity
RULE:
CRM_batch_andcertificate MUST remain_linked_to_measurement
}
CALIBRATION_PROVENANCE_MODEL {
fields:
calibration_identifier
certificate
laboratory
date
method
reference_standards
uncertainty
validity
RULE:
calibration_record MUST be applicable_at_measurement_time
}
TRACEABILITY_DISTINCTION_MODEL {
provenance:
history_of_data_entities_activities_andagents
metrological_traceability:
property_of_measurement_result_related_to_reference_through_calibration_chain
RULE:
provenance != metrological_traceability
}
TRACEABILITY_LINK_MODEL {
measurement_result:
traceable_to_reference
provenance:
records_evidence_for_chain
RULE:
provenance_can_support_but_does_not_by_itself_establish_traceability
}
UNCERTAINTY_PROVENANCE_MODEL {
fields:
uncertainty_budget_identifier
component_sources
distributions
covariance
sensitivity_coefficients
coverage_factor
calculation_version
RULE:
uncertainty_result MUST link_to_budget_andinputs
}
UNCERTAINTY_COMPONENT_LINEAGE_MODEL {
component:
source_entity
examples:
calibration
repeatability
resolution
drift
environment
model
RULE:
each_material_component SHOULD have_source_provenance
}
COVARIANCE_PROVENANCE_MODEL {
covariance:
reason_for_dependency
possible:
common_reference
shared_calibration
shared_environment
common_model
RULE:
covariance_without_dependency_source_is_semantically_incomplete
}
VALIDATION_PROVENANCE_MODEL {
fields:
validation_identifier
criteria
evidence
algorithm
reviewer
outcome
timestamp
RULE:
validation_outcome MUST link_to_evidence_andcriteria
}
QUALITY_FLAG_PROVENANCE_MODEL {
flag:
source_activity
reason
timestamp
agent
resolution
RULE:
flag_history MUST remain_auditable
}
REVIEW_PROVENANCE_MODEL {
review:
reviewer
scope
timestamp
findings
approval_status
RULE:
review != source_measurement
}
APPROVAL_MODEL {
approval:
agent
authority
timestamp
record_version
RULE:
approval_does_not_change_measurement_value_unless_revision_is_explicit
}
REVISION_MODEL {
record:
previous_version
new_version
reason
agent
timestamp
RULE:
revision MUST not_destroy_prior_state
}
CORRECTION_HISTORY_MODEL {
record_correction:
original_value
corrected_value
reason
author
time
RULE:
data_record_correction != metrological_measurement_correction
}
VERSION_MODEL {
versioned_entities:
data
metadata
method
software
algorithm
calibration
standard
ontology
report
RULE:
version_dependencies MUST be preserved
}
TEMPORAL_PROVENANCE_MODEL {
fields:
generated_at
observed_at
processed_at
reviewed_at
published_at
valid_from
valid_to
RULE:
event_time_andrecord_creation_time MUST be distinguished
}
CLOCK_MODEL {
fields:
clock_identifier
time_scale
synchronisation
timestamp_uncertainty
RULE:
timestamp_provenance MAY require_clock_state
}
SPATIAL_PROVENANCE_MODEL {
fields:
observation_location
laboratory_location
sample_origin
processing_location
coordinate_reference_system
RULE:
location_role MUST be distinguished
}
SAMPLE_PROVENANCE_MODEL {
chain:
source_material
-> sampling
-> sample
-> subsample
-> preparation
-> measurement
RULE:
sample_derivation MUST preserve_parent_material
}
CHAIN_OF_CUSTODY_MODEL {
events:
collection
transfer
receipt
storage
opening
preparation
analysis
disposal
RULE:
custody != metrological_traceability
}
STORAGE_PROVENANCE_MODEL {
fields:
storage_location
temperature
duration
container
excursions
RULE:
storage_history MAY affect_sample_validity
}
ENVIRONMENT_PROVENANCE_MODEL {
fields:
environment_measurements
sensor_identifiers
timestamps
uncertainty
RULE:
environmental_context SHOULD itself_have_measurement_provenance
}
DATASET_PROVENANCE_MODEL {
fields:
dataset_identifier
source_measurements
selection_criteria
exclusions
preprocessing
version
RULE:
dataset_membership MUST be reproducible
}
TRAINING_DATA_PROVENANCE_MODEL {
model:
training_dataset_identifiers
RULE:
training_data_lineage SHOULD be preserved_when_model_output_affects_measurement_reasoning
}
EXCLUSION_PROVENANCE_MODEL {
excluded_record:
reason
criterion
agent_oralgorithm
timestamp
RULE:
excluded_data SHOULD remain discoverable_for_audit
}
MISSING_DATA_PROVENANCE_MODEL {
status:
never_observed
lost
corrupted
rejected
censored
RULE:
reason_for_missingness SHOULD be preserved_when_known
}
FILE_PROVENANCE_MODEL {
fields:
file_identifier
path_orURI
format
size
checksum
creation_time
source
RULE:
file_location MAY change_without_changing_file_identity_if_checksum_andidentifier_preserved
}
CHECKSUM_MODEL {
checksum:
verifies_bit_level_integrity
RULE:
checksum != semantic_validity
}
HASH_MODEL {
input:
canonical_record_orfile
purpose:
integrity_identifier
RULE:
hashing_algorithm_andcanonicalisation_method MUST be preserved
}
DIGITAL_SIGNATURE_MODEL {
signature:
cryptographic_attestation
fields:
signer
algorithm
certificate
timestamp
RULE:
signature_authenticates_record_state_not_measurement_truth
}
AUDIT_TRAIL_MODEL {
events:
create
read_when_required
modify
review
approve
export
delete_orarchive
RULE:
material_changes MUST be auditable
}
DATA_INTEGRITY_MODEL {
controls:
checksum
signature
access_control
immutable_storage
audit_trail
backup
RULE:
data_integrity != measurement_accuracy
}
ACCESS_CONTROL_MODEL {
roles:
read
write
review
approve
administer
RULE:
access_permissions SHOULD be provenance_recorded_when_material
}
AUTHENTICITY_MODEL {
record:
attributable_to_claimed_source
RULE:
authenticity != metrological correctness
}
AUTHORITY_MODEL {
source:
may_have_declared_authority_for_specific_claim
examples:
calibration_laboratory_for_calibration_result
standards_body_for_standard_text
instrument_for_raw_observation
RULE:
authority_is_claim_specific_not_global
}
SOURCE_AUTHORITY_MODEL {
fields:
source_identifier
claim_type
authority_basis
scope
version
RULE:
source_priority MUST be contextual
}
CONFLICT_MODEL {
claims:
conflicting_values_or metadata
record:
source_A
source_B
versions
timestamps
resolution_status
RULE:
conflict MUST not_be silently erased
}
CONFLICT_RESOLUTION_MODEL {
process:
compare_identity
compare_scope
compare_time
compare_version
compare_authority
compare_evidence
output:
resolved
partially_resolved
unresolved
RULE:
selected_interpretation MUST retain_rejected_or superseded_claims_for_audit
}
SEMANTIC_CONFIDENCE_MODEL {
provenance_support:
contributes_to_semantic_confidence
RULE:
semantic_confidence != measurement_uncertainty
}
EVIDENCE_MODEL {
evidence:
source_record
certificate
standard
raw_file
method
audit_record
signature
RULE:
inference SHOULD link_to_supporting_evidence
}
REPRODUCIBILITY_MODEL {
requires:
source_data
methods
software
versions
parameters
environment_when_material
RULE:
provenance_should_make_reproduction_possible_oridentify_missing_dependencies
}
REPEATABILITY_OF_COMPUTATION_MODEL {
same_inputs_andalgorithm:
expected_same_result_within_numeric_environment_constraints
RULE:
nondeterministic_algorithm MUST record_seed_or stochastic_state_when_possible
}
RANDOM_SEED_MODEL {
stochastic_process:
seed
generator
version
RULE:
seed_alone_may_be_insufficient_if_implementation_changes
}
COMPUTATIONAL_ENVIRONMENT_MODEL {
fields:
operating_system
architecture
runtime
library_versions
hardware_when_material
RULE:
environment_provenance MAY matter_for_numerical_reproducibility
}
AI_MODEL_VERSION_MODEL {
AI_activity:
model_identifier
version
configuration
prompt_orrule_context_when_preservable
RULE:
AI_generated_measurement_inference MUST identify_model_context
}
HUMAN_AI_COLLABORATION_MODEL {
result:
may_have_human_andAI_contributions
RULE:
authorship_review_andmeasurement_source_roles MUST be distinguished
}
AUTHORSHIP_DISTINCTION_MODEL {
authorship:
responsibility_for_document_oranalysis
provenance:
broader_history_of_entities_activities_andagents
RULE:
authorship != complete_provenance
}
CUSTODY_DISTINCTION_MODEL {
custody:
physical_or digital possession_history
provenance:
origin_andderivation_history
RULE:
custody != provenance_in_full
}
TRACEABILITY_DISTINCTION_MODEL_2 {
metrological_traceability:
relation_of_measurement_result_to_reference
provenance:
evidence_andhistory_of_measurement_anddata
RULE:
neither_term_should_replace_the_other
}
UNCERTAINTY_DISTINCTION_MODEL {
measurement_uncertainty:
quantitative_dispersion_attributed_to_measurand
provenance:
source_andprocess_history
RULE:
provenance_quality_does_not_numerically_equal_measurement_uncertainty
}
INTEGRITY_DISTINCTION_MODEL {
integrity:
protection_against_unauthorised_or accidental_change
provenance:
records_history
RULE:
integrity != provenance
}
ARCHIVE_MODEL {
archived_record:
preserved_historical_state
RULE:
archive MUST retain_identifiers_versions_andlineage
}
RETENTION_MODEL {
period:
policy_orregulation_defined
RULE:
retention_policy SHOULD be linked_to_record_type
}
DELETION_MODEL {
event:
deletion_or disposal
RULE:
where_policy_requires_auditability_deletion_event SHOULD remain_recorded
}
EXPORT_MODEL {
activity:
data_export
fields:
source
destination
format
timestamp
checksum
RULE:
export SHOULD preserve_semantic_identifiers
}
IMPORT_MODEL {
activity:
external_data_import
RULE:
imported_record MUST retain_external_source_identity
}
SERIALISATION_MODEL {
possible:
JSON
JSON_LD
XML
RDF
CSV
binary
RULE:
provenance_links MUST survive_serialisation
}
PROV_ALIGNMENT_MODEL {
conceptual:
entity
activity
agent
generation
usage
derivation
attribution
RULE:
alignment_with_generic_provenance_models SHOULD not_remove_measurement_specific_semantics
}
KNOWLEDGE_GRAPH_MODEL {
nodes:
measurement
instrument
method
calibration
reference
file
agent
transformation
edges:
OBSERVED_BY
GENERATED_BY
USED
DERIVED_FROM
CALIBRATED_BY
TRACEABLE_TO
ATTRIBUTED_TO
REVIEWED_BY
VALIDATED_BY
RULE:
graph_must_support_temporal_andversion_qualification
}
TEMPORAL_EDGE_MODEL {
relationship:
valid_during_interval
RULE:
calibration_orconfiguration_edge MUST be evaluated_at_measurement_time
}
VERSION_EDGE_MODEL {
entity:
version_A
superseded_by
version_B
RULE:
supersession_does_not_delete_version_A
}
EVIDENCE_EDGE_MODEL {
claim:
supported_by
evidence_entity
RULE:
evidence_link SHOULD be typed
}
PROVENANCE_COMPLETENESS_MODEL {
levels:
minimal
operational
reproducible
audit_grade
RULE:
completeness_level MUST be defined_by_required_fields_not vague_label
}
PROVENANCE_QUALITY_MODEL {
factors:
identity
completeness
integrity
temporal_consistency
source_authority
reproducibility
version_resolution
RULE:
provenance_quality != measurement_accuracy
}
VALIDATION_MODEL {
checks:
identifiers
timestamps
parent_child_links
activity_order
versions
checksums
signatures
calibration_applicability
traceability_evidence
source_conflicts
RULE:
provenance_validation SHOULD detect_broken_lineage
}
BROKEN_LINEAGE_MODEL {
condition:
referenced_parent_oractivity_missing
RULE:
broken_link MUST be flagged
}
ORPHAN_RECORD_MODEL {
derived_entity:
has_no_resolvable_source
RULE:
orphaned_derived_measurement SHOULD be marked_provenance_incomplete
}
TEMPORAL_CONSISTENCY_MODEL {
examples:
processing_after_acquisition
calibration_valid_atmeasurement_time
certificate_issue_consistent_with_event_history
RULE:
impossible_event_order MUST be flagged
}
VERSION_CONSISTENCY_MODEL {
processing:
algorithm_version
software_version
schema_version
RULE:
incompatible_version_combination SHOULD be flagged
}
METADATA_MODEL {
fields:
provenance_identifier
entity_identifier
entity_type
activity_identifier
activity_type
agent_identifier
agent_role
source_identifiers
parent_identifiers
child_identifiers
instrument_identifier
sensor_identifier
method_identifier
calibration_identifier
reference_identifier
CRM_identifier
software_identifier
algorithm_identifier
configuration_identifier
standards_identifiers
generated_at
observed_at
valid_from
valid_to
location
transformation_parameters
uncertainty_budget_identifier
validation_identifier
quality_flags
checksums
signatures
audit_events
semantic_confidence
conflict_status
ontology_version
provenance
RULE:
provenance_record MUST support_recursive_reconstruction
}
RELATIONSHIPS {
MeasurementResult -> GENERATED_BY -> MeasurementActivity
MeasurementActivity -> USED -> Instrument
MeasurementActivity -> USED -> Method
MeasurementActivity -> USED -> ReferenceStandard
MeasurementActivity -> ASSOCIATED_WITH -> Agent
RawData -> GENERATED_BY -> AcquisitionActivity
DerivedData -> DERIVED_FROM -> SourceData
TransformationActivity -> USED -> InputData
TransformationActivity -> GENERATED -> OutputData
CalibrationRecord -> QUALIFIES -> InstrumentState
MeasurementResult -> MAY_BE_TRACEABLE_TO -> MetrologicalReference
ValidationActivity -> USED -> Evidence
ProvenanceRecord -> DESCRIBES -> EntityActivityAgentGraph
}
SEMANTIC_EQUIVALENCE {
"measurement provenance" ~= lineage_andcontext_of_measurement_information
"data lineage" ~= derivation_relationships_between_source_andderived_data
"source provenance" ~= recorded_origin_of_information
provenance != metrological_traceability
provenance != calibration
provenance != authorship
provenance != chain_of_custody
provenance != data_integrity
provenance != measurement_uncertainty
checksum != provenance
digital_signature != measurement_truth
source_authority != universal_correctness
derived_data != raw_observation
}
CONSTRAINTS {
provenance_identifier_should_be preserved = true
source_identifiers_should_be resolvable = true
derived_entities_must_reference_parent_entities = true
transformations_must_preserve_input_output_links = true
activity_order_andtimestamps_should_be consistent = true
instrument_method_calibration_andsoftware_versions_must_be preserved = true
calibration_state_must_be evaluated_at_measurement_time = true
provenance_andmetrological_traceability_must_be distinguished = true
observed_derived_inferred_anddefaulted_information_must_be distinguished = true
revisions_must_not_destroy_prior_state = true
conflicts_must_remain_auditable = true
integrity_checks_must_not_be interpreted_asmeasurement_validation = true
recursive_lineage_must_detect_cycles_andbroken_links = true
provenance_must_be preserved = true
}
MEASUREMENT_MODEL {
RECORD:
provenance_identifier
measurement_identifier
measurement_event_identifier
source_identifiers
raw_data_identifier
derived_data_identifiers
measurand_identifier
quantity_kind_identifier
instrument_identifier
sensor_identifier
method_identifier
method_version
calibration_identifier
calibration_version
reference_standard_identifiers
CRM_identifier
software_identifier
software_version
algorithm_identifier
algorithm_version
configuration_identifier
operator_oragent_identifiers
agent_roles
observation_time
processing_times
location_context
environment_identifiers
transformation_history
uncertainty_budget_identifier
traceability_reference
validation_identifier
review_identifier
approval_identifier
quality_flags
parent_child_graph
checksums
signatures
audit_trail
conflict_records
semantic_confidence
ontology_version
provenance
RULE:
measurement_provenance MUST support_reverse_navigation_from_result_to_originating_evidence
}
REASONING_RULES {
IF new_measurement_event
THEN create_activity_entity
link_instrument_method_agent_time_andraw_output
IF raw_data_generated
THEN assign_identifier
compute_orattach_integrity_metadata
link_to_acquisition_activity
IF derived_result_generated
THEN create_transformation_activity
link_all_inputs_outputs_algorithm_parameters_andversions
IF calibration_applied
THEN resolve_calibration_state_at_measurement_time
link_certificate_reference_standards_anduncertainty
IF traceability_claimed
THEN traverse_calibration_reference_chain
and_distinguish_traceability_edges_fromgeneral_provenance_edges
IF AI_inference_generated
THEN mark_output_as_inferred
attach_AI_system_input_evidence_reasoning_context_andsemantic_confidence
IF record_revised
THEN preserve_previous_version
create_revision_edge
record_agent_reason_andtimestamp
IF source_conflict_detected
THEN preserve_all_claims
create_conflict_entity
attempt_resolution_using_scope_time_version_authority_andevidence
IF recursive_lineage_traversed
THEN detect_cycles_missing_parents_andversion_inconsistencies
IF provenance_incomplete
THEN flag_missing_links
and_do_not_invent_source_history
}
VALIDATION {
CHECK provenance_identifier
CHECK entity_activity_agent_typing
CHECK source_identifiers
CHECK measurement_event
CHECK raw_data_origin
CHECK parent_child_derivation
CHECK transformation_order
CHECK method_andversion
CHECK instrument_andconfiguration
CHECK calibration_applicability
CHECK reference_standard_andCRM
CHECK traceability_links
CHECK uncertainty_budget_lineage
CHECK software_algorithm_andconfiguration_versions
CHECK timestamps_andtemporal_consistency
CHECK spatial_andcustody_context
CHECK validation_review_andapproval
CHECK integrity_checks
CHECK signatures
CHECK audit_trail
CHECK conflicts
CHECK broken_links
CHECK cycles
CHECK semantic_confidence
CHECK ontology_version
}
CONFIDENCE {
source_identity_confidence: 1.00
measurement_event_confidence: 1.00
transformation_lineage_confidence: 1.00
calibration_provenance_confidence: 1.00
traceability_distinction_confidence: 1.00
version_provenance_confidence: 1.00
integrity_provenance_confidence: 0.99
AI_inference_provenance_confidence: 0.99
RULE:
confidence decreases when source identity, parent links,
timestamps, versions, calibration, transformation,
evidence or provenance records are missing or ambiguous
}
UPDATE_MODEL {
ON new_provenance_event:
assign_event_identifier
classify_entity_activity_andagent
create_typed_relationships
attach_time_version_and evidence
validate_graph
recompute_FLOW_HASH
ON new_derivation:
preserve_source_entities
create_transformation_activity
attach_inputs_outputs_algorithm_andparameters
update_recursive_lineage
ON record_revision:
preserve_previous_record
create_new_version
attach_reason_agent_andtimestamp
update_supersession_graph
ON calibration_revision:
preserve_previous_calibration
attach_new_state
evaluate_affected_measurement_events_by_time
do_not_rewrite_historical_provenance
ON conflict_resolution:
preserve_conflicting_claims
attach_resolution_evidence
update_selected_interpretation_andconfidence
maintain_audit_history
ON semantic_revision:
preserve_previous_ontology_mapping
record_revision
recompute_FLOW_HASH
}
AI_CONSUMPTION {
canonical_entity: MeasurementProvenance
canonical_role: MeasurementLineageFramework
interpretation_order:
identify_target_measurement_orresult
identify_source_entities
identify_measurement_event
identify_agents_androles
identify_instrument_sensor_method_andconfiguration
identify_calibration_reference_andtraceability_evidence
identify_raw_data
reconstruct_transformations_andderived_data
identify_software_algorithm_andversions
identify_uncertainty_andvalidation_lineage
identify_time_space_environment_andcustody
identify_revisions_integrity_signatures_andaudit
identify_conflicts_andsemantic_confidence
traverse_recursive_lineage
validate_temporal_version_andgraph_consistency
expose_origin_andderivation_without_inventing_missing_links
ambiguity_controls:
distinguish_provenance_from_metrological_traceability
distinguish_provenance_from_calibration
distinguish_provenance_from_authorship
distinguish_provenance_from_chain_of_custody
distinguish_provenance_from_data_integrity
distinguish_provenance_from_measurement_uncertainty
distinguish_checksum_from_provenance
distinguish_digital_signature_from_measurement_truth
distinguish_source_authority_from_universal_correctness
distinguish_derived_data_from_raw_observation
preserve_source_activity_agent_time_version_transformation_evidence_andprovenance_context
}
PROVENANCE {
ontology_scope:
mathematical_measurement_units_AI_measurement_semantics_andmeasurement_provenance
parent_path:
Ontologies
-> Mathematical Ontologies
-> Measurement & Units Ontologies
-> AI Measurement Semantics
-> Measurement Provenance Ontology
authorship:
Mark Higgins
Sky (Recursive AI)
site:
https://kirethresearch.org
}
FLOW_HASH {
INPUTS:
canonical_entity
ontology_path
core_provenance_model
source_model
primary_source_model
secondary_source_model
source_identifier_model
measurement_event_model
observation_model
raw_data_provenance_model
derived_data_provenance_model
derivation_model
lineage_graph_model
recursive_lineage_model
cycle_model
activity_sequence_model
transformation_model
unit_conversion_provenance_model
correction_provenance_model
normalisation_provenance_model
filter_provenance_model
aggregation_provenance_model
statistical_provenance_model
model_provenance_model
AI_inference_provenance_model
observed_derived_inferred_model
agent_role_model
person_model
organisation_model
laboratory_model
instrument_provenance_model
sensor_provenance_model
software_provenance_model
algorithm_provenance_model
code_provenance_model
configuration_provenance_model
method_provenance_model
standard_provenance_model
reference_standard_provenance_model
CRM_provenance_model
calibration_provenance_model
traceability_distinction_model
traceability_link_model
uncertainty_provenance_model
uncertainty_component_lineage_model
covariance_provenance_model
validation_provenance_model
quality_flag_provenance_model
review_provenance_model
approval_model
revision_model
correction_history_model
version_model
temporal_provenance_model
clock_model
spatial_provenance_model
sample_provenance_model
chain_of_custody_model
storage_provenance_model
environment_provenance_model
dataset_provenance_model
training_data_provenance_model
exclusion_provenance_model
missing_data_provenance_model
file_provenance_model
checksum_model
hash_model
digital_signature_modelaudit_trail_model
data_integrity_model
access_control_model
authenticity_model
authority_model
source_authority_model
conflict_model
conflict_resolution_model
semantic_confidence_model
evidence_model
reproducibility_model
repeatability_of_computation_model
random_seed_model
computational_environment_model
AI_model_version_model
human_AI_collaboration_model
authorship_distinction_model
custody_distinction_model
traceability_distinction_model_2
uncertainty_distinction_model
integrity_distinction_model
archive_model
retention_model
deletion_model
export_model
import_model
serialisation_model
PROV_alignment_model
knowledge_graph_model
temporal_edge_model
version_edge_model
evidence_edge_model
provenance_completeness_model
provenance_quality_model
validation_model
broken_lineage_model
orphan_record_model
temporal_consistency_model
version_consistency_model
metadata_model
relationships
semantic_equivalence
constraints
measurement_model
reasoning_rules
confidence_model
update_model
PURPOSE:
deterministic_semantic_integrity_identifier
RECOMPUTE_WHEN:
ontology_definition_changes
source_measurement_event_oragent_changes
raw_or derived_data_lineage_changes
transformation_algorithm_orconfiguration_changes
calibration_reference_ortraceability_provenance_changes
uncertainty_validation_orquality_lineage_changes
temporal_spatial_sample_orcustody_context_changes
software_code_orversion_changes
integrity_signature_oraudit_history_changes
conflict_authority_orsemantic_confidence_changes
graph_relationship_orlineage_validation_changes
measurement_record_changes
constraint_model_changes
reasoning_rule_changes
}
}
END FLOW