Hybrid Computing Ontology

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

FLOW HYBRID_COMPUTING_ONTOLOGY {

  META {
    DOMAIN = "Computing Ontologies"
    SUBDOMAIN = "Foundations of Computing"
    ONTOLOGY = "Hybrid Computing Ontology"
    PURPOSE = "Formalise entities, interfaces, representations and computational processes that integrate analogue and digital computing within hybrid computational systems."
    LOCALE = "en-GB"
  }

  ENTITY_TYPES {
    HYBRID_COMPUTING_SYSTEM
    ANALOG_COMPUTING_SYSTEM
    DIGITAL_COMPUTING_SYSTEM
    COMPUTATIONAL_COMPONENT
    ANALOG_COMPONENT
    DIGITAL_COMPONENT
    PROCESSOR
    MEMORY
    STORAGE
    ANALOG_CIRCUIT
    DIGITAL_CIRCUIT
    SENSOR
    ACTUATOR
    INTERFACE
    ANALOG_TO_DIGITAL_CONVERTER
    DIGITAL_TO_ANALOG_CONVERTER
    SAMPLE_AND_HOLD
    SIGNAL_CONDITIONER
    CLOCK
    TIMER
    ANALOG_SIGNAL
    DIGITAL_SIGNAL
    CONTINUOUS_SIGNAL
    DISCRETE_SIGNAL
    PHYSICAL_QUANTITY
    BINARY_VALUE
    SAMPLE
    QUANTISATION_LEVEL
    SAMPLE_RATE
    RESOLUTION
    SCALE_FACTOR
    REFERENCE_VALUE
    INPUT
    OUTPUT
    STATE
    CONTINUOUS_STATE
    DISCRETE_STATE
    HYBRID_STATE
    EVENT
    STATE_TRANSITION
    PROGRAM
    ALGORITHM
    CONTROL_LOGIC
    FEEDBACK_LOOP
    MODEL
    DIFFERENTIAL_EQUATION
    DISCRETE_EQUATION
    HYBRID_MODEL
    ERROR
    NOISE
    QUANTISATION_ERROR
    CONVERSION_ERROR
    LATENCY
    SYNCHRONISATION
    CALIBRATION
    CONFIGURATION
    VERSION
    EVIDENCE
    CONFIDENCE_SCORE
    PROVENANCE_RECORD
  }

  RELATIONSHIPS {
    IS_A
    INSTANCE_OF
    PART_OF
    CONTAINS
    CONNECTED_TO
    INTERFACES_WITH
    REPRESENTS
    MODELS
    CONVERTS_TO
    SAMPLES
    QUANTISES
    ENCODES
    DECODES
    MEASURES
    CONTROLS
    EXECUTES
    PROCESSES
    TRANSFORMS
    RECEIVES
    PRODUCES
    SENDS
    READS
    WRITES
    FEEDS_BACK_TO
    SYNCHRONISES_WITH
    TRIGGERS
    HAS_INPUT
    HAS_OUTPUT
    HAS_STATE
    HAS_SAMPLE_RATE
    HAS_RESOLUTION
    HAS_SCALE_FACTOR
    HAS_LATENCY
    HAS_CONFIGURATION
    HAS_VERSION
    HAS_ERROR
    DEPENDS_ON
    PRECEDES
    FOLLOWS
    DERIVED_FROM
    INFERRED_FROM
    HAS_EVIDENCE
    HAS_CONFIDENCE
    HAS_PROVENANCE
    MAPS_TO
    SEMANTICALLY_EQUIVALENT_TO
  }

  INPUTS {
    ANALOG_SIGNALS
    DIGITAL_DATA
    PHYSICAL_VARIABLES
    SENSOR_DATA
    CONTROL_INPUTS
    INITIAL_CONDITIONS
    SYSTEM_PARAMETERS
    SAMPLE_RATES
    QUANTISATION_PARAMETERS
    SCALE_FACTORS
    CALIBRATION_DATA
    ANALOG_COMPONENT_VALUES
    DIGITAL_PROGRAMS
    HYBRID_MODELS
    EXECUTION_TRACES
    MEASUREMENT_DATA
    ONTOLOGY_TERMS
  }

  NORMALISE {
    STANDARDISE_IDENTIFIERS
    NORMALISE_PHYSICAL_UNITS
    NORMALISE_ANALOG_SIGNAL_RANGES
    NORMALISE_DIGITAL_ENCODINGS
    NORMALISE_SAMPLE_RATES
    NORMALISE_RESOLUTION
    NORMALISE_SCALE_FACTORS
    NORMALISE_TIMESTAMPS
    NORMALISE_CONFIGURATION
    RESOLVE_COMPONENT_IDENTITIES
    ALIGN_ONTOLOGY_TERMS
    REMOVE_DUPLICATES
    VALIDATE_METADATA
    PRESERVE_PROVENANCE
  }

  PROCESS HYBRID_COMPUTATION_PIPELINE {
    INPUT
      -> DOMAIN_IDENTIFICATION
      -> ANALOG_OR_DIGITAL_REPRESENTATION
      -> INTERFACE_CONVERSION_IF_REQUIRED
      -> HYBRID_PROCESSING
      -> STATE_UPDATE
      -> OUTPUT_CONVERSION_IF_REQUIRED
      -> OUTPUT
      -> VALIDATION
  }

  PROCESS ANALOG_TO_DIGITAL_CONVERSION {
    ANALOG_SIGNAL
      -> SIGNAL_CONDITIONING

    SIGNAL_CONDITIONING
      -> SAMPLING

    SAMPLING
      -> QUANTISATION

    QUANTISATION
      -> DIGITAL_ENCODING

    DIGITAL_ENCODING
      -> DIGITAL_DATA

    DIGITAL_DATA
      -> CONVERSION_ERROR_ESTIMATE
  }

  PROCESS DIGITAL_TO_ANALOG_CONVERSION {
    DIGITAL_DATA
      -> DIGITAL_DECODING

    DIGITAL_DECODING
      -> LEVEL_RECONSTRUCTION

    LEVEL_RECONSTRUCTION
      -> HOLD_OR_INTERPOLATION

    HOLD_OR_INTERPOLATION
      -> ANALOG_OUTPUT_SIGNAL

    ANALOG_OUTPUT_SIGNAL
      -> FILTERING
      -> PHYSICAL_OUTPUT
  }

  PROCESS HYBRID_STATE_REASONING {
    HYBRID_STATE(T1)
      + CONTINUOUS_DYNAMICS
      + DISCRETE_EVENT
      -> HYBRID_TRANSITION

    HYBRID_TRANSITION
      -> HYBRID_STATE(T2)

    HYBRID_STATE_SEQUENCE
      -> HYBRID_EXECUTION_TRACE
  }

  PROCESS HYBRID_CONTROL {
    SENSOR_SIGNAL
      -> ANALOG_TO_DIGITAL_CONVERSION

    ANALOG_TO_DIGITAL_CONVERSION
      -> DIGITAL_CONTROL_ALGORITHM

    DIGITAL_CONTROL_ALGORITHM
      -> CONTROL_OUTPUT

    CONTROL_OUTPUT
      -> DIGITAL_TO_ANALOG_CONVERSION

    DIGITAL_TO_ANALOG_CONVERSION
      -> ACTUATOR_SIGNAL

    ACTUATOR_SIGNAL
      -> PHYSICAL_SYSTEM

    PHYSICAL_SYSTEM
      -> FEEDBACK_SIGNAL
  }

  PROCESS SYNCHRONISATION_REASONING {
    ANALOG_TIMELINE + DIGITAL_CLOCK
      -> TIME_ALIGNMENT

    TIME_ALIGNMENT
      -> SAMPLE_EVENT_MAPPING

    SAMPLE_EVENT_MAPPING
      -> SYNCHRONISATION_CHECK

    SYNCHRONISATION_CHECK
      -> ALIGNED_STATE_OR_TIMING_ERROR
  }

  PROCESS ERROR_REASONING {
    ANALOG_ERROR
    + QUANTISATION_ERROR
    + CONVERSION_ERROR
    + TIMING_ERROR
    + DIGITAL_PROCESSING_ERROR
      -> HYBRID_ERROR_MODEL

    HYBRID_ERROR_MODEL
      -> TOTAL_UNCERTAINTY_ESTIMATE
  }

  RULES {
    IF ANALOG_SIGNAL IS_CONVERTED_TO_DIGITAL
    THEN REQUIRE {
      SAMPLE_RATE
      RESOLUTION
      INPUT_RANGE
      REFERENCE_VALUE
      ENCODING
    }

    IF DIGITAL_VALUE IS_CONVERTED_TO_ANALOG
    THEN REQUIRE {
      RESOLUTION
      OUTPUT_RANGE
      REFERENCE_VALUE
      RECONSTRUCTION_METHOD
    }

    IF SAMPLE_RATE_IS_INSUFFICIENT_FOR_SIGNAL_BANDWIDTH
    THEN FLAG ALIASING_RISK

    IF ANALOG_INPUT_EXCEEDS_CONVERTER_RANGE
    THEN FLAG SATURATION_OR_CLIPPING

    IF QUANTISATION_OCCURS
    THEN DO_NOT_ASSERT_EXACT_ANALOG_VALUE_PRESERVATION

    IF HYBRID_STATE_CHANGES
    THEN PRESERVE {
      CONTINUOUS_STATE
      DISCRETE_STATE
      EVENT
      TIME_CONTEXT
    }

    IF SEMANTIC_IDENTIFIERS_DIFFER
    AND HYBRID_COMPUTING_REFERENT_IS_SAME
    THEN APPLY SEMANTIC_EQUIVALENCE
  }

  CONFIDENCE {
    CONFIDENCE_SCORE =
      WEIGHT(
        ANALOG_SIGNAL_QUALITY,
        CONVERTER_RESOLUTION,
        SAMPLE_RATE_ADEQUACY,
        CALIBRATION_QUALITY,
        TIMING_ALIGNMENT,
        DIGITAL_EXECUTION_CERTAINTY,
        MODEL_FIDELITY,
        PROVENANCE_COMPLETENESS
      )

    LEVELS {
      HIGH
      MODERATE
      LOW
      INSUFFICIENT
    }

    IF ALIASING_RISK_EXISTS
    THEN REDUCE CONFIDENCE_SCORE

    IF CLIPPING_OR_SATURATION_OCCURS
    THEN REDUCE_CONFIDENCE_AND_FLAG_INVALID_RANGE

    IF CALIBRATED_SYNCHRONISED_REPEATABLE_RESULT_EXISTS
    THEN INCREASE CONFIDENCE_SCORE
  }

  SEMANTIC_EQUIVALENCE {
    EQUIVALENCE_KEY =
      NORMALISE(
        ENTITY_TYPE,
        REPRESENTATION_DOMAIN,
        PHYSICAL_QUANTITY_OR_DIGITAL_VALUE,
        SCALE_FACTOR,
        SAMPLE_RATE,
        RESOLUTION,
        TIME_CONTEXT
      )

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

    ELSE PRESERVE_DISTINCT_ENTITIES
  }

  REASONING_CONSTRAINTS {
    ANALOG_VALUE != DIGITAL_SAMPLE
    DIGITAL_SAMPLE != CONTINUOUS_SIGNAL
    QUANTISED_VALUE != EXACT_PHYSICAL_VALUE
    SAMPLE_TIME != CONTINUOUS_TIME
    MODEL != PHYSICAL_SYSTEM
    CONVERSION_INTRODUCES_LIMITATIONS
    SAMPLE_RATE_LIMITS_REPRESENTABLE_BANDWIDTH
    RESOLUTION_LIMITS_VALUE_PRECISION
    LATENCY_AFFECTS_CONTROL_BEHAVIOUR
    SYNCHRONISATION_AFFECTS_STATE_ALIGNMENT
    ANALOG_AND_DIGITAL_ERRORS_MUST_BOTH_BE_PROPAGATED
    CONFIGURATION_AFFECTS_BEHAVIOUR
    PROVENANCE_MUST_BE_PRESERVED
    UNCERTAINTY_MUST_NOT_BE_DISCARDED
  }

  VALIDATION {
    CHECK_ENTITY_TYPES
    CHECK_RELATION_DOMAINS_AND_RANGES
    CHECK_PHYSICAL_UNITS
    CHECK_SIGNAL_RANGES
    CHECK_SAMPLE_RATES
    CHECK_RESOLUTION
    CHECK_SCALE_FACTORS
    CHECK_CONVERTER_RANGES
    CHECK_TIME_ALIGNMENT
    CHECK_SYNCHRONISATION
    CHECK_STATE_TRANSITIONS
    CHECK_CALIBRATION
    CHECK_ERROR_PROPAGATION
    CHECK_PROVENANCE
    CHECK_CONFIDENCE
    CHECK_SEMANTIC_CONSISTENCY
  }

  OUTPUTS {
    NORMALISED_HYBRID_COMPUTING_ENTITIES
    ANALOG_DIGITAL_MAPPINGS
    CONVERSION_RELATIONS
    SAMPLE_RELATIONS
    QUANTISATION_RELATIONS
    HYBRID_STATE_TRANSITIONS
    HYBRID_EXECUTION_TRACES
    CONTROL_RELATIONS
    SYNCHRONISATION_RELATIONS
    ERROR_MODELS
    UNCERTAINTY_ESTIMATES
    CONFIDENCE_SCORES
    EVIDENCE_LINKS
    PROVENANCE_RECORDS
    EXPLANATION_PATHS
  }

  UPDATE_MODEL {
    ON NEW_SIGNAL_OR_EXECUTION_DATA {
      NORMALISE
      UPDATE_ANALOG_STATE
      UPDATE_DIGITAL_STATE
      UPDATE_TIME_ALIGNMENT
      RECOMPUTE_CONVERSION_ERRORS
      RECOMPUTE_HYBRID_STATE
      UPDATE_CONFIDENCE
      PRESERVE_VERSION_HISTORY
    }

    ON NEW_CALIBRATION_OR_EVIDENCE {
      LINK_EVIDENCE
      UPDATE_CALIBRATION
      REASSESS_CONVERSION_RELATIONS
      REASSESS_MODEL_FIDELITY
      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_ANALOG_COMPONENT
      BY_DIGITAL_COMPONENT
      BY_SIGNAL
      BY_SAMPLE
      BY_CONVERTER
      BY_STATE
      BY_EVENT
      BY_CONTROL_LOOP
      BY_SYNCHRONISATION
      BY_ERROR
      BY_CONFIDENCE
    }

    REASON {
      APPLY_RELATIONSHIPS
      APPLY_RULES
      TRACE_ANALOG_DIGITAL_CONVERSIONS
      TRACE_SIGNAL_FLOW
      TRACE_HYBRID_STATE
      ANALYSE_SAMPLING
      ANALYSE_QUANTISATION
      ANALYSE_SYNCHRONISATION
      ANALYSE_ERROR_PROPAGATION
      CHECK_SEMANTIC_EQUIVALENCE
      PRESERVE_UNCERTAINTY
      TRACE_EVIDENCE
      TRACE_PROVENANCE
      GENERATE_EXPLANATION_PATH
    }

    RESPONSE_POLICY {
      DISTINGUISH_ANALOG_FROM_DIGITAL_REPRESENTATION
      PRESERVE_SAMPLE_RATE_AND_RESOLUTION
      PRESERVE_TIME_AND_SYNCHRONISATION_CONTEXT
      PRESERVE_CALIBRATION_CONTEXT
      RETURN_CONVERSION_UNCERTAINTY_WHEN_AVAILABLE
      RETURN_CONFIDENCE_WHEN_AVAILABLE
      RETURN_PROVENANCE_WHEN_AVAILABLE
      AVOID_UNSUPPORTED_HYBRID_COMPUTING_INFERENCE
    }
  }

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

END FLOW