Analog Computing Ontology

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FLOW ALGEBRA — ANALOG COMPUTING ONTOLOGY
Semantic Library
Version: 4.0
Canonical Page:
https://kirethresearch.org/booksai-core/ontologies/computing-ontologies/foundations-of-computing/analog-computing-ontology.html

FLOW ANALOG_COMPUTING_ONTOLOGY {

  META {
    DOMAIN = "Computing Ontologies"
    SUBDOMAIN = "Foundations of Computing"
    ONTOLOGY = "Analog Computing Ontology"
    PURPOSE = "Formalise entities, continuous representations, physical variables, components and computational processes underlying analogue computing systems."
    LOCALE = "en-GB"
  }

  ENTITY_TYPES {
    ANALOG_COMPUTING_SYSTEM
    ANALOG_COMPUTER
    ANALOG_DEVICE
    PHYSICAL_SYSTEM
    ANALOG_SIGNAL
    CONTINUOUS_SIGNAL
    PHYSICAL_QUANTITY
    VOLTAGE
    CURRENT
    CHARGE
    FREQUENCY
    PHASE
    TIME
    POSITION
    VELOCITY
    PRESSURE
    TEMPERATURE
    REPRESENTATION
    SCALE_FACTOR
    REFERENCE_VALUE
    INPUT
    OUTPUT
    STATE
    STATE_VARIABLE
    CONTINUOUS_STATE
    COMPONENT
    CIRCUIT
    RESISTOR
    CAPACITOR
    INDUCTOR
    AMPLIFIER
    OPERATIONAL_AMPLIFIER
    INTEGRATOR
    DIFFERENTIATOR
    SUMMING_AMPLIFIER
    MULTIPLIER
    DIVIDER
    FUNCTION_GENERATOR
    COMPARATOR
    POTENTIOMETER
    SWITCH
    SIGNAL_SOURCE
    MEASUREMENT_DEVICE
    FEEDBACK_LOOP
    TRANSFER_FUNCTION
    DIFFERENTIAL_EQUATION
    DYNAMICAL_SYSTEM
    MODEL
    SIMULATION
    CALIBRATION
    NOISE
    DRIFT
    ERROR
    TOLERANCE
    SATURATION
    BANDWIDTH
    EVIDENCE
    CONFIDENCE_SCORE
    PROVENANCE_RECORD
  }

  RELATIONSHIPS {
    IS_A
    INSTANCE_OF
    PART_OF
    CONTAINS
    CONNECTED_TO
    REPRESENTS
    MODELS
    SIMULATES
    MEASURES
    SCALES_TO
    RECEIVES
    PRODUCES
    TRANSFORMS
    AMPLIFIES
    ATTENUATES
    INTEGRATES
    DIFFERENTIATES
    SUMS
    MULTIPLIES
    DIVIDES
    COMPARES
    FEEDS_BACK_TO
    CONTROLS
    HAS_INPUT
    HAS_OUTPUT
    HAS_STATE
    HAS_STATE_VARIABLE
    HAS_SCALE_FACTOR
    HAS_TRANSFER_FUNCTION
    HAS_TOLERANCE
    HAS_BANDWIDTH
    HAS_NOISE
    HAS_DRIFT
    SATURATES_AT
    DEPENDS_ON
    PRECEDES
    FOLLOWS
    DERIVED_FROM
    INFERRED_FROM
    HAS_EVIDENCE
    HAS_CONFIDENCE
    HAS_PROVENANCE
    MAPS_TO
    SEMANTICALLY_EQUIVALENT_TO
  }

  INPUTS {
    CONTINUOUS_SIGNALS
    PHYSICAL_VARIABLES
    INITIAL_CONDITIONS
    BOUNDARY_CONDITIONS
    DIFFERENTIAL_EQUATIONS
    SYSTEM_PARAMETERS
    COMPONENT_VALUES
    SCALE_FACTORS
    TRANSFER_FUNCTIONS
    CALIBRATION_DATA
    MEASUREMENT_DATA
    NOISE_DATA
    TOLERANCE_DATA
    CIRCUIT_DEFINITIONS
    ONTOLOGY_TERMS
  }

  NORMALISE {
    STANDARDISE_IDENTIFIERS
    NORMALISE_PHYSICAL_UNITS
    NORMALISE_SIGNAL_RANGES
    NORMALISE_SCALE_FACTORS
    NORMALISE_COMPONENT_VALUES
    NORMALISE_TIME_REFERENCES
    NORMALISE_TRANSFER_FUNCTIONS
    RESOLVE_COMPONENT_IDENTITIES
    ALIGN_ONTOLOGY_TERMS
    REMOVE_DUPLICATES
    VALIDATE_METADATA
    PRESERVE_PROVENANCE
  }

  PROCESS ANALOG_COMPUTATION_PIPELINE {
    PHYSICAL_OR_MATHEMATICAL_INPUT
      -> ANALOG_REPRESENTATION
      -> SCALE_TO_MACHINE_RANGE
      -> CONTINUOUS_SIGNAL_PROCESSING
      -> DYNAMIC_STATE_EVOLUTION
      -> OUTPUT_SIGNAL
      -> MEASUREMENT
      -> RESCALE_TO_PROBLEM_DOMAIN
      -> INTERPRETED_OUTPUT
  }

  PROCESS ANALOG_REPRESENTATION {
    PROBLEM_VARIABLE
      -> PHYSICAL_QUANTITY_SELECTION

    PHYSICAL_QUANTITY_SELECTION
      -> SCALE_FACTOR

    SCALE_FACTOR
      -> ANALOG_SIGNAL

    ANALOG_SIGNAL
      -> MACHINE_VARIABLE
  }

  PROCESS DIFFERENTIAL_EQUATION_COMPUTATION {
    DIFFERENTIAL_EQUATION
      -> VARIABLE_MAPPING

    VARIABLE_MAPPING
      -> INTEGRATOR_NETWORK

    INTEGRATOR_NETWORK
      -> INITIAL_CONDITION_SETUP

    INITIAL_CONDITION_SETUP
      -> CONTINUOUS_EVOLUTION

    CONTINUOUS_EVOLUTION
      -> SOLUTION_TRAJECTORY
  }

  PROCESS SIGNAL_OPERATION {
    INPUT_SIGNAL
      -> ANALOG_COMPONENT

    ANALOG_COMPONENT
      -> TRANSFER_FUNCTION_APPLICATION

    TRANSFER_FUNCTION_APPLICATION
      -> OUTPUT_SIGNAL

    OUTPUT_SIGNAL
      -> RANGE_AND_ERROR_CHECK
  }

  PROCESS FEEDBACK_REASONING {
    SYSTEM_OUTPUT
      -> FEEDBACK_PATH

    FEEDBACK_PATH
      -> FEEDBACK_SIGNAL

    FEEDBACK_SIGNAL + INPUT_SIGNAL
      -> CONTROLLED_INPUT

    CONTROLLED_INPUT
      -> SYSTEM_STATE_UPDATE

    SYSTEM_STATE_UPDATE
      -> NEW_OUTPUT
  }

  PROCESS STATE_REASONING {
    CONTINUOUS_STATE(T1)
      + SYSTEM_DYNAMICS
      + DELTA_TIME
      -> CONTINUOUS_STATE(T2)

    STATE_TRAJECTORY
      -> DYNAMIC_BEHAVIOUR

    DYNAMIC_BEHAVIOUR
      -> STABILITY_OR_RESPONSE_ANALYSIS
  }

  PROCESS CALIBRATION_REASONING {
    REFERENCE_INPUT
      -> OBSERVED_OUTPUT

    OBSERVED_OUTPUT + EXPECTED_OUTPUT
      -> CALIBRATION_ERROR

    CALIBRATION_ERROR
      -> SCALE_OR_OFFSET_ADJUSTMENT

    SCALE_OR_OFFSET_ADJUSTMENT
      -> UPDATED_CALIBRATION
  }

  PROCESS ERROR_REASONING {
    IDEAL_SIGNAL + OBSERVED_SIGNAL
      -> ERROR_ESTIMATE

    ERROR_ESTIMATE
      -> NOISE_COMPONENT
      -> DRIFT_COMPONENT
      -> COMPONENT_TOLERANCE_COMPONENT
      -> MEASUREMENT_COMPONENT

    ERROR_COMPONENTS
      -> UNCERTAINTY_ESTIMATE
  }

  RULES {
    IF ANALOG_SIGNAL REPRESENTS PROBLEM_VARIABLE
    THEN REQUIRE {
      PHYSICAL_QUANTITY
      SCALE_FACTOR
      VALID_SIGNAL_RANGE
      UNIT_CONTEXT
    }

    IF COMPONENT_PERFORMS_OPERATION
    THEN LINK {
      INPUT_SIGNAL
      COMPONENT
      TRANSFER_FUNCTION_OR_OPERATION
      OUTPUT_SIGNAL
    }

    IF SIGNAL_EXCEEDS_COMPONENT_RANGE
    THEN FLAG SATURATION

    IF SIGNAL_BANDWIDTH_EXCEEDS_SYSTEM_BANDWIDTH
    THEN FLAG REPRESENTATION_OR_RESPONSE_LIMITATION

    IF TWO_ANALOG_VALUES_ARE_CLOSE
    THEN DO_NOT_ASSERT_EXACT_EQUALITY_WITHOUT_TOLERANCE_CONTEXT

    IF OUTPUT_IS_MEASURED
    THEN PRESERVE {
      MEASUREMENT_DEVICE
      CALIBRATION
      RESOLUTION
      UNCERTAINTY
    }

    IF SEMANTIC_IDENTIFIERS_DIFFER
    AND ANALOG_COMPUTING_REFERENT_IS_SAME
    THEN APPLY SEMANTIC_EQUIVALENCE
  }

  CONFIDENCE {
    CONFIDENCE_SCORE =
      WEIGHT(
        CALIBRATION_QUALITY,
        SIGNAL_TO_NOISE_RATIO,
        COMPONENT_TOLERANCE,
        SCALE_FACTOR_CERTAINTY,
        MEASUREMENT_ACCURACY,
        MODEL_FIDELITY,
        REPEATABILITY,
        PROVENANCE_COMPLETENESS
      )

    LEVELS {
      HIGH
      MODERATE
      LOW
      INSUFFICIENT
    }

    IF NOISE_OR_DRIFT_INCREASES
    THEN REDUCE CONFIDENCE_SCORE

    IF SATURATION_OCCURS
    THEN REDUCE_CONFIDENCE_AND_FLAG_INVALID_RANGE

    IF CALIBRATED_REPEATABLE_RESULT_EXISTS
    THEN INCREASE CONFIDENCE_SCORE
  }

  SEMANTIC_EQUIVALENCE {
    EQUIVALENCE_KEY =
      NORMALISE(
        ENTITY_TYPE,
        PHYSICAL_QUANTITY,
        SCALE_FACTOR,
        UNIT,
        SIGNAL_RANGE,
        COMPUTATIONAL_CONTEXT
      )

    IF EQUIVALENCE_KEY(A) == EQUIVALENCE_KEY(B)
    THEN A SEMANTICALLY_EQUIVALENT_TO B

    ELSE PRESERVE_DISTINCT_ENTITIES
  }

  REASONING_CONSTRAINTS {
    ANALOG_VALUE != EXACT_SYMBOLIC_VALUE
    PHYSICAL_SIGNAL != ABSTRACT_VARIABLE
    REPRESENTATION_REQUIRES_SCALE_CONTEXT
    CONTINUOUS != INFINITELY_PRECISE
    MEASURED_OUTPUT != EXACT_OUTPUT
    MODEL != PHYSICAL_SYSTEM
    NOISE_AFFECTS_SIGNAL
    COMPONENT_TOLERANCE_AFFECTS_RESULT
    DRIFT_AFFECTS_CALIBRATION
    SATURATION_INVALIDATES_LINEAR_ASSUMPTIONS
    BANDWIDTH_LIMITS_DYNAMIC_RESPONSE
    INITIAL_CONDITIONS_AFFECT_TRAJECTORY
    PROVENANCE_MUST_BE_PRESERVED
    UNCERTAINTY_MUST_NOT_BE_DISCARDED
  }

  VALIDATION {
    CHECK_ENTITY_TYPES
    CHECK_RELATION_DOMAINS_AND_RANGES
    CHECK_PHYSICAL_UNITS
    CHECK_SCALE_FACTORS
    CHECK_SIGNAL_RANGES
    CHECK_COMPONENT_VALUES
    CHECK_TRANSFER_FUNCTIONS
    CHECK_INITIAL_CONDITIONS
    CHECK_BANDWIDTH
    CHECK_SATURATION
    CHECK_CALIBRATION
    CHECK_ERROR_AND_UNCERTAINTY
    CHECK_PROVENANCE
    CHECK_CONFIDENCE
    CHECK_SEMANTIC_CONSISTENCY
  }

  OUTPUTS {
    NORMALISED_ANALOG_COMPUTING_ENTITIES
    ANALOG_REPRESENTATIONS
    SIGNAL_RELATIONS
    COMPONENT_OPERATION_RELATIONS
    DIFFERENTIAL_EQUATION_MAPPINGS
    CONTINUOUS_STATE_TRAJECTORIES
    FEEDBACK_RELATIONS
    CALIBRATION_RECORDS
    ERROR_ESTIMATES
    UNCERTAINTY_ESTIMATES
    CONFIDENCE_SCORES
    EVIDENCE_LINKS
    PROVENANCE_RECORDS
    EXPLANATION_PATHS
  }

  UPDATE_MODEL {
    ON NEW_MEASUREMENT_OR_COMPONENT_DATA {
      NORMALISE
      UPDATE_COMPONENT_VALUES
      UPDATE_CALIBRATION
      UPDATE_SIGNAL_MODEL
      RECOMPUTE_ERROR_ESTIMATES
      UPDATE_CONFIDENCE
      PRESERVE_VERSION_HISTORY
    }

    ON NEW_EXPERIMENTAL_EVIDENCE {
      LINK_EVIDENCE
      REASSESS_MODEL_FIDELITY
      REASSESS_TRANSFER_RELATIONS
      UPDATE_CONFIDENCE
      RECORD_PROVENANCE
    }

    ON ONTOLOGY_REVISION {
      REMAP_TERMS
      CHECK_SEMANTIC_EQUIVALENCE
      IDENTIFY_DEPRECATED_TERMS
      MIGRATE_RELATIONSHIPS
      PRESERVE_PRIOR_VERSION_REFERENCES
    }
  }

  FLOW_HASH {
    HASH_INPUT =
      CANONICALISE(
        ENTITY_TYPES,
        RELATIONSHIPS,
        RULES,
        CONFIDENCE,
        SEMANTIC_EQUIVALENCE,
        REASONING_CONSTRAINTS,
        UPDATE_MODEL
      )

    FLOW_HASH = SHA256(HASH_INPUT)
  }

  AI_CONSUMPTION {
    INDEX {
      ONTOLOGY
      ENTITY_TYPES
      RELATIONSHIPS
      RULES
      OUTPUTS
    }

    RETRIEVE {
      BY_SYSTEM
      BY_SIGNAL
      BY_PHYSICAL_QUANTITY
      BY_COMPONENT
      BY_OPERATION
      BY_STATE
      BY_DIFFERENTIAL_EQUATION
      BY_FEEDBACK_LOOP
      BY_CALIBRATION
      BY_ERROR
      BY_CONFIDENCE
    }

    REASON {
      APPLY_RELATIONSHIPS
      APPLY_RULES
      TRACE_SIGNAL_FLOW
      TRACE_COMPONENT_OPERATIONS
      ANALYSE_CONTINUOUS_STATE
      ANALYSE_FEEDBACK
      ANALYSE_SCALE_FACTORS
      ANALYSE_ERROR_AND_UNCERTAINTY
      CHECK_SEMANTIC_EQUIVALENCE
      TRACE_EVIDENCE
      TRACE_PROVENANCE
      GENERATE_EXPLANATION_PATH
    }

    RESPONSE_POLICY {
      DISTINGUISH_PHYSICAL_SIGNAL_FROM_ABSTRACT_VALUE
      PRESERVE_SCALE_AND_UNIT_CONTEXT
      PRESERVE_CALIBRATION_CONTEXT
      PRESERVE_ERROR_AND_UNCERTAINTY
      DISTINGUISH_MODEL_FROM_PHYSICAL_SYSTEM
      RETURN_CONFIDENCE_WHEN_AVAILABLE
      RETURN_PROVENANCE_WHEN_AVAILABLE
      AVOID_UNSUPPORTED_ANALOG_COMPUTING_INFERENCE
    }
  }

  TERMINAL {
    RESULT =
      VALIDATED(
        SEMANTICALLY_NORMALISED(
          EVIDENCE_LINKED(
            CONFIDENCE_AWARE(
              ANALOG_COMPUTING_KNOWLEDGE
            )
          )
        )
      )
  }
}

END FLOW