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net.sansa_stack.rdf.flink.qualityassessment

QualityAssessmentOperations

implicit class QualityAssessmentOperations extends AnyRef

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Instance Constructors

  1. new QualityAssessmentOperations(triples: DataSet[Triple])

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  5. def assessAmountOfTriples(): Double

    Computes the size of the triples.

  6. def assessCoverageDetail(): Double

    This metric measures the the coverage (i.e.

    This metric measures the the coverage (i.e. number of entities described in a dataset) and level of detail (i.e. number of properties) in a dataset to ensure that the data retrieved is appropriate for the task at hand.

  7. def assessCoverageScope(): Double

    This metric calculate the coverage of a dataset referring to the covered scope.

    This metric calculate the coverage of a dataset referring to the covered scope. This covered scope is expressed as the number of 'instances' statements are made about.

  8. def assessDereferenceableBackLinks(): Double

    This metric measures the extent to which a resource includes all triples from the dataset that have the resource's URI as the object.

    This metric measures the extent to which a resource includes all triples from the dataset that have the resource's URI as the object. The ratio computed is the number of objects that are "back-links" (are part of the resource's URI) and the total number of objects.

  9. def assessDereferenceableForwardLinks(): Double

    This metric measures the extent to which a resource includes all triples from the dataset that have the resource's URI as the subject.

    This metric measures the extent to which a resource includes all triples from the dataset that have the resource's URI as the subject. The ratio computed is the number of subjects that are "forward-links" (are part of the resource's URI) and the total number of subjects.

  10. def assessDereferenceableUris(): Double

    This metric calculates the number of valid redirects of URI.

    This metric calculates the number of valid redirects of URI. It computes the ratio between the number of all valid redirects (subject + predicates + objects)a.k.a dereferencedURIS and the total number of URIs on the dataset.

  11. def assessHumanReadableLicense(): Double

    Human -readable indication of a license This metric checks whether a human-readable text, stating the of licensing model attributed to the resource, has been provided as part of the dataset.

    Human -readable indication of a license This metric checks whether a human-readable text, stating the of licensing model attributed to the resource, has been provided as part of the dataset. It looks for objects containing literal values and analyzes the text searching for key, licensing related terms.

  12. def assessInterlinkingCompleteness(): Long

    This metric measures the interlinking completeness.

    This metric measures the interlinking completeness. Since any resource of a dataset can be interlinked with another resource of a foreign dataset this metric makes a statement about the ratio of interlinked resources to resources that could potentially be interlinked.

  13. def assessLabeledResources(): Double

    This metric assess the labeled resources.

  14. def assessLiteralNumericRangeChecker(): Long

    Check if the incorrect numeric range for the given predicate and given class of subjects.

    Check if the incorrect numeric range for the given predicate and given class of subjects. A user should specify the RDF class, the RDF property for which he would like to verify if the values are in the specified range determined by the user. The range is specified by the user by indicating the lower and the upper bound of the value.

  15. def assessMachineReadableLicense(): Double

    Machine -readable indication of a license This metric checks whether a machine-readable text, stating the of licensing model attributed to the resource, has been provided as part of the dataset.

    Machine -readable indication of a license This metric checks whether a machine-readable text, stating the of licensing model attributed to the resource, has been provided as part of the dataset. It looks for objects containing literal values and analyzes the text searching for key, licensing related terms.

  16. def assessNoHashUris(): Double

    Checks if a URI contains hashs.

  17. def assessPropertyCompleteness(): Long

    This metric measures the property completeness by checking the missing object values for the given predicate and given class of subjects.

    This metric measures the property completeness by checking the missing object values for the given predicate and given class of subjects. A user specifies the RDF class and the RDF predicate, then it checks for each pair whether instances of the given RDF class contain the specified RDF predicate.

  18. def assessQueryParamFreeURIs(): Double

    This metric calculates the number of non Queryable URIs.

    This metric calculates the number of non Queryable URIs. It computes the ratio between the number of all non queryable URIs and the total number of URIs on the dataset.

  19. def assessSchemaCompleteness(): Double

    This metric measures the ratio of the number of classes and relations of the gold standard existing in g, and the number of classes and relations in the gold standard.

  20. def assessShortURIs(): Double

    This metric calculates the number of long URIs.

    This metric calculates the number of long URIs. It computes the ratio between the number of all long URIs and the total number of URIs on the dataset.

  21. def assessXSDDatatypeCompatibleLiterals(): Long

    Check if the value of a typed literal is valid with regards to the given xsd datatype.

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