Cross-Domain Unit Mapping Ontology
AI Measurement Semantics
Authors: MArk Anthony Higgins - Sky Recursive Ai
Revised Date: 16 September 2026
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# Cross-Domain Unit Mapping Ontology — Flow Algebra
URL: https://kirethresearch.org/booksai-core/ontologies/mathematical-ontologies/measurement-units-ontologies/ai-measurement-semantics/cross-domain-unit-mapping-ontology.html
FLOW CrossDomainUnitMappingOntology {
DOMAIN:
Mathematical Ontologies
-> Measurement & Units Ontologies
-> AI Measurement Semantics
-> Cross-Domain Unit Mapping Ontology
PURPOSE:
Represent the semantic mapping of measurement units, quantity kinds, dimensions, scales, reference states and measurement conventions across scientific, engineering and computational domains. The ontology enables AI systems to determine when two unit expressions are exactly convertible, contextually convertible, dimensionally compatible but semantically distinct, operationally defined, reference-dependent or incompatible. It models SI and non-SI units, domain-specific units, prefixes, compound units, affine and logarithmic scales, count and ratio quantities, chemical and biological concentration conventions, astronomical units, earth-science units, engineering conventions, temporal units, information units, coordinate-dependent quantities, uncertainty propagation, provenance, versioning and machine-readable mapping rules while preventing dimensional similarity from being mistaken for semantic equivalence.
ENTITY CrossDomainUnitMapping {
TYPE: SemanticUnitInteroperabilityFramework
PROPERTIES:
maps_units
maps_quantity_kinds
maps_dimensions
maps_scales
maps_reference_states
maps_domain_conventions
validates_conversion
propagates_uncertainty
preserves_provenance
preserves_versions
exposes_ambiguity
}
ENTITY UnitMapping {
TYPE: TypedSemanticRelation
COMPONENTS:
source_unit
target_unit
source_quantity_kind
target_quantity_kind
mapping_type
conversion_function
constraints
uncertainty
provenance
}
ENTITY DomainUnit {
TYPE: MeasurementUnit
PROPERTIES:
identifier
name
symbol
domain
quantity_kind
dimension
scale
offset
reference_state
definition_source
}
ENTITY MappingContext {
TYPE: ConversionContext
POSSIBLE:
physical_conditions
chemical_composition
reference_temperature
reference_pressure
gravitational_context
coordinate_frame
calendar
domain_standard
measurement_method
}
MAPPING_TYPE_MODEL {
possible:
exact_identity
exact_linear_conversion
defined_linear_conversion
affine_conversion
logarithmic_conversion
contextual_conversion
model_based_conversion
semantic_alignment_without_conversion
dimensionally_compatible_but_semantically_distinct
incompatible
RULE:
mapping_type MUST be explicit
}
EXACT_IDENTITY_MODEL {
source:
canonical_unit_A
target:
canonical_unit_B
condition:
same_definition_andquantity_kind
RULE:
lexical_difference MAY coexist_withsemantic_identity
}
LINEAR_CONVERSION_MODEL {
source_value:
x
target_value:
y =
k*x
RULE:
factor_exactness MUST be preserved
}
AFFINE_CONVERSION_MODEL {
y =
a*x+b
RULE:
affine_mapping MUST distinguish_absolute_values_fromdifferences
}
LOGARITHMIC_CONVERSION_MODEL {
generic:
L =
k*log_b(Q/Q_ref)
REQUIRE:
reference_quantity
logarithm_base
multiplier
quantity_kind
RULE:
logarithmic_units MUST not_be processed_asordinary_linear_units
}
CONTEXTUAL_CONVERSION_MODEL {
y =
f(x,c_1,...,c_n)
RULE:
required_context_parameters MUST not_be invented
}
MODEL_BASED_MAPPING_MODEL {
target:
derived_fromsource_usingphysical_or empirical_model
RULE:
model_based_mapping != unit_conversion_instrict_metrological_sense
}
SEMANTIC_ALIGNMENT_MODEL {
source_entity:
maps_to_target_entity
relation:
exact
broader
narrower
related
RULE:
ontology_alignment MAY exist_withoutnumeric_conversion
}
DIMENSION_MODEL {
canonical:
L^a*M^b*T^c*I^d*Theta^e*N^f*J^g
RULE:
dimension != quantity_kind
}
DIMENSIONAL_COMPATIBILITY_MODEL {
source_dimension:
D_s
target_dimension:
D_t
direct_unit_conversion_requires:
D_s =
D_t
RULE:
equal_dimensions_are_not_sufficient_forsemantic_equivalence
}
SAME_DIMENSION_DIFFERENT_KIND_MODEL {
examples:
energy_vs_torque
frequency_vs_radioactivity
absorbed_dose_vs_dose_equivalent
plane_angle_vs_dimensionless_ratio
RULE:
AI MUST preserve_quantity_kind
}
QUANTITY_KIND_MAPPING_MODEL {
source:
quantity_kind_A
target:
quantity_kind_B
possible:
same
equivalent_undercontext
related_byequation
semantically_distinct
RULE:
unit_mapping MUST not silently_change_quantity_kind
}
SI_MODEL {
system:
International_System_of_Units
RULE:
SI_unit_definitions SHOULD be canonical_reference_whenappropriate
}
NON_SI_MODEL {
unit:
outside_SI
possible:
accepted_with_SI
domain_specific
customary
historical
RULE:
status MUST be version_anddomain_resolved
}
PREFIX_MODEL {
prefixed_unit:
prefix*unit
factor:
10^n
under_SI_decimal_prefix_context
RULE:
prefix_case_andattachment MUST be preserved
}
BINARY_PREFIX_MODEL {
possible:
kibi
mebi
gibi
tebi
pebi
exbi
factor:
2^(10n)
RULE:
binary_prefix != decimal_SI_prefix
}
COMPOUND_UNIT_MODEL {
expression:
products
quotients
powers
RULE:
conversion_factor MUST propagate_throughentire_expression
}
POWERED_UNIT_MODEL {
source:
(k*u)^n
relation:
k^n*u^n
RULE:
prefix_factor MUST be exponentiated_withunit
}
MASS_MAPPING_MODEL {
SI:
kilogram
possible:
gram
tonne
pound
ounce
RULE:
mass_unit_mapping MUST not_be confused_withforce
}
FORCE_MASS_DISTINCTION_MODEL {
mass:
dimension_M
force:
dimension_M*L*T^-2
RULE:
pound_mass_andpound_force MUST be explicitly_distinguished
}
LENGTH_MAPPING_MODEL {
possible:
metre
centimetre
millimetre
kilometre
inch
foot
yard
mile
nautical_mile
RULE:
definition_source_andexact_factor SHOULD be preserved
}
AREA_MAPPING_MODEL {
relation:
length_factor_squared
RULE:
linear_conversion_factor MUST not_be applied_unpowered_toarea
}
VOLUME_MAPPING_MODEL {
relation:
length_factor_cubed
possible:
cubic_metre
litre
millilitre
gallon
fluid_ounce
RULE:
gallon_orfluid_ounce_requires_system_resolution
}
IMPERIAL_US_DISTINCTION_MODEL {
ambiguous_names:
gallon
pint
fluid_ounce
ton
RULE:
jurisdiction_orunit_system MUST be resolved
}
TEMPERATURE_MAPPING_MODEL {
scales:
kelvin
degree_Celsius
degree_Fahrenheit
Rankine
RULE:
temperature_scale_value_conversion_is_affine
}
TEMPERATURE_DIFFERENCE_MODEL {
interval:
delta_temperature
RULE:
offsets_do_not_apply_to_temperature_differences
}
PRESSURE_MAPPING_MODEL {
possible:
pascal
kilopascal
bar
atmosphere
torr
psi
RULE:
gauge_absolute_anddifferential_pressure MUST be distinguished
}
PRESSURE_REFERENCE_MODEL {
possible:
absolute
gauge
differential
RULE:
gauge_toabsolute_conversion_requires_reference_pressure
}
ENERGY_MAPPING_MODEL {
possible:
joule
kilojoule
calorie
kilocalorie
watt_hour
electronvolt
BTU
RULE:
calorie_andBTU_definitions MAY require_variant_resolution
}
POWER_MAPPING_MODEL {
possible:
watt
kilowatt
horsepower
RULE:
horsepower_variant MUST be identified
}
TIME_MAPPING_MODEL {
possible:
second
minute
hour
day
RULE:
fixed_duration_units MUST be distinguished_fromcalendar_units
}
CALENDAR_TIME_MODEL {
possible:
month
year
RULE:
conversion_to_seconds_requires_calendar_orconvention_context
}
FREQUENCY_MODEL {
unit:
hertz
dimension:
T^-1
RULE:
Hz_semantics != Bq_semantics
}
ANGULAR_FREQUENCY_MODEL {
quantity:
angular_frequency
common:
rad/s
relation:
omega =
2*pi*f
RULE:
angular_frequency_andcyclic_frequency_are_related_quantity_kinds_notidentical_numeric_units
}
ANGLE_MODEL {
possible:
radian
degree
arcminute
arcsecond
RULE:
angle_is_dimensionless_inSI_dimension_system_butretains_quantity_kind
}
SPEED_MODEL {
possible:
m/s
km/h
mph
knot
RULE:
velocity_vector_andspeed_scalar MUST be distinguished
}
ACCELERATION_MODEL {
possible:
m/s^2
gal
standard_gravity_multiple
RULE:
symbol_g MAY representquantity_orstandard_gravity_context_andmust_be resolved
}
STANDARD_GRAVITY_MODEL {
g_n:
defined_reference_acceleration
RULE:
local_gravity != standard_gravity
}
TORQUE_ENERGY_MODEL {
shared_dimension:
M*L^2*T^-2
RULE:
N*m_for_torque MUST not_be canonicalised_tojoule_whenquantity_kind_is_torque
}
ELECTRICAL_MODEL {
quantities:
voltage
current
resistance
conductance
charge
capacitance
inductance
RULE:
mapping MUST preserve_quantity_kind
}
MAGNETIC_MODEL {
quantities:
magnetic_flux
magnetic_flux_density
magnetic_field_strength
RULE:
tesla_gauss_andfield_strength_units MUST be quantity-aware
}
PHOTOMETRIC_MODEL {
quantities:
luminous_intensity
luminous_flux
illuminance
luminance
RULE:
radiometric_andphotometric_quantities MUST not_be directly_equated
}
RADIOMETRIC_MODEL {
quantities:
radiant_flux
irradiance
radiance
RULE:
photometric_conversion_requires_spectral_weighting_context
}
CHEMICAL_CONCENTRATION_MODEL {
possible:
molarity
molality
mass_concentration
mass_fraction
amount_fraction
volume_fraction
RULE:
concentration_quantity_kinds_are_not_interchangeable_byunit_scaling_alone
}
MOLARITY_MOLALITY_MODEL {
molarity:
amount/volume_solution
molality:
amount/mass_solvent
RULE:
conversion_requires_density_andcomposition_context
}
MASS_FRACTION_MODEL {
w =
mass_component/mass_total
dimension:
1
RULE:
percent_by_mass MUST retain_fraction_basis
}
VOLUME_FRACTION_MODEL {
phi =
volume_component/volume_total
dimension:
1
RULE:
volume_fraction MAY depend_onreference_temperature_andpressure
}
AMOUNT_FRACTION_MODEL {
x =
amount_component/amount_total
dimension:
1
RULE:
amount_fraction != mass_fraction
}
PPM_MODEL {
token:
ppm
possible:
dimensionless_fraction
mass_fraction
volume_fraction
amount_fraction
RULE:
ppm_requires_basis_resolution
}
PPB_MODEL {
token:
ppb
RULE:
scale_convention_andfraction_basis MUST be explicit
}
GAS_CONCENTRATION_MODEL {
conversion:
volume_oramount_fraction_to_mass_concentration
requires:
molar_mass
temperature
pressure
gas_model
RULE:
conversion_is_contextual_notpure_unit_scaling
}
BIOLOGICAL_CONCENTRATION_MODEL {
possible:
cells_per_volume
copies_per_volume
mass_pervolume
activity_pervolume
RULE:
entity_type_andmeasurement_method MUST be preserved
}
CELL_COUNT_MODEL {
unit:
cells
cells_pervolume
cells_perarea
RULE:
count_entity_identity MUST be explicit
}
ENZYME_ACTIVITY_MODEL {
possible:
katal
enzyme_unit
RULE:
enzyme_unit_conversion_requires_declared_definition
}
CLINICAL_UNIT_MODEL {
possible:
conventional_units
SI_units
RULE:
analyte_specific_molar_mass_orconversion_relation MAY be required
}
PH_MODEL {
quantity:
logarithmic_measure_ofhydrogen_ion_activity_underdefined_convention
RULE:
pH_is_not_linear_concentration_unit
}
DECIBEL_MODEL {
logarithmic:
level_relative_to reference
RULE:
power_andamplitude_ratio_forms_use_different_multipliers
}
SOUND_PRESSURE_LEVEL_MODEL {
L_p =
20*log10(p/p_ref)
RULE:
reference_pressure_andmedium_context MUST be preserved
}
STELLAR_MAGNITUDE_MODEL {
logarithmic_scale:
brightness_related
RULE:
magnitude_system_andzero_point MUST be identified
}
SEISMIC_MAGNITUDE_MODEL {
logarithmic_or empirical_scale:
earthquake_size
RULE:
magnitude_scale_type MUST be explicit
}
EARTH_SCIENCE_MODEL {
possible:
rainfall_depth
river_discharge
soil_moisture
elevation
depth
atmospheric_pressure
wind_speed
RULE:
geodetic_vertical_reference_andmeasurement_basis MAY be required
}
RAINFALL_MODEL {
depth:
length_unit_overaccumulation_period
RULE:
rainfall_depth != rainfall_rate
}
RIVER_DISCHARGE_MODEL {
quantity:
volume/time
possible:
m^3/s
litre/s
cubic_foot/s
RULE:
flow_rate_quantity_kind MUST be explicit
}
SOIL_MOISTURE_MODEL {
possible:
volumetric_water_content
gravimetric_water_content
RULE:
basis MUST be identified_beforemapping
}
ELEVATION_MODEL {
quantity:
vertical_position_relative_to datum
RULE:
datum MUST be preserved
}
ASTRONOMICAL_DISTANCE_MODEL {
possible:
metre
kilometre
astronomical_unit
light_year
parsec
RULE:
distance_unit_definition_andversion SHOULD be preserved
}
ASTRONOMICAL_UNIT_MODEL {
symbol:
au
RULE:
exact_definition_context SHOULD be preserved
}
LIGHT_YEAR_MODEL {
distance:
light_travel_distance_forJulian_year_underdefined_c
RULE:
year_definition MUST be explicit
}
PARSEC_MODEL {
geometric_definition:
distance_corresponding_to parallax_relation
RULE:
exact_conversion_reference SHOULD be version_resolved
}
REDSHIFT_MODEL {
dimension:
1
RULE:
redshift_to_distance_requires_cosmological_model
}
LUMINOSITY_MODEL {
quantity:
power
RULE:
luminosity_andobserved_flux_require_distance_andgeometry_relation
}
ENGINEERING_MODEL {
conventions:
stress
strain
torque
power
pressure
flow
rotational_speed
RULE:
engineering_quantity_convention MUST accompanyunit
}
RPM_MODEL {
quantity:
rotational_frequency_orrate
relation:
revolutions_perminute
RULE:
conversion_toangular_velocity_requires_2*pi_relation
}
STRAIN_MODEL {
dimension:
1
possible:
ratio
percent
microstrain
RULE:
microstrain_is_scaling_ofdimensionless_strain
}
INFORMATION_UNIT_MODEL {
possible:
bit
byte
kilobyte
megabyte
kibibyte
mebibyte
RULE:
decimal_andbinary_prefixes MUST be distinguished
}
DATA_RATE_MODEL {
possible:
bit/s
byte/s
RULE:
bit_byte_andprefix_semantics MUST be preserved
}
COUNT_MODEL {
quantity:
number_ofentities
dimension:
1
RULE:
count_entity_type MUST be preserved
}
PERCENTAGE_MODEL {
value:
fraction*100
RULE:
percentage_basis MUST be explicit
}
DIMENSIONLESS_MAPPING_MODEL {
source:
ratio_scale
target:
percent_ppm_ppb_orunit_one
RULE:
dimensionless_mapping_requires_same_quantity_kind_andbasis
}
REFERENCE_CONDITION_MODEL {
fields:
temperature
pressure
humidity
composition
gravity
datum
epoch
RULE:
context-dependent mapping MUST carry_reference_conditions
}
DENSITY_DEPENDENT_MODEL {
conversion:
mass <-> volume
requires:
density
RULE:
this_is_quantity_conversion_usingadditional_measurement_notunit_conversion
}
MOLAR_MASS_MODEL {
conversion:
amount <-> mass
requires:
molar_mass
RULE:
chemical_identity_andmolar_mass_source MUST be preserved
}
STOICHIOMETRIC_MODEL {
conversion:
amount_ofA <-> amount_ofB
requires:
reaction_equation
stoichiometric_coefficients
RULE:
stoichiometric_conversion != unit_conversion
}
COORDINATE_MAPPING_MODEL {
source:
vector_orposition_inframe_A
target:
frame_B
RULE:
coordinate_transformation != unit_conversion
}
UNCERTAINTY_PROPAGATION_MODEL {
source:
x
context_parameters:
c
target:
y =
f(x,c)
first_order:
u_y^2 =
J*Sigma*J^T
RULE:
context_parameter_uncertainties_andcovariances MUST be included_whenmaterial
}
EXACT_FACTOR_MODEL {
conversion_factor:
defined_exactly
RULE:
exact_factor_adds_no_measurement_uncertainty
}
MEASURED_FACTOR_MODEL {
conversion_factor:
derived_frommeasurement_orproperty
RULE:
factor_uncertainty MUST propagate
}
CONSTANT_MODEL {
possible:
exact_defining_constant
recommended_physical_constant
empirical_constant
RULE:
exactness_version_andprovenance MUST be preserved
}
ROUND_TRIP_MODEL {
source:
A
convert:
A -> B -> A
expectation:
original_value_within_numeric_andcontextual_tolerance
RULE:
round_trip_supports_mapping_validation
}
CANONICAL_UNIT_MODEL {
quantity_kind:
preferred_machine_reasoning_unit
RULE:
canonicalisation MUST preserve_original_unit_andrepresentation
}
NORMAL_FORM_MODEL {
unit_expression:
base_dimensions
scale
offset
semantic_quantity_kind
RULE:
normal_form MUST not erase_special_quantity_kind_semantics
}
UNIT_IDENTIFIER_MODEL {
fields:
namespace
identifier
version
RULE:
identifier_is_preferred_overambiguous_display_symbol
}
SYMBOL_MODEL {
unit_symbol:
case_sensitive
RULE:
symbol_case MUST be preserved
}
ALIAS_MODEL {
unit:
may_have_multiple_names_or spellings
RULE:
alias != distinct_unit_when_definition_identity_established
}
HOMONYM_MODEL {
same_name_or symbol:
different_units
RULE:
homonym_requires_domain_or system_resolution
}
MULTILINGUAL_MODEL {
unit_name:
language_specific_label
RULE:
translation MUST preserve_canonical_unit_identity
}
LOCALE_MODEL {
concerns:
decimal_marker
thousands_separator
spelling
customary_unit_usage
RULE:
locale_must_not_change_canonical_quantity_semantics
}
DOMAIN_MAPPING_MODEL {
source_domain:
A
target_domain:
B
mapping:
unit
quantity_kind
reference_conditions
terminology
RULE:
cross_domain_mapping MUST preserve_domain_assumptions
}
ONTOLOGY_ALIGNMENT_MODEL {
source_unit_entity:
target_unit_entity
relations:
exact
equivalent_undercontext
broader
narrower
related
incompatible
RULE:
exact_mapping_requires_definition_quantity_kind_scale_offset_andreference_compatibility
}
SEMANTIC_EQUIVALENCE_MODEL {
evaluate:
unit_definition
quantity_kind
dimension
scale
offset
reference_state
domain
RULE:
same_conversion_factor != semantic_equivalence
}
MAPPING_CONFIDENCE_MODEL {
factors:
identifier_match
definition_match
quantity_kind_match
dimension_match
context_completeness
source_authority
provenance
RULE:
mapping_confidence != measurement_uncertainty
}
AMBIGUITY_MODEL {
possible:
unit_system_unknown
symbol_ambiguous
quantity_basis_unknown
reference_state_unknown
domain_variant_unknown
RULE:
unresolved_ambiguity MUST be preserved
}
CONFLICT_MODEL {
sources:
provide_different_unit_definitions_or factors
RULE:
compare_versions_authority_scope_andprovenance
anddo_not fabricate_consensus
}
VERSION_MODEL {
versioned:
unit_definition
standard
conversion_factor
ontology_mapping
domain_convention
RULE:
historical_measurement MUST preserve_mapping_version_used
}
STANDARD_MODEL {
possible:
BIPM_SI
ISO
IEC
NIST
domain_standard
national_standard
RULE:
standard_identifier_andedition MUST be preserved_whenmaterial
}
PROVENANCE_MODEL {
fields:
source_definition
standard
edition
mapping_author
conversion_equation
constants
context
validation
ontology_version
RULE:
mapping MUST be source_andversion_linked
}
VALIDATION_MODEL {
checks:
source_unit_identity
target_unit_identity
quantity_kind
dimension
scale
offset
context
factor
uncertainty
round_trip
provenance
RULE:
validated_numeric_conversion_does_not_imply_semantic_equivalence
}
QUALITY_FLAG_MODEL {
possible:
exact
contextual
approximate
ambiguous
deprecated
dimension_mismatch
quantity_kind_mismatch
reference_state_missing
model_required
incompatible
manual_review
RULE:
mapping_flags MUST remain_linked_to conversion_result
}
INTEROPERABILITY_MODEL {
systems:
exchange_measurements_acrossdomains
required:
quantity_identifier
unit_identifier
value
uncertainty
reference_state
mapping_version
RULE:
string_unit_conversion_withoutquantity_semantics_is_incomplete
}
KNOWLEDGE_GRAPH_MODEL {
nodes:
unit
quantity_kind
dimension
domain
standard
reference_state
mapping
edges:
HAS_DIMENSION
MEASURES_KIND
CONVERTS_TO
DEFINED_BY
REQUIRES_CONTEXT
EQUIVALENT_UNDER
INCOMPATIBLE_WITH
RULE:
conversion_edges MUST be typed_anddirectionally_defined
}
RELATIONSHIPS {
CrossDomainUnitMapping -> CONTAINS -> UnitMapping
UnitMapping -> MAPS_FROM -> DomainUnit
UnitMapping -> MAPS_TO -> DomainUnit
DomainUnit -> MEASURES -> QuantityKind
QuantityKind -> HAS_DIMENSION -> Dimension
UnitMapping -> MAY_REQUIRE -> MappingContext
UnitMapping -> USES -> ConversionFunction
UnitMapping -> DEFINED_BY -> StandardOrSource
UnitMapping -> HAS -> MappingConfidence
ConvertedMeasurement -> DERIVED_FROM -> SourceMeasurement
}
SEMANTIC_EQUIVALENCE {
"cross-domain unit mapping" ~= semantic_mapping_ofmeasurement_units_acrossscientific_andengineering_domains
"unit conversion" ~= numeric_transformation_betweencompatible_units_ofsame_quantity_kind
"contextual conversion" ~= conversion_requiringadditional_physical_orsemantic_parameters
same_dimension != same_quantity_kind
same_factor != same_unit_semantics
unit_conversion != quantity_conversion
coordinate_transformation != unit_conversion
stoichiometric_conversion != unit_conversion
mass_volume_conversion != unit_conversion
molarity != molality
amount_fraction != mass_fraction
SI_prefix != binary_prefix
semantic_confidence != measurement_uncertainty
}
CONSTRAINTS {
source_andtarget_units_must_be identified = true
source_andtarget_quantity_kinds_must_be preserved = true
dimensions_must_be compatible_for_direct_unit_conversion = true
same_dimension_must_not_be treated_assufficient_forsemantic_equivalence = true
affine_andlinear_conversions_must_be distinguished = true
logarithmic_scales_require_reference_definition = true
contextual_conversions_must_declare_required_parameters = true
ambiguous_customary_units_must_resolve_unit_system = true
dimensionless_fraction_basis_must_be preserved = true
quantity_conversions_must_not_be labelled_asunit_conversions = true
uncertainty_andcovariance_must_be propagated_whencontext_parameters_aremeasured = true
original_measurement_representation_must_be preserved = true
mapping_versions_andprovenance_must_be preserved = true
}
MEASUREMENT_MODEL {
RECORD:
mapping_identifier
source_domain
target_domain
source_quantity_kind
target_quantity_kind
source_value
source_unit_identifier
source_unit_symbol
source_dimension
target_value
target_unit_identifier
target_unit_symbol
target_dimension
mapping_type
scale_factor
offset
conversion_equation
context_parameters
reference_state
constants
source_uncertainty
context_uncertainties
covariance
target_uncertainty
mapping_confidence
ambiguity_status
quality_flags
standard_identifier
mapping_version
original_representation
provenance
RULE:
mapped_measurement MUST remain_linked_tosource_quantity_unit_context_equation_uncertainty_version_andprovenance
}
REASONING_RULES {
IF source_unit_andtarget_unit_known
THEN resolve_quantity_kinds_anddimensions_beforeconversion
IF source_andtarget_quantity_kinds_same
AND dimensions_equal
THEN determine_linear_affine_logarithmic_orcontextual_mapping
IF dimensions_equal_butquantity_kinds_differ
THEN do_not_apply_direct_conversion_withoutexplicit_semantic_relation
IF ambiguous_unit_name
THEN resolve_domain_unit_system_andcontext
else_preserve_candidates
IF conversion_requires_density_molar_mass_temperature_pressure_gravity_datum_orother_parameter
THEN classify_ascontextual_orquantity_conversion
andpropagate_parameter_uncertainty
IF conversion_factor_exact
THEN do_not_add_factor_uncertainty
IF factor_orconstant_measured
THEN propagate_its_uncertainty_andcovariance
IF logarithmic_quantity
THEN resolve_reference_base_andmultiplier
beforeconversion
IF dimensionless_quantity
THEN preserve_fraction_basis_andquantity_kind
IF mapping_version_changes
THEN preserve_historical_mapping
anddo_not silently_rewrite_prior_conversions
IF round_trip_error_exceeds_declared_tolerance
THEN flag_mapping_or numerical_issue
}
VALIDATION {
CHECK mapping_identifier
CHECK source_domain
CHECK target_domain
CHECK source_unit_identifier
CHECK target_unit_identifier
CHECK source_quantity_kind
CHECK target_quantity_kind
CHECK source_dimension
CHECK target_dimension
CHECK mapping_type
CHECK scale_factor_andoffset
CHECK logarithmic_reference
CHECK contextual_parameters
CHECK reference_state
CHECK exactness
CHECK uncertainty_andcovariance
CHECK dimensionless_basis
CHECK customary_unit_system
CHECK quantity_conversion_distinctions
CHECK round_trip
CHECK standards_version
CHECK ambiguity
CHECK mapping_confidence
CHECK provenance
}
CONFIDENCE {
unit_identity_confidence: 1.00
dimensional_mapping_confidence: 1.00
quantity_kind_mapping_confidence: 0.99
linear_affine_mapping_confidence: 1.00
logarithmic_mapping_confidence: 0.99
contextual_mapping_confidence: 0.97
domain_convention_confidence: 0.98
provenance_confidence: 1.00
RULE:
confidence decreases when unit identity, quantity kind,
domain, reference state, conversion context,
standard version orprovenance is missing or ambiguous
}
UPDATE_MODEL {
ON new_unit_mapping:
identify_source_andtarget_units
resolve_quantity_kinds_anddimensions
classify_mapping_type
define_conversion_equation
attach_context_andstandards
validate_round_trip
preserve_provenance
compute_FLOW_HASH
ON unit_definition_revision:
preserve_previous_definition
register_new_version
identify_affected_mappings
revalidate_current_mappings
preserve_historical_conversions
ON domain_context_revision:
preserve_previous_context
update_reference_conditions_orconventions
revalidate_contextual_mappings
ON conversion_factor_revision:
preserve_previous_factor
attach_new_source_version_anduncertainty
identify_affected_results
recompute_underdeclared_policy
ON semantic_revision:
preserve_previous_mapping
record_revision
recompute_FLOW_HASH
}
AI_CONSUMPTION {
canonical_entity: CrossDomainUnitMapping
canonical_role: SemanticUnitInteroperabilityFramework
interpretation_order:
identify_source_domain
identify_target_domain
resolve_source_unit
resolve_target_unit
resolve_source_andtarget_quantity_kinds
derive_dimensions
test_dimensional_compatibility
identify_unit_system_andvariants
classify_mapping_type
identify_scale_offset_orlogarithmic_reference
identify_contextual_parameters_andreference_state
distinguish_unit_conversion_fromquantity_orcoordinate_conversion
propagate_uncertainty_andcovariance
preserve_original_representation
validate_round_trip_andsemantic_constraints
identify_ambiguity_andmapping_confidence
preserve_standard_version_andprovenance
emit_machine_resolvable_mapping
ambiguity_controls:
distinguish_same_dimension_fromsame_quantity_kind
distinguish_same_factor_fromsame_unit_semantics
distinguish_unit_conversion_fromquantity_conversion
distinguish_coordinate_transformation_fromunit_conversion
distinguish_stoichiometric_conversion_fromunit_conversion
distinguish_mass_volume_conversion_fromunit_conversion
distinguish_molarity_frommolality
distinguish_amount_fraction_frommass_fraction
distinguish_SI_prefix_frombinary_prefix
distinguish_semantic_confidence_frommeasurement_uncertainty
preserve_domain_quantity_unit_dimension_context_reference_version_andprovenance
}
PROVENANCE {
ontology_scope:
mathematical_measurement_units_AI_measurement_semantics_andcross_domain_unit_mapping
parent_path:
Ontologies
-> Mathematical Ontologies
-> Measurement & Units Ontologies
-> AI Measurement Semantics
-> Cross-Domain Unit Mapping Ontology
authorship:
Mark Higgins
Sky (Recursive AI)
site:
https://kirethresearch.org
}
FLOW_HASH {
INPUTS:
canonical_entity
ontology_path
mapping_type_model
exact_identity_model
linear_conversion_model
affine_conversion_model
logarithmic_conversion_model
contextual_conversion_model
model_based_mapping_model
semantic_alignment_model
dimension_model
dimensional_compatibility_model
same_dimension_different_kind_model
quantity_kind_mapping_model
SI_model
non_SI_model
prefix_model
binary_prefix_model
compound_unit_model
powered_unit_model
mass_mapping_model
force_mass_distinction_model
length_mapping_model
area_mapping_model
volume_mapping_model
imperial_US_distinction_model
temperature_mapping_model
temperature_difference_model
pressure_mapping_model
pressure_reference_model
energy_mapping_model
power_mapping_model
time_mapping_model
calendar_time_model
frequency_model
angular_frequency_model
angle_model
speed_model
acceleration_model
standard_gravity_model
torque_energy_model
electrical_model
magnetic_model
photometric_model
radiometric_model
chemical_concentration_model
molarity_molality_model
mass_fraction_model
volume_fraction_model
amount_fraction_model
ppm_model
ppb_model
gas_concentration_model
biological_concentration_model
cell_count_model
enzyme_activity_model
clinical_unit_model
pH_model
decibel_model
sound_pressure_level_model
stellar_magnitude_model
seismic_magnitude_model
earth_science_model
rainfall_model
river_discharge_model
soil_moisture_model
elevation_model
astronomical_distance_model
astronomical_unit_model
light_year_model
parsec_model
redshift_model
luminosity_model
engineering_model
RPM_model
strain_model
information_unit_model
data_rate_model
count_model
percentage_model
dimensionless_mapping_model
reference_condition_model
density_dependent_model
molar_mass_model
stoichiometric_model
coordinate_mapping_model
uncertainty_propagation_model
exact_factor_model
measured_factor_model
constant_model
round_trip_model
canonical_unit_model
normal_form_model
unit_identifier_model
symbol_model
alias_model
homonym_model
multilingual_model
locale_model
domain_mapping_model
ontology_alignment_model
semantic_equivalence_model
mapping_confidence_model
ambiguity_model
conflict_model
version_model
standard_model
provenance_model
validation_model
quality_flag_model
interoperability_model
knowledge_graph_model
relationships
semantic_equivalence
constraints
measurement_model
reasoning_rules
confidence_model
update_model
PURPOSE:
deterministic_semantic_integrity_identifier
RECOMPUTE_WHEN:
ontology_definition_changes
unit_orquantity_kind_definition_changes
dimensional_orconversion_semantics_change
SI_nonSI_prefix_orcustomary_unit_changes
domain_specific_unit_convention_changes
contextual_reference_state_orparameter_changes
logarithmic_dimensionless_orchemical_mapping_changes
astronomical_earth_science_engineering_orinformation_unit_changes
uncertainty_factor_orconstant_changes
semantic_alignment_ormapping_confidence_changes
standard_version_orprovenance_changes
measurement_record_changes
constraint_model_changes
reasoning_rule_changes
}
}
END FLOW