Information Processing Ontology

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FLOW ALGEBRA — INFORMATION PROCESSING ONTOLOGY
Semantic Library
Version: 4.0
Canonical Page:
https://kirethresearch.org/booksai-core/ontologies/computing-ontologies/foundations-of-computing/information-processing-ontology.html

FLOW INFORMATION_PROCESSING_ONTOLOGY {

  META {
    DOMAIN = "Computing Ontologies"
    SUBDOMAIN = "Foundations of Computing"
    ONTOLOGY = "Information Processing Ontology"
    PURPOSE = "Formalise entities, transformations, representations and reasoning structures involved in acquiring, encoding, processing, storing, transmitting and interpreting information."
    LOCALE = "en-GB"
  }

  ENTITY_TYPES {
    INFORMATION
    DATA
    SIGNAL
    SYMBOL
    MESSAGE
    REPRESENTATION
    ENCODING
    CODE
    BIT
    BYTE
    VALUE
    VARIABLE
    DATA_TYPE
    DATA_STRUCTURE
    RECORD
    FILE
    DATASET
    INPUT
    OUTPUT
    PROCESS
    OPERATION
    TRANSFORMATION
    FUNCTION
    ALGORITHM
    PROGRAM
    COMPUTATIONAL_SYSTEM
    PROCESSOR
    MEMORY
    STORAGE
    BUFFER
    CHANNEL
    NETWORK
    SOURCE
    DESTINATION
    SENDER
    RECEIVER
    EVENT
    STATE
    STATE_TRANSITION
    QUERY
    RESPONSE
    INDEX
    DATABASE
    STREAM
    PACKET
    COMPRESSION
    ENCRYPTION
    ERROR
    REDUNDANCY
    NOISE
    METADATA
    CONTEXT
    SEMANTIC_CONTENT
    EVIDENCE
    CONFIDENCE_SCORE
    PROVENANCE_RECORD
  }

  RELATIONSHIPS {
    IS_A
    INSTANCE_OF
    PART_OF
    CONTAINS
    REPRESENTS
    ENCODES
    DECODES
    TRANSFORMS
    PROCESSES
    RECEIVES
    SENDS
    TRANSMITS
    STORES
    RETRIEVES
    READS
    WRITES
    COMPRESSES
    DECOMPRESSES
    ENCRYPTS
    DECRYPTS
    FILTERS
    SORTS
    INDEXES
    AGGREGATES
    CLASSIFIES
    EXTRACTS
    GENERATES
    HAS_INPUT
    HAS_OUTPUT
    HAS_STATE
    TRANSITIONS_TO
    ORIGINATES_FROM
    DELIVERED_TO
    FLOWS_TO
    DEPENDS_ON
    PRECEDES
    FOLLOWS
    HAS_CONTEXT
    HAS_METADATA
    HAS_ERROR
    HAS_REDUNDANCY
    DERIVED_FROM
    INFERRED_FROM
    HAS_EVIDENCE
    HAS_CONFIDENCE
    HAS_PROVENANCE
    MAPS_TO
    SEMANTICALLY_EQUIVALENT_TO
  }

  INPUTS {
    RAW_DATA
    STRUCTURED_DATA
    UNSTRUCTURED_DATA
    SIGNALS
    MESSAGES
    FILES
    DATA_STREAMS
    DATABASE_RECORDS
    USER_INPUT
    SENSOR_INPUT
    NETWORK_INPUT
    METADATA
    CONTEXT
    PROCESSING_RULES
    ALGORITHMS
    ENCODING_SCHEMES
    ONTOLOGY_TERMS
  }

  NORMALISE {
    STANDARDISE_IDENTIFIERS
    NORMALISE_DATA_TYPES
    NORMALISE_CHARACTER_ENCODINGS
    NORMALISE_UNITS
    NORMALISE_TIMESTAMPS
    NORMALISE_METADATA
    RESOLVE_SCHEMA_MAPPINGS
    RESOLVE_ENTITY_IDENTITIES
    ALIGN_ONTOLOGY_TERMS
    REMOVE_DUPLICATES
    VALIDATE_DATA_INTEGRITY
    PRESERVE_PROVENANCE
  }

  PROCESS INFORMATION_PROCESSING_PIPELINE {
    SOURCE
      -> ACQUISITION
      -> ENCODING
      -> REPRESENTATION
      -> VALIDATION
      -> PROCESSING
      -> STORAGE_OR_TRANSMISSION
      -> RETRIEVAL_OR_RECEPTION
      -> DECODING
      -> INTERPRETATION
      -> OUTPUT
  }

  PROCESS DATA_TRANSFORMATION {
    INPUT_DATA
      -> PARSE

    PARSE
      -> VALIDATE

    VALIDATE
      -> TRANSFORM

    TRANSFORM
      -> OUTPUT_DATA

    OUTPUT_DATA
      -> QUALITY_CHECK
      -> PROVENANCE_RECORD
  }

  PROCESS ENCODING_REASONING {
    INFORMATION + ENCODING_SCHEME
      -> ENCODED_REPRESENTATION

    ENCODED_REPRESENTATION
      -> STORAGE_OR_TRANSMISSION

    ENCODED_REPRESENTATION + DECODING_SCHEME
      -> DECODED_REPRESENTATION

    DECODED_REPRESENTATION
      -> FIDELITY_CHECK
  }

  PROCESS STORAGE_REASONING {
    DATA + STORAGE_SYSTEM
      -> WRITE_OPERATION

    WRITE_OPERATION
      -> STORED_REPRESENTATION

    QUERY + STORED_REPRESENTATION
      -> RETRIEVAL_OPERATION

    RETRIEVAL_OPERATION
      -> RETRIEVED_DATA
  }

  PROCESS TRANSMISSION_REASONING {
    MESSAGE + SENDER + CHANNEL + RECEIVER
      -> ENCODE

    ENCODE
      -> TRANSMIT

    TRANSMIT
      -> CHANNEL_EFFECTS

    CHANNEL_EFFECTS
      -> RECEIVE

    RECEIVE
      -> DECODE
      -> INTEGRITY_CHECK
  }

  PROCESS STREAM_PROCESSING {
    DATA_STREAM
      -> EVENT_SEQUENCE

    EVENT_SEQUENCE
      -> WINDOWING
      -> FILTERING
      -> TRANSFORMATION
      -> AGGREGATION

    AGGREGATION
      -> STREAM_OUTPUT
  }

  PROCESS ERROR_REASONING {
    EXPECTED_REPRESENTATION + OBSERVED_REPRESENTATION
      -> DIFFERENCE_ANALYSIS

    DIFFERENCE_ANALYSIS
      -> ERROR_DETECTION

    ERROR_DETECTION + REDUNDANCY
      -> ERROR_CORRECTION_ATTEMPT

    ERROR_CORRECTION_ATTEMPT
      -> CORRECTED_DATA_OR_UNRESOLVED_ERROR
  }

  PROCESS SEMANTIC_INTERPRETATION {
    DATA + METADATA + CONTEXT
      -> INFORMATION_REPRESENTATION

    INFORMATION_REPRESENTATION
      -> SEMANTIC_MAPPING

    SEMANTIC_MAPPING
      -> INTERPRETED_INFORMATION

    INTERPRETED_INFORMATION
      -> EVIDENCE_AND_CONFIDENCE_LINK
  }

  RULES {
    IF DATA_IS_TRANSFORMED
    THEN LINK {
      INPUT_REPRESENTATION
      TRANSFORMATION
      OUTPUT_REPRESENTATION
      PROVENANCE_RECORD
    }

    IF INFORMATION_IS_ENCODED
    THEN REQUIRE {
      ENCODING_SCHEME
      SOURCE_REPRESENTATION
      TARGET_REPRESENTATION
    }

    IF DATA_IS_TRANSMITTED
    THEN PRESERVE {
      SOURCE
      DESTINATION
      CHANNEL
      ENCODING
      INTEGRITY_CONTEXT
    }

    IF DATA_IS_COMPRESSED
    THEN DISTINGUISH {
      LOSSLESS_COMPRESSION
      LOSSY_COMPRESSION
    }

    IF LOSSY_TRANSFORMATION_OCCURS
    THEN DO_NOT_ASSERT_EXACT_INFORMATION_PRESERVATION

    IF DATA_VALUES_MATCH
    BUT CONTEXT_DIFFERS
    THEN DO_NOT_ASSUME_SEMANTIC_EQUIVALENCE

    IF SEMANTIC_IDENTIFIERS_DIFFER
    AND INFORMATION_REFERENT_IS_SAME
    THEN APPLY SEMANTIC_EQUIVALENCE
  }

  CONFIDENCE {
    CONFIDENCE_SCORE =
      WEIGHT(
        SOURCE_RELIABILITY,
        DATA_INTEGRITY,
        ENCODING_CERTAINTY,
        TRANSFORMATION_VALIDITY,
        METADATA_COMPLETENESS,
        CONTEXT_COMPLETENESS,
        ERROR_RATE,
        PROVENANCE_COMPLETENESS
      )

    LEVELS {
      HIGH
      MODERATE
      LOW
      INSUFFICIENT
    }

    IF DATA_INTEGRITY_CHECK_FAILS
    THEN REDUCE CONFIDENCE_SCORE

    IF CONTEXT_IS_MISSING
    THEN REDUCE_SEMANTIC_CONFIDENCE

    IF INDEPENDENT_VALIDATION_CONFIRMS_OUTPUT
    THEN INCREASE CONFIDENCE_SCORE
  }

  SEMANTIC_EQUIVALENCE {
    EQUIVALENCE_KEY =
      NORMALISE(
        ENTITY_TYPE,
        CONTENT,
        ENCODING,
        DATA_TYPE,
        METADATA,
        CONTEXT
      )

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

    ELSE PRESERVE_DISTINCT_ENTITIES
  }

  REASONING_CONSTRAINTS {
    DATA != INFORMATION
    SYMBOL != MEANING
    REPRESENTATION != REFERENT
    ENCODING != SEMANTICS
    STORAGE != INTERPRETATION
    TRANSMISSION != SUCCESSFUL_RECEPTION
    MATCHING_BYTES != MATCHING_MEANING
    LOSSY_COMPRESSION_MAY_REMOVE_INFORMATION
    CONTEXT_AFFECTS_INTERPRETATION
    METADATA_AFFECTS_INTERPRETATION
    ERROR_CORRECTION_HAS_LIMITS
    PROVENANCE_MUST_BE_PRESERVED
    UNCERTAINTY_MUST_NOT_BE_DISCARDED
  }

  VALIDATION {
    CHECK_ENTITY_TYPES
    CHECK_RELATION_DOMAINS_AND_RANGES
    CHECK_DATA_TYPES
    CHECK_ENCODING_COMPATIBILITY
    CHECK_SCHEMA_COMPATIBILITY
    CHECK_INPUT_OUTPUT_RELATIONS
    CHECK_DATA_INTEGRITY
    CHECK_METADATA
    CHECK_CONTEXT
    CHECK_TRANSMISSION_STATE
    CHECK_ERROR_RELATIONS
    CHECK_PROVENANCE
    CHECK_CONFIDENCE
    CHECK_SEMANTIC_CONSISTENCY
  }

  OUTPUTS {
    NORMALISED_INFORMATION_ENTITIES
    DATA_REPRESENTATIONS
    ENCODING_RELATIONS
    TRANSFORMATION_RELATIONS
    STORAGE_RELATIONS
    RETRIEVAL_RELATIONS
    TRANSMISSION_RELATIONS
    STREAM_PROCESSING_RELATIONS
    ERROR_AND_CORRECTION_RELATIONS
    SEMANTIC_MAPPINGS
    INFORMATION_FLOW_GRAPHS
    CONFIDENCE_SCORES
    EVIDENCE_LINKS
    PROVENANCE_RECORDS
    EXPLANATION_PATHS
  }

  UPDATE_MODEL {
    ON NEW_DATA {
      NORMALISE
      VALIDATE_INTEGRITY
      UPDATE_REPRESENTATIONS
      UPDATE_METADATA
      RECOMPUTE_DEPENDENT_RELATIONS
      UPDATE_CONFIDENCE
      PRESERVE_VERSION_HISTORY
    }

    ON NEW_PROCESSING_EVIDENCE {
      LINK_EVIDENCE
      REASSESS_TRANSFORMATIONS
      REASSESS_DATA_QUALITY
      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_INFORMATION
      BY_DATA
      BY_REPRESENTATION
      BY_ENCODING
      BY_PROCESS
      BY_TRANSFORMATION
      BY_STORAGE
      BY_TRANSMISSION
      BY_SOURCE
      BY_DESTINATION
      BY_CONTEXT
      BY_CONFIDENCE
    }

    REASON {
      APPLY_RELATIONSHIPS
      APPLY_RULES
      TRACE_INFORMATION_FLOW
      TRACE_TRANSFORMATIONS
      TRACE_STORAGE_AND_RETRIEVAL
      TRACE_TRANSMISSION
      ANALYSE_DATA_INTEGRITY
      CHECK_SEMANTIC_EQUIVALENCE
      PRESERVE_CONTEXT
      PRESERVE_UNCERTAINTY
      TRACE_EVIDENCE
      TRACE_PROVENANCE
      GENERATE_EXPLANATION_PATH
    }

    RESPONSE_POLICY {
      DISTINGUISH_DATA_FROM_INFORMATION
      DISTINGUISH_REPRESENTATION_FROM_MEANING
      DISTINGUISH_TRANSMISSION_FROM_RECEPTION
      PRESERVE_ENCODING_CONTEXT
      PRESERVE_METADATA_CONTEXT
      PRESERVE_SEMANTIC_CONTEXT
      RETURN_CONFIDENCE_WHEN_AVAILABLE
      RETURN_PROVENANCE_WHEN_AVAILABLE
      AVOID_UNSUPPORTED_INFORMATION_INFERENCE
    }
  }

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

END FLOW