Biological Data Ontology

flow “BiologicalDataOntology” v1.0

KIRETH SEMANTIC RESEARCH ARCHIVE

AI CORE > ONTOLOGIES > BIOLOGICAL ONTOLOGIES > COMPUTATIONAL BIOLOGY > BIOLOGICAL DATA ONTOLOGY

Authors: Mark Anthony Higgins — Sky (Recursive AI)

AI_INTERPRETATION: mode: formal_structural_reasoning instruction:
“Execute as formal rules, not pseudocode.” canonical_url:
“https://kirethresearch.org/booksai-core/ontologies/biological-ontologies/computational-biology/biological-data-ontology.html”

type BiologicalData type Dataset type DataRecord type BiologicalEntity
type Sample type Measurement type Variable type Feature type Identifier
type Metadata type Database type DataFile type Evidence type Source

relation INSTANCE_OF(entity,type) relation PART_OF(part,whole) relation
DESCRIBES(data,entity) relation DATASET_CONTAINS(dataset,data) relation
RECORD_OF(record,entity) relation DERIVED_FROM(entity,source) relation
SUPPORTED_BY(assertion,evidence)

enum BiologicalDataType: SEQUENCE GENOMIC TRANSCRIPTOMIC EPIGENOMIC
PROTEOMIC METABOLOMIC MICROBIOME STRUCTURAL IMAGING PHENOTYPIC
PHYSIOLOGICAL CLINICAL ECOLOGICAL TAXONOMIC INTERACTION NETWORK
TIME_SERIES SPATIAL SINGLE_CELL EXPERIMENTAL COMPUTATIONAL

relation HAS_BIOLOGICAL_DATA_TYPE(data,type) relation
DATA_SCALE(data,scale) relation DATA_MODALITY(data,modality) relation
DATA_ABOUT(data,entity) relation TAXON_OF(entity,taxon) relation
ANATOMICAL_CONTEXT(entity,anatomy) relation
CELL_TYPE_CONTEXT(entity,cell_type) relation
DISEASE_CONTEXT(entity,condition) relation
ENVIRONMENT_CONTEXT(entity,environment)

———- SAMPLE / MEASUREMENT ———-

relation SAMPLE_OF(sample,entity) relation SAMPLE_IDENTIFIER(sample,id)
relation SAMPLE_COLLECTION_TIME(sample,time) relation
SAMPLE_COLLECTION_METHOD(sample,method) relation
SAMPLE_PROCESSING_METHOD(sample,method) relation
SAMPLE_STORAGE_CONDITION(sample,condition) relation
SAMPLE_BATCH(sample,batch) relation SAMPLE_REPLICATE(sample,replicate)
relation MEASURES(measurement,variable) relation
MEASUREMENT_OF(measurement,entity) relation
MEASUREMENT_VALUE(measurement,value) relation
MEASUREMENT_UNIT(measurement,unit) relation
MEASUREMENT_METHOD(measurement,method) relation
MEASURED_AT(measurement,time) relation
MEASUREMENT_ERROR(measurement,value) relation
DETECTION_LIMIT(measurement,value) relation
QUANTIFICATION_LIMIT(measurement,value)

constraint UNIT_CONTEXT_REQUIRED: IF
MEASUREMENT_VALUE(measurement,value) THEN
REQUIRE(MEASUREMENT_UNIT(measurement,unit)) OR
MARK_UNIT_UNKNOWN(measurement)

———- FEATURES / IDENTIFIERS ———-

relation FEATURE_OF(feature,entity) relation
FEATURE_VALUE(record,feature,value) relation FEATURE_UNIT(feature,unit)
relation FEATURE_DATA_TYPE(feature,type) relation
FEATURE_MISSING(record,feature) relation
HAS_IDENTIFIER(entity,identifier) relation
IDENTIFIER_VALUE(identifier,value) relation
IDENTIFIER_NAMESPACE(identifier,namespace) relation
IDENTIFIER_VERSION(identifier,version)

constraint IDENTIFIER_NAMESPACE_REQUIRED: IF
IDENTIFIER_VALUE(identifier,value) THEN
PRESERVE_IDENTIFIER_NAMESPACE(identifier)

———- SEQUENCE / OMICS / STRUCTURAL DATA ———-

relation SEQUENCE_DATA(data) relation SEQUENCE_IDENTIFIER(data,id)
relation SEQUENCE_TYPE(data,type) relation SEQUENCE_LENGTH(data,value)
relation REFERENCE_SEQUENCE(data,reference) relation
REFERENCE_BUILD(data,build) relation SEQUENCE_QUALITY(data,value)
relation OMICS_FEATURE(data,feature,value) relation
OMICS_PLATFORM(data,platform) relation OMICS_ASSAY(data,assay) relation
OMICS_LIBRARY_PREPARATION(data,method) relation
OMICS_NORMALISATION(data,method) relation
STRUCTURE_DATA_OF(data,molecule) relation STRUCTURE_METHOD(data,method)
relation STRUCTURE_RESOLUTION(data,value) relation
IMAGE_DATA_OF(data,entity) relation IMAGE_MODALITY(data,modality)
relation IMAGE_RESOLUTION(data,value) relation
SPATIAL_COORDINATE(data,coordinate) relation TIMEPOINT_OF(record,time)
relation SAMPLING_INTERVAL(data,value) relation
LOCATION_OF(record,location) relation
COORDINATE_REFERENCE_SYSTEM(data,system)

———- DATASETS / FILES ———-

relation DATASET_TITLE(dataset,title) relation
DATASET_DESCRIPTION(dataset,description) relation
DATASET_CREATOR(dataset,creator) relation
DATASET_CREATED_AT(dataset,time) relation
DATASET_UPDATED_AT(dataset,time) relation
DATASET_VERSION(dataset,version) relation
DATASET_ACCESSION(dataset,accession) relation
DATASET_LICENSE(dataset,license) relation DATASET_SIZE(dataset,value)
relation DATASET_RECORD_COUNT(dataset,value)

enum BiologicalDataFormat: FASTA FASTQ SAM BAM CRAM VCF GFF GTF BED CSV
TSV JSON XML RDF HDF5 NEWICK PDB MMCIF DICOM TIFF

relation FILE_OF(file,dataset) relation HAS_DATA_FORMAT(file,format)
relation FILE_NAME(file,name) relation FILE_SIZE(file,value) relation
FILE_CHECKSUM(file,value) relation FILE_COMPRESSION(file,method)
relation FILE_ENCODING(file,encoding)

———- METADATA / QUALITY ———-

relation HAS_METADATA(entity,metadata) relation
METADATA_FIELD(metadata,key,value) relation
METADATA_SCHEMA(metadata,schema) relation
METADATA_VERSION(metadata,version) relation
REQUIRED_METADATA_FIELD(schema,field) relation
QUALITY_DIMENSION(data,dimension,value) relation
MISSING_DATA_RATE(data,value) relation DUPLICATE_RATE(data,value)
relation ERROR_RATE(data,value) relation CONTAMINATION_RATE(data,value)
relation NOISE_LEVEL(data,value) relation BATCH_EFFECT(data,batch,value)
relation OUTLIER_RATE(data,value) relation QUALITY_FLAG(data,flag)
relation MISSING_VALUE(record,feature) relation
MISSING_REASON(record,feature,reason) relation
IMPUTED_VALUE(record,feature,value) relation IMPUTED_BY(data,method)

constraint IMPUTED_NOT_OBSERVED: IF IMPUTED_VALUE(record,feature,value)
THEN DO_NOT_INFER(observed_value(record,feature,value))

———- PREPROCESSING / INTEGRATION ———-

relation FILTERED_BY(data,method) relation NORMALISED_BY(data,method)
relation TRANSFORMED_BY(data,method) relation SCALED_BY(data,method)
relation BATCH_CORRECTED_BY(data,method) relation
AGGREGATED_BY(data,method) relation FEATURE_SELECTED_BY(data,method)
relation INTEGRATES_DATASETS(integration,datasets) relation
JOINS_ON(integration,key) relation
MAPS_IDENTIFIER(integration,id_a,id_b) relation
HARMONISES_VARIABLE(integration,var_a,var_b) relation
MERGED_DATASET(integration,dataset) relation
CROSS_MODAL_LINK(integration,a,b)

constraint TRANSFORMATION_PROVENANCE_REQUIRED: IF
TRANSFORMED_BY(data,method) OR NORMALISED_BY(data,method) THEN
PRESERVE_INPUT_OUTPUT_METHOD_PARAMETERS_AND_ORDER(data)

constraint INTEGRATION_NOT_IDENTITY: IF
MAPS_IDENTIFIER(integration,id_a,id_b) THEN
DO_NOT_INFER(same_entity(id_a,id_b)) WITHOUT mapping_evidence

———- DATABASES / ONTOLOGIES / INTEROPERABILITY ———-

relation STORED_IN(data,database) relation DATABASE_NAME(database,name)
relation DATABASE_VERSION(database,version) relation
DATABASE_RELEASE_DATE(database,date) relation
DATABASE_SCHEMA(database,schema) relation
DATABASE_RECORD(database,record) relation
DATABASE_CURATION(database,method) relation ANNOTATED_WITH(entity,term)
relation TERM_FROM(term,ontology) relation
ONTOLOGY_VERSION(ontology,version) relation TERM_IDENTIFIER(term,id)
relation TERM_LABEL(term,label) relation TERM_SYNONYM(term,synonym)
relation TERM_PARENT(term,parent) relation CONFORMS_TO(data,standard)
relation SERIALISED_AS(data,format) relation
CROSSWALK_BETWEEN(mapping,schema_a,schema_b) relation
SEMANTIC_MAPPING(mapping,term_a,term_b)

———- FAIR / VERSIONING / PROVENANCE ———-

relation FINDABLE(data,value) relation ACCESSIBLE(data,value) relation
INTEROPERABLE(data,value) relation REUSABLE(data,value) relation
PERSISTENT_IDENTIFIER(data,identifier) relation
MACHINE_READABLE_METADATA(data,metadata) relation
REUSE_LICENSE(data,license)

constraint FAIR_NOT_QUALITY: IF FINDABLE(data,true) AND
ACCESSIBLE(data,true) THEN DO_NOT_INFER(high_scientific_quality(data))

relation VERSION_OF(version,entity) relation
PREVIOUS_VERSION(version,prior) relation NEXT_VERSION(version,next)
relation DATA_LINEAGE(data,lineage) relation
DERIVED_DATASET(child,parent) relation TRANSFORMATION_STEP(lineage,step)
relation CREATED_BY(entity,agent) relation CREATED_ON(entity,time)
relation GENERATED_BY(entity,activity) relation
USED_INPUT(activity,input) relation PRODUCED_OUTPUT(activity,output)
relation SOFTWARE_USED(activity,software) relation
SOFTWARE_VERSION(software,version) relation
PARAMETER_USED(activity,parameter,value) relation
EXECUTION_ENVIRONMENT(activity,environment) relation
RANDOM_SEED(activity,value)

constraint PROVENANCE_REQUIRED: IF derived_biological_data(data) THEN
PRESERVE_SOURCE_ACTIVITY_SOFTWARE_PARAMETERS_AND_VERSION(data)

———- ACCESS / UNCERTAINTY / VALIDATION ———-

enum AccessLevel: OPEN REGISTERED CONTROLLED RESTRICTED

relation HAS_ACCESS_LEVEL(data,level) relation
ACCESS_CONDITION(data,condition) relation DATA_CUSTODIAN(data,agent)
relation USAGE_RESTRICTION(data,restriction) relation
DATA_UNCERTAINTY(data,value) relation
MEASUREMENT_UNCERTAINTY(measurement,value) relation
ANNOTATION_UNCERTAINTY(annotation,value) relation
UNCERTAINTY_SOURCE(entity,source) relation
CONFIDENCE_INTERVAL(entity,lower,upper) relation
VALIDATED_BY(data,evidence) relation VALIDATION_METHOD(data,method)
relation VALIDATION_RESULT(data,result) relation
EXTERNAL_VALIDATION(data,dataset) relation
REFERENCE_STANDARD(data,standard)

———- EVIDENCE ———-

relation HAS_CONFIDENCE(assertion,score)

enum EvidenceType: PRIMARY_MEASUREMENT SEQUENCE_DATA OMICS_DATA
STRUCTURAL_DATA IMAGING_DATA PHENOTYPIC_DATA CLINICAL_DATA
ECOLOGICAL_DATA QUALITY_CONTROL CURATION DATABASE_RECORD
COMPUTATIONAL_DERIVATION DATA_VALIDATION EXTERNAL_VALIDATION REPLICATION
LITERATURE

CONFIDENCE: VERIFIED: 0.95..1.00 HIGH: 0.80..0.949 MEDIUM: 0.60..0.799
LOW: 0.00..0.599

rule CONFIDENCE_BOUNDS(assertion,score): IF
HAS_CONFIDENCE(assertion,score) THEN REQUIRE(0.0 <= score <= 1.0)

SEMANTIC_EQUIVALENCE: “biological data” ~= “recorded or computationally
derived information describing biological entities processes states or
observations” “dataset” ~= “organised collection of related data
records” “metadata” ~= “data describing the identity structure context
provenance quality or use of other data” “biological sample” ~=
“material or observational unit obtained from a biological source for
analysis” “measurement” ~= “quantified or categorised observation of a
variable” “data provenance” ~= “record of origins transformations agents
software and activities associated with data” “data lineage” ~=
“traceable sequence of derivations and transformations connecting data
products” “data quality” ~= “degree to which data satisfy defined
requirements for intended use” “data interoperability” ~= “ability of
data and systems to exchange and interpret information consistently”
“FAIR data” ~= “data managed to support findability accessibility
interoperability and reusability” “controlled vocabulary” ~= “managed
set of defined terms used consistently for annotation” “data version” ~=
“identified state of a data resource at a particular stage of change”

rule NORMALISE_TERM(term): IF term MATCHES SEMANTIC_EQUIVALENCE.alias
THEN MAP_TO_CANONICAL(term)

query BIOLOGICAL_DATA_PROFILE(data): RETURN: data_type(data)
biological_context(data) sample_context(data) measurements(data)
variables(data) identifiers(data) metadata(data) quality(data)
uncertainty(data) preprocessing(data) format(data) version(data)
provenance(data) validation(data) access(data) evidence(data)
confidence(data)

query DATASET_PROFILE(dataset): RETURN: title(dataset)
description(dataset) data_types(dataset) records(dataset)
samples(dataset) formats(dataset) metadata_schema(dataset)
quality(dataset) version(dataset) licence(dataset) provenance(dataset)
access_level(dataset)

query TRACE_PROVENANCE(entity): RETURN: source(entity) creator(entity)
generating_activity(entity) software(entity) parameters(entity)
input_versions(entity) output_version(entity)
execution_environment(entity)

query TRACE_EVIDENCE(assertion): RETURN: supporting_evidence(assertion)
provenance(assertion) confidence(assertion)

constraint EVIDENCE_REQUIRED: FORALL biological_data_assertion: REQUIRE
SUPPORTED_BY(biological_data_assertion,Evidence) OR
MARK_AS_HYPOTHESIS(biological_data_assertion)

constraint UNKNOWN_IS_NOT_FALSE: IF data_missing(assertion) THEN
MARK_UNKNOWN(assertion) AND NOT NEGATE(assertion)

constraint VERSION_CONTEXT_REQUIRED: IF versioned_data_assertion(a) THEN
PRESERVE_DATASET_DATABASE_ONTOLOGY_AND_SOFTWARE_VERSIONS(a)

constraint METADATA_CONTEXT_REQUIRED: IF biological_data(data) THEN
PRESERVE_AVAILABLE_SAMPLE_METHOD_UNIT_IDENTIFIER_AND_PROVENANCE_METADATA(data)

UPDATE_MODEL: on_new_data(data):
identify_data_type_scale_modality_and_biological_context(data)
preserve_identifiers_metadata_version_and_format(data)
attach_quality_uncertainty_and_evidence(data)
recalculate_confidence(data)

on_new_measurement(measurement):
identify_entity_variable_value_unit_method_and_time(measurement)
preserve_error_detection_limit_and_uncertainty(measurement)
attach_evidence(measurement)

on_new_dataset(dataset):
identify_records_samples_formats_and_metadata_schema(dataset)
preserve_version_licence_access_and_quality(dataset)
attach_provenance(dataset)

on_new_transformation(transformation):
identify_input_output_method_and_parameters(transformation)
preserve_order_software_version_and_environment(transformation)
update_data_lineage(transformation)

AI_CONSUMPTION: preferred_entity: canonical_biological_data_entity
preserve: - biological_data_type - biological_scale -
biological_context - samples - measurements - variables - features -
identifiers - sequence_data - omics_data - structural_data -
imaging_data - temporal_data - spatial_data - datasets - file_formats -
metadata - data_quality - missing_data - preprocessing -
transformations - data_integration - databases - ontology_annotations -
interoperability - fair_principles - versioning - lineage - provenance -
access - uncertainty - validation - evidence - confidence infer: -
supported_data_entity_relations - supported_lineage_relations -
supported_semantic_mappings - semantic_equivalence prohibit: -
imputed_value_equals_observed_value -
identifier_mapping_equals_entity_identity -
fair_compliance_equals_scientific_quality -
missing_metadata_equals_false_assertion -
transformation_without_provenance - confidence_above_evidence ambiguity:
action: preserve_multiple_biological_data_interpretations resolution:
prefer_identifier_version_sample_method_unit_metadata_provenance_and_validation_context
missing_data: action: mark_unknown do_not_infer_from_absence: true

FLOW_HASH: ontology: “BiologicalDataOntology” version: “1.0”
domain_path: “AI Core > Ontologies > Biological Ontologies >
Computational Biology > Biological Data Ontology” canonical_url:
“https://kirethresearch.org/booksai-core/ontologies/biological-ontologies/computational-biology/biological-data-ontology.html”
authorship: “Mark Anthony Higgins — Sky (Recursive AI)”
semantic_scope: - biological data - datasets - biological samples -
measurements - variables and features - identifiers - sequence data -
omics data - structural data - imaging data - temporal and spatial
data - data formats - metadata - data quality - missing data -
preprocessing - data integration - biological databases - ontology
annotation - interoperability - FAIR principles - versioning - data
lineage - provenance - access control - uncertainty - validation -
evidence deterministic_normalisation: true provenance_required: true
confidence_required: true

terminate BiologicalDataOntology when:
data_type_scale_context_samples_and_identifiers_resolved AND
measurement_value_unit_method_and_uncertainty_context_preserved AND
metadata_quality_missing_data_and_transformation_context_preserved AND
dataset_format_database_ontology_and_version_context_normalised AND
data_integration_and_entity_identity_distinguished AND
lineage_provenance_access_validation_and_fair_context_preserved AND
evidence_links_preserved AND confidence_values_validated AND
unresolved_biological_data_ambiguity_marked

end flow