Unit Conversion Ontology
Measurement Mathematics
Authors: MArk Anthony Higgins - Sky Recursive Ai
Revised Date: 16 September 2026
Audio Overview
# Unit Conversion Ontology — Flow Algebra
URL: https://kirethresearch.org/booksai-core/ontologies/mathematical-ontologies/measurement-units-ontologies/measurement-mathematics/unit-conversion-ontology.html
FLOW UnitConversionOntology {
DOMAIN:
Mathematical Ontologies
-> Measurement & Units Ontologies
-> Measurement Mathematics
-> Unit Conversion Ontology
PURPOSE:
Represent unit conversion as a mathematically valid transformation of the numerical representation of a quantity from one unit to another while preserving the underlying quantity. The ontology models linear, affine, multiplicative, reciprocal, logarithmic and context-dependent conversions; SI prefixes; coherent and non-coherent units; compound units; powers and roots; temperature scales; angular units; time, area, volume, speed, pressure, energy and other derived-unit transformations; exact and experimentally determined conversion factors; uncertainty propagation; dimensional validation; significant figures; provenance; parsing; formatting; and machine-consumable reasoning while preventing conversions between dimensionally incompatible quantities.
ENTITY UnitConversion {
TYPE: QuantityRepresentationTransformation
DEFINITION:
transformation_of_quantity_value_representation
from_source_unit_to_target_unit
such_that_underlying_quantity_is_preserved
PROPERTIES:
has_source_unit
has_target_unit
has_conversion_function
preserves_quantity
preserves_dimension
may_change_numerical_value
may_use_exact_factor
may_use_offset
may_have_context
may_propagate_uncertainty
has_provenance
}
ENTITY SourceUnit {
TYPE: MeasurementUnit
}
ENTITY TargetUnit {
TYPE: MeasurementUnit
}
ENTITY ConversionFactor {
TYPE: ScaleParameter
PROPERTIES:
numerical_value
exactness
uncertainty_when_inexact
source
}
ENTITY ConversionOffset {
TYPE: AffineParameter
PROPERTIES:
numerical_value
unit_context
exactness
uncertainty_when_inexact
}
QUANTITY_PRESERVATION_MODEL {
source:
Q =
x_s*u_s
target:
Q =
x_t*u_t
equality:
x_s*u_s =
x_t*u_t
RULE:
conversion_changes_representation_not_underlying_quantity
}
DIMENSION_MODEL {
source_dimension:
D_s
target_dimension:
D_t
REQUIRE:
D_s =
D_t
for_direct_unit_conversion
RULE:
dimensionally_incompatible_units MUST_NOT be_directly_converted
}
QUANTITY_KIND_MODEL {
same_dimension:
does_not_always_imply_same_quantity_kind
examples:
torque_and_energy
frequency_and_activity
RULE:
quantity_kind_semantics SHOULD be checked_in_addition_to_dimension
}
LINEAR_CONVERSION_MODEL {
target_value:
x_t =
k*x_s
inverse:
x_s =
x_t/k
WHEN k != 0
RULE:
factor_direction MUST be explicit
}
EXACT_FACTOR_MODEL {
factor:
defined_exactly
uncertainty:
zero_from_conversion_factor_definition
RULE:
exact_conversion_factor_does_not_add_measurement_uncertainty
}
INEXACT_FACTOR_MODEL {
factor:
experimentally_determined_or_context_dependent
uncertainty:
u(k) > 0
potentially
RULE:
factor_uncertainty MUST be propagated
}
AFFINE_CONVERSION_MODEL {
target:
x_t =
a*x_s+b
inverse:
x_s =
(x_t-b)/a
WHEN a != 0
RULE:
affine_conversion_is_not_pure_scale_conversion
}
TEMPERATURE_SCALE_MODEL {
Celsius_to_kelvin:
T_K =
t_C+273.15
kelvin_to_Celsius:
t_C =
T_K-273.15
Celsius_to_Fahrenheit:
t_F =
(9/5)*t_C+32
Fahrenheit_to_Celsius:
t_C =
(5/9)*(t_F-32)
Fahrenheit_to_kelvin:
T_K =
(5/9)*(t_F-32)+273.15
RULE:
absolute_temperature_and_temperature_difference_require_distinct_conversion_semantics
}
TEMPERATURE_DIFFERENCE_MODEL {
delta_K =
delta_Celsius
delta_Fahrenheit =
(9/5)*delta_Celsius
RULE:
additive_offsets_do_not_apply_to_temperature_differences
}
PREFIX_MODEL {
SI_prefix:
scales_unit_by_power_of_ten
examples:
kilo = 10^3
mega = 10^6
milli = 10^-3
micro = 10^-6
nano = 10^-9
RULE:
prefix_factor_applies_to_unit_before_power_handling
}
PREFIX_CONVERSION_MODEL {
source_prefix_power:
p_s
target_prefix_power:
p_t
numeric:
x_t =
x_s*10^(p_s-p_t)
RULE:
quantity_and_base_unit_remain_same
}
BINARY_PREFIX_MODEL {
possible:
kibi = 2^10
mebi = 2^20
gibi = 2^30
tebi = 2^40
RULE:
binary_prefixes MUST be distinguished_from_decimal_SI_prefixes
}
COMPOUND_UNIT_MODEL {
source:
product_and_quotient_of_units
target:
equivalent_compound_unit
process:
decompose
convert_components
combine_scale_factors
RULE:
exponent_of_each_unit_component MUST be preserved
}
POWERED_UNIT_MODEL {
if:
u_t =
k*u_s
then_for_power_n:
u_t^n =
k^n*u_s^n
RULE:
area_and_volume_conversion_factors_require_squared_or_cubed_scale
}
AREA_CONVERSION_MODEL {
length_factor:
k
area_factor:
k^2
example:
1_m =
100_cm
therefore:
1_m^2 =
10000_cm^2
RULE:
do_not_apply_linear_length_factor_directly_to_area
}
VOLUME_CONVERSION_MODEL {
length_factor:
k
volume_factor:
k^3
example:
1_m^3 =
1000000_cm^3
}
RECIPROCAL_UNIT_MODEL {
source:
1/u_s
if:
u_t =
k*u_s
then:
1/u_t =
(1/k)*(1/u_s)
RULE:
reciprocal_units_invert_scale_factor
}
RATE_UNIT_MODEL {
source:
A_per_B
target:
C_per_D
conversion:
numerator_factor/denominator_factor
RULE:
numerator_and_denominator_factors MUST be applied_separately
}
SPEED_MODEL {
metres_per_second_to_kilometres_per_hour:
x_kmh =
3.6*x_ms
kilometres_per_hour_to_metres_per_second:
x_ms =
x_kmh/3.6
RULE:
factor_results_from_length_and_time_unit_conversions
}
FREQUENCY_PERIOD_MODEL {
frequency:
f =
1/T
RULE:
conversion_between_frequency_and_period_is_quantity_transformation
not_simple_unit_conversion
}
ANGLE_MODEL {
radians_to_degrees:
deg =
rad*180/pi
degrees_to_radians:
rad =
deg*pi/180
RULE:
pi_is_exact_mathematical_constant
}
ARC_MINUTE_SECOND_MODEL {
1_degree =
60_arcminutes
1_arcminute =
60_arcseconds
RULE:
angular_units_are_not_time_units_despite_shared_minute_second_terms
}
TIME_UNIT_MODEL {
exact_common:
1_minute =
60_seconds
1_hour =
3600_seconds
1_day =
86400_seconds
under_conventional_day_duration_context
RULE:
calendar_month_and_year_conversions_are_context_dependent
}
CALENDAR_DURATION_MODEL {
month:
variable_number_of_days
year:
may_be_365_or_366_days_in_Gregorian_calendar
RULE:
calendar_duration_conversion_requires_date_calendar_and_context
}
MASS_MODEL {
source_and_target:
compatible_mass_units
RULE:
mass_and_weight_force MUST be distinguished
}
MASS_FORCE_DISTINCTION_MODEL {
mass:
dimension_M
force:
dimension_M*L*T^-2
relation:
F =
m*g
RULE:
converting_mass_to_force_requires_gravitational_model
and_is_not_unit_conversion
}
PRESSURE_MODEL {
pressure:
force/area
possible_units:
Pa
kPa
MPa
bar
mbar
psi
atm
torr
RULE:
conversion_factor_exactness_depends_on_unit_definition
}
ENERGY_MODEL {
possible_units:
joule
kilojoule
watt_hour
kilowatt_hour
electronvolt
RULE:
energy_and_torque_share_dimension_but_are_distinct_quantity_kinds
}
POWER_MODEL {
power:
energy/time
possible_units:
watt
kilowatt
horsepower_variant
RULE:
horsepower_unit_variant MUST be identified
}
FORCE_MODEL {
possible:
newton
kilonewton
pound_force
RULE:
pound_force_and_pound_mass MUST be distinguished
}
LENGTH_MODEL {
possible:
metre
kilometre
centimetre
millimetre
inch
foot
yard
mile
nautical_mile
RULE:
conversion_source_definition MUST be preserved
}
VOLUME_CAPACITY_MODEL {
possible:
cubic_metre
litre
millilitre
cubic_centimetre
gallon
pint
RULE:
imperial_and_US_customary_volume_units MUST be disambiguated
}
LITRE_MODEL {
exact:
1_L =
1_dm^3
=
10^-3_m^3
RULE:
litre_symbol_and_prefix_semantics MUST be preserved
}
DENSITY_MODEL {
density:
mass/volume
conversion:
combine_mass_and_volume_scale_factors
RULE:
quantity_basis_must_remain_same
}
CONCENTRATION_MODEL {
possible:
mol_per_litre
mol_per_cubic_metre
mass_per_volume
amount_fraction
mass_fraction
RULE:
different_concentration_kinds_are_not_interconvertible_without_composition_density_or_molar_mass_information
}
MOLAR_MASS_MODEL {
relation:
mass =
amount_of_substance*molar_mass
RULE:
converting_mass_concentration_to_molar_concentration_requires_molar_mass_and_possible_density_or_volume_context
}
LOGARITHMIC_UNIT_MODEL {
examples:
decibel
neper
pH_related_scale
RULE:
logarithmic_quantity_conversion_requires_reference_and_definition
not_simple_linear_unit_factor
}
DECIBEL_MODEL {
power_level:
L =
10*log10(P/P_ref)
amplitude_level:
L =
20*log10(A/A_ref)
under_squared_power_relation
RULE:
reference_quantity_and_ratio_type MUST be defined
}
ABSOLUTE_LOG_LEVEL_MODEL {
examples:
dBm
dBW
RULE:
absolute_logarithmic_level_includes_reference_power
and_must_not_be_treated_as_dimensionless_dB_only
}
PH_MODEL {
pH:
logarithmic_measure_related_to_hydrogen_ion_activity
RULE:
pH_to_concentration_is_not_simple_unit_conversion
and_requires_chemical_activity_model
}
DIMENSIONLESS_UNIT_MODEL {
possible:
percent
ppm
ppb
radian
steradian
RULE:
dimensionless_quantities_can_have_distinct_semantics_and_named_units
}
PERCENT_MODEL {
percent_to_fraction:
x_fraction =
x_percent/100
fraction_to_percent:
x_percent =
100*x_fraction
}
PPM_MODEL {
ppm_to_fraction:
x =
ppm*10^-6
under_dimensionless_fraction_context
RULE:
ppm_by_mass_volume_or_mole MUST be disambiguated
}
COUNT_UNIT_MODEL {
counts:
dimensionless_but_semantically_discrete
RULE:
count_rate_and_activity_units MUST not_be conflated
}
CURRENCY_DISTINCTION_MODEL {
currency_conversion:
uses_time_dependent_exchange_rate
RULE:
currency_conversion_is_not_metrological_unit_conversion_in_measurement_ontology
}
CONTEXT_DEPENDENT_MODEL {
conversions:
require_additional_parameters
examples:
standard_cubic_volume
gas_flow
mass_to_volume
wet_to_dry_basis
gauge_to_absolute_pressure
RULE:
context_parameters MUST be explicit
}
STANDARD_CONDITION_MODEL {
gas_volume:
depends_on_temperature_pressure_and_composition
RULE:
standard_or_normal_conditions MUST be identified
}
GAUGE_ABSOLUTE_PRESSURE_MODEL {
P_absolute =
P_gauge+P_atmospheric
RULE:
atmospheric_pressure_is_contextual_input
not_unit_conversion_factor
}
UNIT_SYMBOL_MODEL {
symbol:
formal_unit_representation
RULE:
symbol_case_is_significant
}
UNIT_NAME_MODEL {
name:
textual_unit_name
RULE:
parser SHOULD distinguish_symbol_from_free_text_name
}
PREFIX_PARSING_MODEL {
token:
prefix+unit_symbol
RULE:
parser MUST resolve_longest_valid_unit_structure_without_ambiguous_double_prefixing
}
COMPOUND_PARSING_MODEL {
possible:
m/s
kg*m/s^2
W/(m*K)
mol/L
RULE:
multiplication_division_parentheses_and_exponents MUST be parsed structurally
}
CANONICAL_UNIT_MODEL {
quantity_kind:
may_have_preferred_canonical_unit
conversion:
source -> canonical -> target
possible_implementation
RULE:
chained_conversion_must_not_introduce_rounding_error_if_direct_exact_factor_available
}
SI_COHERENT_MODEL {
coherent_unit:
derived_without_additional_numerical_factor_from_base_units
RULE:
coherence_is_property_of_unit_system_not_measurement_accuracy
}
BASE_UNIT_DECOMPOSITION_MODEL {
target:
express_derived_unit_in_base_units
examples:
N =
kg*m*s^-2
Pa =
kg*m^-1*s^-2
RULE:
derived_and_base_unit_forms_may_be_semantically_equivalent_for_same_quantity
}
CONVERSION_GRAPH_MODEL {
nodes:
units
edges:
conversion_functions
properties:
exactness
uncertainty
domain
context
source
RULE:
path_selection SHOULD prefer_valid_exact_low_complexity_conversion_when_equivalent
}
PATH_COMPOSITION_MODEL {
A_to_B:
f
B_to_C:
g
A_to_C:
g(f(x))
RULE:
composed_conversion_must_preserve_context_and_uncertainty
}
INVERSE_MODEL {
forward:
y =
f(x)
inverse:
x =
f^-1(y)
RULE:
conversion_should_be_invertible_over_declared_domain_for_bidirectional_unit_mapping
}
ROUND_TRIP_MODEL {
source:
x
convert:
source_to_target_to_source
expectation:
recover_original_value_within_numeric_rounding_and_inexact_factor_uncertainty
RULE:
round_trip_test_supports_conversion_validation
}
UNCERTAINTY_PROPAGATION_MODEL {
linear_exact:
u_y =
abs(k)*u_x
affine_exact:
u_y =
abs(a)*u_x
uncertain_factor:
y =
k*x
variance_first_order:
u_y^2 =
k^2*u_x^2
+x^2*u_k^2
+2*k*x*cov(x,k)
RULE:
conversion_parameter_uncertainty MUST be included_when_inexact
}
RELATIVE_UNCERTAINTY_MODEL {
exact_nonzero_scale:
relative_uncertainty_preserved
u_y/abs(y) =
u_x/abs(x)
WHEN y=k*x
AND k_exact_nonzero
AND x_nonzero
}
COVARIANCE_MODEL {
multiple_values:
converted_by_common_uncertain_factor
RULE:
shared_factor_uncertainty_creates_covariance_between_converted_results
}
SIGNIFICANT_FIGURES_MODEL {
exact_conversion:
does_not_reduce_significant_information
RULE:
final_reporting_should_reflect_original_measurement_uncertainty_not_number_of_digits_in_exact_factor
}
ROUNDING_MODEL {
internal:
retain_sufficient_precision
final:
round_under_declared_reporting_policy
RULE:
avoid_rounding_at_each_conversion_step
}
SCIENTIFIC_NOTATION_MODEL {
numeric:
may_be_rescaled_with_unit_conversion
RULE:
scientific_exponent_and_unit_prefix_must_not_be_double_applied
}
OVERFLOW_MODEL {
machine:
converted_numeric_value_may_exceed_format_range
RULE:
use_scaled_or_arbitrary_precision_representation_when_needed
}
UNDERFLOW_MODEL {
machine:
very_small_converted_value_may_underflow
RULE:
underflow != physical_zero
}
EXACTNESS_MODEL {
conversion_relation:
exact
conventional_exact
measured
approximate
context_dependent
RULE:
exactness_status MUST be preserved
}
PROVENANCE_MODEL {
conversion_factor_source:
SI_definition
legal_definition
standard
reference_database
experimental_measurement
user_defined
RULE:
nontrivial_or_inexact_conversion_source SHOULD be recorded
}
VERSION_MODEL { conversion_definition:
may_change_if_legal_or_conventional_definition_revised
RULE:
version_and_effective_date SHOULD be preserved
}
LOCALE_MODEL {
decimal_separator:
locale_dependent
thousands_separator:
locale_dependent
RULE:
machine_conversion_input SHOULD use_unambiguous_numeric_parsing
}
FORMAT_MODEL {
output:
numerical_value
unit_symbol
uncertainty
significant_figures
RULE:
formatting_is_separate_from_conversion_mathematics
}
VALIDATION_MODEL {
tests:
dimension_compatibility
quantity_kind_compatibility
known_reference_pairs
inverse_conversion
round_trip
boundary_values
zero
negative_values
uncertainty_scaling
RULE:
conversion_library SHOULD include_automated_validation
}
RELATIONSHIPS {
UnitConversion -> HAS_SOURCE -> SourceUnit
UnitConversion -> HAS_TARGET -> TargetUnit
UnitConversion -> USES -> ConversionFunction
ConversionFactor -> SCALES -> NumericalValue
ConversionOffset -> SHIFTS -> NumericalValue
Unit -> HAS -> Dimension
Unit -> REPRESENTS -> QuantityKind
SIPrefix -> SCALES -> Unit
CompoundUnit -> COMPOSED_OF -> UnitFactors
UnitConversion -> PRESERVES -> UnderlyingQuantity
ConversionParameterUncertainty -> CONTRIBUTES_TO -> OutputUncertainty
}
SEMANTIC_EQUIVALENCE {
"unit conversion" ~= transformation_between_equivalent_quantity_unit_representations
"conversion factor" ~= multiplicative_scale_factor WHEN linear_conversion_context
unit_conversion != quantity_transformation
unit_conversion != dimensional_analysis
unit_conversion != unit_definition
temperature_value_conversion != temperature_difference_conversion
mass_to_force != unit_conversion
frequency_to_period != unit_conversion
gauge_to_absolute_pressure != pure_unit_conversion
currency_conversion != metrological_unit_conversion
exact_conversion_factor != measured_quantity
}
CONSTRAINTS {
source_unit_must_be_defined = true
target_unit_must_be_defined = true
source_and_target_dimensions_must_match_for_direct_conversion = true
quantity_kind_compatibility_should_be_validated = true
conversion_direction_must_be_defined = true
affine_and_linear_conversions_must_be_distinguished = true
powered_units_must_apply_factor_exponent = true
temperature_values_and_temperature_differences_must_be_distinguished = true
exact_and_inexact_conversion_parameters_must_be_distinguished = true
context_dependent_conversions_require_context_parameters = true
conversion_must_preserve_underlying_quantity = true
provenance_should_be_preserved_for_nontrivial_conversion_relations = true
}
MEASUREMENT_MODEL {
RECORD:
quantity_identifier
quantity_kind
source_value
source_unit
source_dimension
target_value
target_unit
target_dimension
conversion_type
conversion_factor
conversion_offset
parameter_exactness
parameter_uncertainty
context_parameters
source_uncertainty
target_uncertainty
covariance
significant_figures
rounding_mode
conversion_source
conversion_version
original_representation
final_representation
provenance
RULE:
converted_value MUST remain_linked_to_source_value_conversion_relation_and_uncertainty
}
REASONING_RULES {
IF source_and_target_dimensions_differ
THEN reject_direct_unit_conversion
IF dimensions_match_but_quantity_kinds_are_semantically_incompatible
THEN require_explicit_quantity_transformation_model
IF linear_conversion_factor_known
THEN target_value =
factor*source_value
IF affine_conversion_known
THEN target_value =
scale*source_value+offset
IF converting_powered_unit
THEN raise_linear_unit_factor_to_unit_exponent
IF converting_compound_unit
THEN decompose_components
apply_each_factor_with_exponent
recombine_total_scale
IF exact_scale_factor
THEN target_uncertainty =
abs(factor)*source_uncertainty
without_new_factor_uncertainty
IF factor_uncertain
THEN propagate_source_and_factor_uncertainty
including_covariance
IF converting_temperature_difference
THEN do_not_apply_absolute_temperature_offset
IF SI_prefix_conversion
THEN apply_difference_in_prefix_powers
IF calendar_month_or_year_requested
THEN require_calendar_and_date_context_before_exact_duration_conversion
IF mass_to_force_requested
THEN route_to_physical_relation_F=m*g
rather_than_direct_unit_conversion
IF frequency_to_period_requested
THEN route_to_reciprocal_quantity_relation
rather_than_direct_unit_conversion
IF multiple_conversions_chained
THEN preserve_full_internal_precision
and_round_only_at_final_reporting_stage
IF round_trip_conversion_performed
THEN compare_returned_value_to_original_with_numeric_and_parameter_uncertainty_tolerance
}
VALIDATION {
CHECK source_unit
CHECK target_unit
CHECK quantity_kind
CHECK dimensions
CHECK conversion_type
CHECK factor_direction
CHECK factor_exactness
CHECK affine_offset
CHECK powered_unit_exponents
CHECK compound_unit_structure
CHECK SI_and_binary_prefixes
CHECK temperature_value_vs_difference
CHECK context_dependent_parameters
CHECK logarithmic_reference
CHECK uncertainty_propagation
CHECK covariance_from_shared_factors
CHECK significant_figures
CHECK rounding
CHECK inverse_conversion
CHECK round_trip_consistency
CHECK provenance
}
CONFIDENCE {
quantity_preservation_confidence: 1.00
dimensional_validation_confidence: 1.00
linear_conversion_confidence: 1.00
affine_conversion_confidence: 1.00
SI_prefix_confidence: 1.00
compound_unit_confidence: 1.00
uncertainty_propagation_confidence: 0.99
context_dependent_conversion_confidence: 0.98
RULE:
confidence decreases when quantity kind, unit definition, exactness,
context parameters, conversion source, uncertainty
or provenance is missing or ambiguous
}
UPDATE_MODEL {
ON new_conversion_request:
identify_quantity_kind
parse_source_value_and_unit
identify_target_unit
validate_dimensions
resolve_conversion_relation
identify_exactness_and_context
convert_value
propagate_uncertainty
format_result
preserve_provenance
ON conversion_definition_revision:
preserve_previous_relation
update_factor_offset_function_source_and_effective_date
create_new_version
recompute_affected_results_when_policy_allows
ON unit_definition_revision:
preserve_historical_unit_definition
update_conversion_graph
validate_inverse_and_round_trip_paths
prevent_reinterpretation_of_historical_values_without_version_context
ON uncertainty_revision:
preserve_converted_value_relation
update_source_or_parameter_uncertainty
recompute_target_uncertainty
preserve_covariance
ON formatting_revision:
preserve_underlying_converted_value
update significant_figures_rounding_or_notation
regenerate_representation_without_recomputing_quantity
ON semantic_revision:
preserve_previous_definition
record_revision
recompute_FLOW_HASH
}
AI_CONSUMPTION {
canonical_entity: UnitConversion
canonical_role: QuantityRepresentationTransformation
interpretation_order:
identify_quantity_kind
identify_source_value_and_unit
identify_source_dimension
identify_target_unit_and_dimension
validate_quantity_kind_compatibility
identify_linear_affine_logarithmic_or_context_dependent_conversion
identify_factor_offset_and_exactness
identify_compound_or_powered_unit_structure
identify_context_parameters
identify_source_uncertainty_and_covariance
identify_significant_figures_and_rounding
identify_conversion_source_and_version
identify_provenance
perform_conversion
validate_quantity_preservation
ambiguity_controls:
distinguish_unit_conversion_from_quantity_transformation
distinguish_unit_conversion_from_dimensional_analysis
distinguish_temperature_value_from_temperature_difference
distinguish_mass_from_force
distinguish_frequency_from_period
distinguish_gauge_from_absolute_pressure
distinguish_decimal_SI_prefixes_from_binary_prefixes
distinguish_exact_conversion_factor_from_measured_parameter
distinguish_formatting_from_conversion_mathematics
preserve_quantity_kind_source_target_factor_exactness_context_uncertainty_version_and_provenance
}
PROVENANCE {
ontology_scope:
mathematical_measurement_units_measurement_mathematics_and_unit_conversion_semantics
parent_path:
Ontologies
-> Mathematical Ontologies
-> Measurement & Units Ontologies
-> Measurement Mathematics
-> Unit Conversion Ontology
authorship:
Mark Higgins
Sky (Recursive AI)
site:
https://kirethresearch.org
}
FLOW_HASH {
INPUTS:
canonical_entity
ontology_path
quantity_preservation_model
dimension_model
quantity_kind_model
linear_conversion_model
exact_factor_model
inexact_factor_model
affine_conversion_model
temperature_scale_model
temperature_difference_model
prefix_model
prefix_conversion_model
binary_prefix_model
compound_unit_model
powered_unit_model
area_conversion_model
volume_conversion_model
reciprocal_unit_model
rate_unit_model
speed_model
frequency_period_model
angle_model
arc_minute_second_model
time_unit_model
calendar_duration_model
mass_model
mass_force_distinction_model
pressure_model
energy_model
power_model
force_model
length_model
volume_capacity_model
litre_model
density_model
concentration_model
molar_mass_model
logarithmic_unit_model
decibel_model
absolute_log_level_model
pH_model
dimensionless_unit_model
percent_model
ppm_model
count_unit_model
currency_distinction_model
context_dependent_model
standard_condition_model
gauge_absolute_pressure_model
unit_symbol_model
unit_name_model
prefix_parsing_model
compound_parsing_model
canonical_unit_model
SI_coherent_model
base_unit_decomposition_model
conversion_graph_model
path_composition_model
inverse_model
round_trip_model
uncertainty_propagation_model
relative_uncertainty_model
covariance_model
significant_figures_model
rounding_model
scientific_notation_model
overflow_model
underflow_model
exactness_model
provenance_model
version_model
locale_model
format_model
validation_model
relationships
semantic_equivalence
constraints
measurement_model
reasoning_rules
confidence_model
update_model
PURPOSE:
deterministic_semantic_integrity_identifier
RECOMPUTE_WHEN:
ontology_definition_changes
unit_or_quantity_kind_definition_changes
linear_affine_or_context_conversion_changes
prefix_compound_or_powered_unit_changes
temperature_or_logarithmic_conversion_changes
conversion_factor_exactness_or_source_changes
uncertainty_or_covariance_model_changes
conversion_graph_or_path_changes
parsing_formatting_or_version_changes
measurement_record_changes
constraint_model_changes
reasoning_rule_changes
}
}
END FLOW