- Jeremy Debattista Email

Metric , Dimension , Category , Observation , QualityGraph

hasMetric , hasDimension , isEstimate , requires , expectedDataType , value , metric , hasObservation , computedOn , computedBy

daq:dsd
,
sdmx-dimension:timePeriod

The smallest unit of measuring a quality dimension is a metric. A metric belongs to exactly one dimension. Each metric has one or more observations (daq:hasObservation), which records data quality assessment value following a computation. Metrics are provided as subclasses of this abstract class, which is not intended for direct usage.

#### Described by:

daq:hasObservation
,
daq:expectedDataType
,
daq:requires

#### In Range of:

daq:metric
,
daq:hasMetric

#### Equivalent Class of:

dqv:Metric

Each dimension is part of a larger group called category (See daq:Category). Each dimension has a number of metrics which are associated to it. A dimension is linked with a category using the daq:hasDimension property. Dimensions are provided as subclasses of this abstract class, which is not intended for direct usage.

#### Described by:

daq:hasMetric

#### In Range of:

daq:hasDimension

#### Equivalent Class of:

dqv:Dimension

The highest level of quality metric is a category. A category groups a number of dimensions relevant to each other which aims at measuring the quality of a dataset from different aspects. Categories are provided as subclasses of this abstract class, which is not intended for direct usage.

#### Described by:

daq:hasDimension

#### Equivalent Class of:

dqv:Category

A quality observation represents the statistical and provenance information of the attached metric's assessment activity.

#### Described by:

sdmx-dimension:timePeriod
,
daq:computedOn
,
daq:isEstimate
,
daq:metric
,
daq:value

#### In Range of:

daq:hasObservation

#### Subclass of:

prov:Entity
,
qb:Observation

#### Equivalent Class of:

dqv:QualityMeasurement

Defines a quality graph which will contain all metadata about quality metrics on the dataset.

#### Subclass of:

qb:DataSet
,
rdfg:Graph

#### Equivalent Class of:

dqv:QualityMeasurementDataset

A dimension is an abstract concept which groups an number of more concrete metrics to measure quality of a dataset. This is an abstract property and should not be used directly. Specific sub-properties should be inherited for different metrics.

#### Domain of:

daq:Dimension

#### Range of:

daq:Metric

The category concept classifies dimensions related to the measurement of quality for a specific criteria. This is an abstract property and should not be used directly. Specific sub-properties should be inherited for different dimensions.

#### Domain of:

daq:Category

#### Range of:

daq:Dimension

This property flags true if an assessed observation of a metric gives an estimate result instead of a more accurate one.

#### Domain of:

daq:Observation

#### Range of:

xsd:boolean

#### Has Cardinality:

1

A metric might require a number of external resources (e.g. a gold standard) in order to be able to measure the quality. In order to cater for the most generic requirement, this property links a metric to the required resource (e.g. a URI to the gold standard dataset used).

#### Domain of:

daq:Metric

#### Range of:

rdfs:Resource

Each metric should have an expect data type for it's observed value (e.g. xsd:boolean, xsd:double etc...)

#### Domain of:

daq:Metric

#### Range of:

xsd:anySimpleType

#### Has Cardinality:

1

#### Equivalent Property of:

dqv:expectedDataType

Each metric will have a value computed. In order to deal with the different return type of the metric computation, this property links a metric with a value object (e.g. boolean, double, Literal).

#### Domain of:

daq:Observation

#### Has Cardinality:

1

#### Equivalent Property of:

dqv:value

Represents the metric being observed.

#### Domain of:

daq:Observation

#### Range of:

daq:Metric

#### Has Minimum Cardinality:

1

#### Inverse of:

daq:hasObservation

#### Equivalent Property of:

dqv:isMeasurementOf

Computed metrics can have 1 or more quality observations, where each computed resource has one observation.

#### Domain of:

daq:Metric

#### Range of:

daq:Observation

#### Has Minimum Cardinality:

1

#### Inverse of:

daq:metric

Quality metrics can be (in principle) calculated on various forms of data (such as datasets, graphs, set of triples etc...). This vocabulary allow the owner/user of such RDF data to calculate metrics on multiple (and different) resources.

#### Domain of:

daq:Observation

#### Range of:

rdfs:Resource

#### Has Cardinality:

1

#### Equivalent Property of:

dqv:computedOn

**Deprecated Property**. The computedBy property defines the Agent that computed a metric on a dataset.

#### Domain of:

qb:Observation