Simulation Input Identification Module (SIIM)
OOF™ Origin Open Foundation™
Independent Methodological Authority
Architecture Ecosystem: Structured Reality Standards™
Architecture Family: SIMULOS® — Simulation Governance Architecture
Parent Standard: Simulation Input & Data Standard (SIDS)
Operational Layer: Simulation Input & Data Governance Layer
Category: Governance & Enforcement
Subcategory: Simulation Governance
Type: Parent Standard Module
Governed Space: Simulation Input Identification
Version: 1.0
Status: Canonical · Open Module
Effective Date: 18 August 2026
Compatibility: OOF® Methodology OS™ · GOA™ · ORA™ · VALIDOS® · INTEGROS® · ADIT® · AGA™ ·
AIG® · CLIA® · MGIA™ · ASGA™ · RIS™
AI-Readable: Yes
Authority: OOF®
Protection: MIP® — Methodological Intellectual Property
Canonical Language: English (UCL™)
Governed Space
Simulation Input Identification
Canonical Definition
Simulation Input Identification Module (SIIM) defines the governance frameworkthrough which every materially relevant data object, value, signal,
measurement, state, distribution, event, record, synthetic input, derived
input, human-supplied input, model-generated input, or other information
capable of influencing a simulation is identified, classified, distinguished,
source-referenced, bound to its simulation role, and maintained as a traceable
Simulation Input.
SIIM establishes the first internal governance space of SIDS by determining
what is entering the simulation before questions of representativeness,
transformation, temporal applicability, and uncertainty are evaluated.
Operational Role
SIIM serves as the first internal governance space of the Simulation Input &Data Standard (SIDS).
The preceding Parent Standard, Simulation Model & Environment Standard (SMES),
establishes the controlled model and environment through which simulation
occurs.
SIIM asks:
What information is proposed to enter that governed simulation structure, what
exactly is each input, where does it originate, and what role can it
influence?
The governed progression is:
Governed Simulation Model & Environment → Input Requirement → Proposed Input →
Input Identification → Input Classification → Origin Reference → Simulation
Role Binding → Simulation Input Register
The resulting identified input basis becomes available to the subsequent SIDS
modules for representativeness, transformation, temporal, and uncertainty
governance.
Module Function
SIIM exists to prevent a simulation from consuming materially influentialinformation whose identity or role is unclear.
It prevents: unidentified inputs entering simulation execution, ambiguous
variables being treated as equivalent, different data objects sharing an
indistinguishable identity, source origin disappearing after ingestion,
synthetic information appearing as observed information, derived information
appearing as directly measured information, historical information appearing
as live information, units or semantics becoming detached from values, input
roles becoming unclear, substitutions occurring invisibly, input dependencies
being hidden, and simulation outputs becoming impossible to reconstruct
because the actual consumed inputs cannot be determined.
Simulation Input
A Simulation Input is any identifiable information object capable ofmaterially influencing: simulation initialization, model behavior,
environmental state, actor behavior, state transitions, simulation
progression, scenario conditions, or simulation outputs.
A Simulation Input may be:
Data
Value
Signal
Measurement
State
Event
Distribution
RecordSequence
Instruction
External Observation
Synthetic Information
or another governed information object consumed by the simulation.Material Input
SIIM focuses on material Simulation Inputs.An input is material where changing, removing, substituting, or misidentifying
it could materially affect: simulation configuration, simulation behavior,
scenario conditions, execution, output, interpretation, or downstream
reliance.
Not every technical field requires equal governance depth.
Input Requirement
Before an input is identified, the simulation may establish an InputRequirement.
An Input Requirement defines what information the simulation needs without
presupposing which specific data object will satisfy that need.
For example:
Requirement: Current external temperature
may later be satisfied by:Sensor TEMP-04 measurement
This distinction prevents the required information from being confused withthe particular source selected to provide it.
Input Identification
Every material Simulation Input should be sufficiently identifiable beforegoverned simulation use.
Identification may establish: Simulation Input Identifier, input name, input
description, input type, input origin, source reference, unit, format,
semantic meaning, temporal reference where known, transformation state,
applicable Simulation Object, applicable model or environment element, and
intended simulation role.
Simulation Input Identifier
A Simulation Input Identifier provides a persistent reference through which amaterial input can remain distinguishable throughout the simulation lifecycle.
Conceptually:
SI-0001
may identify one governed input object.
The identifier should remain connected to the actual input rather than merely
to a display label. Identity ≠ Variable Name
SIMULOS® establishes:
A variable name is not sufficient input identity where materially different
information can exist under that same name.
For example:
Temperature
could refer to: external temperature, engine temperature, battery temperature,
historical average temperature, predicted temperature, or synthetic scenario
temperature.
SIIM requires sufficient distinction.
Input Naming
Input names should communicate the represented information with enoughspecificity to prevent material ambiguity.
Where necessary:
Temperature
should become:
External Ambient Temperature
or another sufficiently precise representation.Naming alone does not establish full identity, but poor naming can weaken
traceability.
Input Semantics
SIIM governs what the input means, not only how it is technically encoded.For example:
0.75
may represent: 75% probability, normalized sensor output, friction
coefficient, model confidence, actuator position, or another quantity.
The numerical value alone is insufficient.
Input Units
Where units materially affect interpretation, they must remain associated with
the input.
For example:
50
is not a sufficiently defined physical input if it could mean:
50 km/h
50 mph
50 °C
or:
50 milliseconds.
Input Format
Input format may include: scalar, vector, matrix, categorical value, timeseries, event stream, image, audio, text, geospatial data, structured record,
distribution, or another machine- or human-readable form.
Format should remain identifiable where it affects simulation interpretation.
Input Classification
SIIM classifies Simulation Inputs according to their material origin and role.Possible classes include: Observed Input
Information obtained through observation of represented reality.Measured Input
Information produced through a measurement process.Historical Input
Information originating from a previous period.Live Input
Information supplied from an active operational environment during or near
simulation execution.
Estimated Input
Information established through estimation where direct measurement orobservation is unavailable.
Derived Input
Information calculated from other information objects.Synthetic Input
Information generated rather than directly observed from the representedreality.
Human-Supplied Input
Information introduced by a human participant or operator.Externally Supplied Input
Information supplied by an external organization, system, service, or dataprovider.
Model-Generated Input
Information produced by another model and consumed by the simulation.Scenario-Specified Input
Information deliberately introduced to establish a scenario condition.One input may require multiple classifications where its provenance or role is
composite.
Classification Must Follow Reality
SIMULOS® establishes:Input classification must describe how the information was actually produced,
not how the simulation wishes to interpret it.
A model-generated estimate does not become a measured input merely because it
is formatted like sensor data.
Input Origin
Input Origin identifies the point from which the information entered thegoverned simulation chain.
Origin may refer to: sensor, database, organization, person, operational
system, AI system, external model, simulator, scientific instrument,
historical dataset, synthetic generator, or another identifiable origin.
Origin ≠ Reliability
SIIM identifies origin.It does not establish that the origin is reliable.
Source reliability may require governance under VALIDOS® or another applicable
architecture.
The distinction is important:
Known Origin ≠ Trusted Origin Origin
Preservation
Where materially relevant, origin should remain attached throughout:Origin → Input → Transformation →
Simulation Use
Subsequent transformation should not silently erase the origin of theinformation.
Source Reference
An input may maintain a reference to the source object or system from which itoriginates.
The source reference may include: source identifier, system identifier,
dataset identifier, sensor identifier, provider identifier, model identifier,
or another persistent reference.
Input State
An input may exist in different states.
For example:
Raw
Cleaned
Normalized
Aggregated
Derived
Imputed
Synthetic
or:
Transformed
SIIM identifies the state.
SDTM — Simulation Data Transformation Module governs the transformation
itself.
Raw Input
A Raw Simulation Input is information before simulation-specific
transformation.
Raw does not mean: correct, reliable, representative, complete, or suitable.
It only describes its position relative to subsequent processing.
Derived Input
A Derived Input should preserve the relationship:Source Input(s) → Derivation → Derived
Input
SIIM identifies the resulting object as derived.SDTM governs the methodological transformation.
Synthetic Input Identification
Synthetic inputs must remain distinguishable from directly observed ormeasured information.
SIMULOS® establishes:
Synthetic information must never acquire an observed-data identity merely
because it is technically indistinguishable in format.
Estimated Input Identification
Estimated values should remain identifiable as estimates.For example:
Estimated Vehicle Mass = 1,850 kg
should not silently become:Measured Vehicle Mass = 1,850 kg
after ingestion.Live vs Historical Input
SIIM distinguishes whether information originates from:current or near-current operational conditions
or:
historical records.
Detailed temporal suitability is governed by STDM — Simulation Temporal Data
Module.
SIIM preserves the initial classification required for that assessment.
Input Role
An input should remain connected to the role it performs in the simulation.
Possible roles include: initialization, state update, environmental condition,
actor condition, control signal, disturbance, behavioral input, scenario
condition, external event, calibration reference, or another defined
simulation function.
Input-to-Simulation Object Binding
Where relevant:Simulation Input → Simulation Object
should remain identifiable.This prevents inputs associated with one Simulation Object from being silently
applied to another.
Input-to-Model Binding
Where an input affects a specific model component:Simulation Input → Model Component
should remain traceable.This supports later analysis of which information could have influenced which
simulated behavior.
Input-to-Environment Binding
Inputs affecting environmental conditions should preserve:Simulation Input → Environment Element /
State
For example:Rainfall Input → Road Surface Environment State Input-to-Configuration Binding
Where an input is valid only under a particular simulation configuration, that
relationship should remain visible.
Input-to-Scenario Reference
An input may be associated with one or more scenarios.SIIM records the association where known.
SSS — Simulation Scenario Standard governs scenario design and coverage.
Input Dependency
One input may depend upon another.For example:
Vehicle Speed
may contribute to:Calculated Braking Distance Input
The dependency should remain visible where it materially affects traceability.Composite Input
A Composite Input combines multiple information objects into onesimulation-consumed input.
Conceptually:
Input A + Input B + Input C → Composite
Input D
The composite should not erase the identities of its materially relevantcomponents.
Duplicate Input
Two technically separate inputs may represent the same underlying information.Duplicate inputs can create: double counting, unintended weighting, correlated
influence, or false independence.
SIIM identifies material duplication for subsequent treatment.
Ambiguous Input
An Ambiguous Simulation Input exists where the available information isinsufficient to determine exactly: what the input represents, where it
originated, which unit applies, which object it describes, or which role it
performs.
Material ambiguity should be resolved or explicitly preserved before
simulation use.
Unidentified Input
An Unidentified Simulation Input is a materially influential input whoseidentity cannot be sufficiently established.
Possible treatment may include:
Resolve
Restrict
Exclude
or:
Escalate for further assessment
depending upon the simulation context.No Anonymous Material Input Principle
SIMULOS® establishes:A materially influential input should not enter governed simulation execution
anonymously.
Input Equivalence
Two inputs should not be considered equivalent merely because: their valuesmatch, their names match, their formats match, or they occupy the same
software field.
Input equivalence may depend upon: semantics, origin, unit, population,
environment, time, transformation, and simulation role.
Input Substitution
An identified input may later be substituted.For example:
Live Sensor Input
may be replaced with:Historical Replay Input
The replacement should receive its own identity and classification.The simulation record should preserve:
Original Intended Input → Substitution → Actual Consumed Input Actual Consumed
Input
SIIM distinguishes:
Planned Input
from:Actual Consumed Input.
This distinction becomes critical when execution does not consume exactly what
was originally configured.
Input Set Membership
Each material Simulation Input may belong to one or more governed SimulationInput Sets.
Conceptually:
Simulation Input Set SIS-001
may contain:SI-001 + SI-002 + SI-003 + SI-004
Input-set governance enables reconstruction of the complete information basisof an execution.
Input Set Identifier
A Simulation Input Set may receive a persistent identifier.This allows:
Execution → Input Set → Individual Inputs
to remain traceable.Input Set Composition
The composition of an Input Set should identify materially relevant: inputs,input versions, classifications, states, source references, and applicable
simulation configuration.
Input Version Distinction
Where materially changed information exists under the same logical inputidentity, versions should remain distinguishable.
For example:
Weather Dataset v3
should not silently overwrite:Weather Dataset v2
where previous executions relied upon v2.Input Change
A material input may change because: source data changes, values change,origin changes, classification changes, format changes, unit changes,
derivation changes, or its simulation role changes.
The changed input should remain distinguishable from the previous state where
required for reconstruction.
Input Identity Continuity
Input Identity Continuity preserves the relationship between successive statesor versions of the same logical input.
Conceptually:
SI-001 v1 → SI-001 v2 → SI-001 v3
while preventing materially different objects from being falsely treated asone unchanged input.
Point-in-Time Input Identity
SIIM supports reconstruction of:Which exact input existed at the time of a particular simulation execution?
This is essential where input data changes after execution.
No Retrospective Input Replacement
Principle
SIMULOS® establishes:Updating an input must not silently rewrite the historical input identity of
completed simulation executions.
Input Traceability
SIIM establishes the traceability foundation:Input Requirement
↓Simulation Input
↓Origin / Source Reference
↓Classification
↓Simulation Role
↓Model / Environment / Scenario Binding
↓Input Set
↓
Simulation Execution Reference
This chain enables later governance of simulation behavior and outputs.Input Identification Status
A material Simulation Input may receive an identification status such as:Identified
Conditionally Identified
AmbiguousUnidentified
Supersededor:
Excluded
The status concerns input identity.
It does not establish representativeness, temporal suitability, uncertainty,
or general validity.
Identification Sufficiency
Input identification is sufficient when the information necessary todistinguish and trace the material input is adequate for its intended
simulation role.
The required identification depth may vary with: simulation consequence, input
influence, system complexity, simulation purpose, and downstream reliance.
Identification Failure
An Input Identification Failure occurs where a material input cannot besufficiently distinguished or traced for governed use.
Possible causes include: missing origin, ambiguous semantics, unknown units,
indistinguishable versions, undocumented substitution, unknown derivation, or
inability to determine the actual consumed input.
Identification Failure ≠ Data Invalidity
Failure to identify an input sufficiently does not prove the underlyinginformation is false.
It establishes that the information cannot currently support the required
level of governed simulation traceability.
Simulation Input Register
SIIM may maintain a Simulation Input Register containing material SimulationInputs and their governance attributes.
A register entry may contain: Simulation Input Identifier, input name,
description, classification, origin, source reference, unit, format, semantic
definition, input state, simulation role, applicable object, model binding,
environment binding, scenario reference, input-set membership, version, and
identification status.
Minimum Implementation Framework
1. Identify Input RequirementsDetermine which information the governed simulation requires. 2. Discover
Material Proposed Inputs
Identify all materially influential information proposed for simulation use.
3. Assign Simulation Input Identity
Create a persistent identifier for each material input where appropriate. 4.
Define Input Meaning
Record sufficient: name, semantics, unit, format, and represented quantity or
state.
5. Classify Input Origin and Type
Determine whether the input is: observed, measured, historical, live,
estimated, derived, synthetic, human-supplied, externally supplied,
model-generated, scenario-specified, or another defined class.
6. Preserve Origin and Source Reference
Bind the input to its identifiable origin and source where available. 7. Bind
the Input to Simulation Role
Establish which: Simulation Object, model component, environment element,
configuration, or scenario context
the input may influence. 8. Identify Dependencies and Composite Inputs
Preserve material relationships between inputs. 9. Detect Ambiguity,
Duplication, and Substitution
Identify materially unclear, duplicated, replaced, or unexpectedly consumed
inputs. 10. Establish Input Set Membership
Bind the identified inputs to the applicable Simulation Input Set. 11. Assign
Identification Status
Determine whether each material input is sufficiently identified for further
SIDS governance. 12. Preserve Input Traceability
Maintain the chain from input requirement and origin through simulation role
and eventual execution use.
Governance Outputs
SIIM may produce: Simulation Input Requirement Record, Simulation InputIdentifier, Simulation Input Record, Simulation Input Classification,
Simulation Input Origin Record, Simulation Input Source Reference, Simulation
Input Semantic Definition, Simulation Input Unit Record, Simulation Input
Format Record, Simulation Input State Record, Simulation Input Role Record,
Input-to-Simulation Object Binding, Input-to-Model Binding,
Input-to-Environment Binding, Input-to-Configuration Binding,
Input-to-Scenario Reference, Simulation Input Dependency Map, Composite Input
Record, Duplicate Input Record, Ambiguous Input Record, Unidentified Input
Record, Synthetic Input Identification Record, Derived Input Identification
Record, Estimated Input Identification Record, Input Substitution Record,
Actual Consumed Input Record, Simulation Input Set, Simulation Input Set
Identifier, Input Set Composition Record, Input Version Record, Input Identity
Continuity Record, Point-in-Time Input Identity Record, Input Identification
Status, Input Identification Failure Record, Simulation Input Register, and
Simulation Input Traceability Map.
Use Case 1 — Autonomous Vehicle Simulation
ScenarioAn autonomous vehicle simulation consumes: camera data, radar measurements,
weather information, road geometry, vehicle state, synthetic pedestrian
behavior, and traffic signals.
Application
SIIM identifies each material input and distinguishes:
Measured Radar Input
from:Synthetic Pedestrian Input
and:Historical Weather Dataset
from:Current Vehicle-State Input.
Each input is bound to the relevant model
or environment component. Result
The simulation possesses an identifiable input basis beforerepresentativeness, transformation, temporal applicability, and uncertainty
are assessed. Use Case 2 — Spacecraft Landing Simulation
Scenario
A spacecraft landing simulation uses: terrain elevation data, gravitational
model outputs, estimated atmospheric density, vehicle telemetry,
engine-performance measurements, and synthetic failure conditions.
Application
SIIM identifies the origin, classification, meaning, units, and simulation
role of each material input.
The module prevents:
Estimated Atmospheric Density
from becoming indistinguishable from:Direct Atmospheric Measurement
and preserves synthetic failure conditions as synthetic inputs. ResultEvery materially influential input can be traced to its origin and simulation
role, providing a controlled basis for subsequent SIMULOS® input governance.
Architectural Position
Simulation Input Identification is the first internal governance space of theSimulation Input & Data Standard (SIDS).
The complete SIDS progression is:
Simulation Input Identification
↓Simulation Data Representativeness
↓Simulation Data Transformation
↓Simulation Temporal Data
↓Simulation Input Uncertainty
SIIM therefore establishes the identity layer upon which all subsequent SIDSgovernance depends.
Representativeness cannot be meaningfully assessed until the input being
assessed is known.
Transformation cannot be governed unless the source and resulting input can be
distinguished.
Temporal applicability cannot be evaluated without an identifiable information
object.
Input uncertainty cannot remain attached to an input whose identity is
unstable.
Foundational Principle
A simulation cannot govern the suitability of information it cannot firstidentify, distinguish, classify, and trace to the role through which that
information can influence simulated behavior.