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<title>Data on the Web Best Practices: Data Quality Vocabulary</title>
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<section id="abstract">
<p>This document provides a framework in which the quality of a
dataset can be described, whether by the dataset publisher or by a
broader community of users. It does not provide a formal, complete
definition of quality, rather, it sets out a consistent means by
which information can be provided such that a potential user of a
dataset can make his/her own judgment about its fitness for purpose.
</p>
</section>
<section id="sotd">
<p>The model for the Data Quality Vocabulary is nearing maturity,
but the Working Group is seeking feedback on a number of specific
issues highlighted in the document below.</p>
</section>
<section id="toc"></section>
<section >
<h2 id="intro">Introduction</h2>
<p>
The Data on the Web Best Practices <a
href="http://www.w3.org/TR/dwbp/">Working Draft</a> has pointed out
the relevance of <a href="http://www.w3.org/TR/dwbp/#quality">publishing
information about the quality of data published on the Web</a>.
Accordingly, the <a href="http://www.w3.org/2013/dwbp/wiki/Main_Page">Data
on the Web Best Practices Working Group</a> has been chartered to create
a vocabulary for expressing data quality. The Data Quality Vocabulary
(DQV) presented in this document is foreseen as an extension to DCAT
[[vocab-dcat]] to cover the quality of the data, how frequently is it
updated, whether it accepts user corrections, persistence commitments
etc. When used by publishers, this vocabulary will foster trust in
the data amongst developers.
</p>
<p>This vocabulary does not seek to determine what
"quality" means. We believe that quality lies in the eye of
the beholder; that there is no objective, ideal definition of it.
Some datasets will be judged as low-quality resources by some data
consumers, while they will perfectly fit others' needs. In
accordance, we attach a lot of importance to allowing many actors to
assess the quality of datasets and publish their annotations,
certificates, opinions about a dataset. A dataset's publisher should
seek to publish metadata that helps data consumers determine whether
they can use the dataset to their benefit. However, publishers should
not be the only ones to have a say on the quality of data published
in an open environment like the Web. Certification agencies, data
aggregators, data consumers can make relevant quality assessments,
too.</p>
<p>We want to stimulate this by making it easier to publish,
exchange and consume quality metadata, for every step of a dataset's
lifecycle. This is why next to rather expected constructs like
quality measures, the Data Quality Vocabulary puts an emphasis
on feedback, annotation, agreements.</p>
<p>Note that DQV elements can be applied not only to
express metadata on the quality of datasets; they can also be used to express
statements about the quality of that metadata itself. This is especially true when it
comes to representing the provenance of that metadata or its conformance with respect
to established metadata standards.</p>
</section>
<section id="namespaces">
<h2>Namespaces</h2>
<p>
The namespace for DQV is provisionally set as
<code>http://www.w3.org/ns/dqv#</code>
. DQV, however, seeks to re-use elements from other vocabularies,
notably <a href="http://www.w3.org/ns/dcat#">DCAT</a>, following the
<a href="http://www.w3.org/TR/dwbp/#dataVocabularies">best
practices for data vocabularies</a> identified by the Data on the Web
Best Practices Working Group.
</p>
<!-- <div class="note">
<p>A first RDF representation of DQV has been created and is temporarily accessible at <a href="http://w3c.github.io/dwbp/dqv.ttl">http://w3c.github.io/dwbp/dqv.ttl</a>.</p>
</div> -->
<p>The table below indicates the full list of namespaces and
prefixes used in this document.</p>
<table id="namespacesTable">
<thead>
<tr>
<th>Prefix</th>
<th>Namespace</th>
</tr>
</thead>
<tbody>
<tr>
<td>daq</td>
<td>http://purl.org/eis/vocab/daq#</td>
</tr>
<tr>
<td>dcat</td>
<td>http://www.w3.org/ns/dcat#</td>
</tr>
<tr>
<td>dcterms</td>
<td>http://purl.org/dc/terms/</td>
</tr>
<tr>
<td>dqv</td>
<td>http://www.w3.org/ns/dqv#</td>
</tr>
<tr>
<td>duv</td>
<td>http://www.w3.org/ns/duv#</td>
</tr>
<tr>
<td>oa</td>
<td>http://www.w3.org/ns/oa#</td>
</tr>
<tr>
<td>prov</td>
<td>http://www.w3.org/ns/prov#</td>
</tr>
<tr>
<td>sdmx-attribute</td>
<td>http://purl.org/linked-data/sdmx/2009/attribute#</td>
</tr>
<tr>
<td>skos</td>
<td>http://www.w3.org/2004/02/skos/core#</td>
</tr>
</tbody>
</table>
</section>
<section id="model">
<h2>Vocabulary Overview</h2>
<p>The following vocabulary is based on DCAT [[vocab-dcat]] that
it extends with a number of additional properties and classes
suitable for expressing the quality of a dataset.</p>
<p>
The quality of a given dataset or distribution is assessed via a
number of observed properties. For instance, one may consider a
dataset to be of high quality because it complies to a specific
standard while for other use-cases the quality of the data will
depend on its level of interlinking with other datasets. To express
these properties an instance of a <a
href="http://www.w3.org/TR/vocab-dcat/#Class:_Dataset">dcat:Dataset</a>
or <a href="http://www.w3.org/TR/vocab-dcat/#Class:_Distribution">dcat:Distribution</a>
can be related to five different types of quality information represented by the following classes:
</p>
<ul>
<li><a href="#dqv:QualityAnnotation">dqv:QualityAnnotation</a>
represents feedback and quality certificates given about the
dataset or its distribution.</li>
<li><a href="http://purl.org/dc/terms/Standard">dcterms:Standard</a>
represents a standard the dataset or its distribution conforms to.</li>
<li><a href="#dqv:QualityPolicy">dqv:QualityPolicy</a>
represents a policy or agreement that is chiefly governed by data quality concerns.</li>
<li><a href="#dqv:QualityMeasurement">dqv:QualityMeasurement</a>
represents a metric value providing quantitative or qualitative
information about the dataset or distribution.</li>
<li><a href="http://www.w3.org/ns/prov#Entity">prov:Entity</a>
represents an entity involved in the provenance of the dataset or
distribution.</li>
</ul>
<p>
DQV defines quality measures as specific instances of Quality Measurements, adapting the daQ quality framework [[DaQ]], [[DaQ-RDFCUBE]]. It relies on quality dimensions and quality metrics. </p>
<ul>
<li>A Quality Dimension (<a href="#dqv:Dimension">dqv:Dimension</a>) is a quality-related characteristic of a dataset
relevant to the consumer (e.g., the availability of a dataset).</li>
<li>A Quality Metric (<a href="#dqv:Metric">dqv:Metric</a>) gives a procedure for measuring a data quality dimension, which is abstract, by observing a concrete quality indicator. There are usually multiple metrics per dimension; e.g., availability can be indicated by the accessibility of a SPARQL endpoint, or that of an RDF dump. The value of a metric can be numeric (e.g., for the metric “human-readable labeling of classes, properties and entities”, the percentage of entities having an rdfs:label or rdfs:comment) or boolean (e.g. whether or not a SPARQL endpoint is accessible).</li>
</ul>
<!--p>For example, a dimension could be "multilinguality" and two metrics could be "ratio of literals with language tags" and "number
of different language tags".</p-->
<p>Besides quality measurements, DQV considers certificates, standards, and quality policies, which can also be organized according to dimensions. Quality metadata containers (<a href="#dqv:QualityMetadata">dqv:QualityMetadata</a>) can group together different quality statements, so that their provenance can be tracked jointly.</p>
<figure>
<a href="images/DataQuality0.2.9.svg"> <img
src="images/DataQuality0.2.9.svg" />
</a>
<figcaption>Data model showing the main relevant classes
and their relations.</figcaption>
</figure>
<p>
<em>
N.B.: "containment" refers to the inclusion of quality statements into "containers", which may or may not be treated as (RDF) graphs (see later <a href="#DocumentProvenanceQualityMetadata">example</a> and the usage note for the class <a href="#dqv:QualityMetadata">dqv:QualityMetadata</a>).
</em>
</p>
<p>
Quality information can be derived from other quality information. For example, a quality annotation can be derived from a standard or a quality measurement. Quality measurements can be derived from other measurements. Metrics can be derived from other metrics. A standard can be built on another standard or a (set of) metrics. DQV models such derivations through the property <a href="https://www.w3.org/TR/prov-o/#wasDerivedFrom">prov:wasDerivedFrom</a> as illustrated in the diagram below.
</p>
<figure>
<a href="images/wasDerivedFrom2.svg"> <img
src="images/wasDerivedFrom2.svg" />
</a>
<figcaption>Using the property <a href="https://www.w3.org/TR/prov-o/#wasDerivedFrom">prov:wasDerivedFrom</a> to interrelate quality metrics and other quality statements.</figcaption>
</figure>
</section>
<section id="VocabularySpecification">
<h2>Vocabulary specification</h2>
<div class="note">
<p>This section is work in progress. We will include later more
tables with specification of individual classes and properties.</p>
</div>
<section id="dqv:QualityMeasurement">
<h3>Class: Quality Measurement</h3>
<!--p>DQV defines quality measures as specific instances of DQV
observations, adapting the daQ quality metrics framework [[DaQ]],
[[DaQ-RDFCUBE]]:</p>
<ul>
<li>A Quality Dimension is a characteristic of a dataset
relevant to the consumer (e.g., the availability of a dataset).</li>
<li>A Quality Metric gives a procedure for measuring a data
quality dimension, which is abstract, by observing a concrete
quality indicator. There are usually multiple metrics per
dimension; e.g., availability can be indicated by the accessibility
of a SPARQL endpoint, or of an RDF dump. The value of a metric can
be numeric (e.g., for the metric “human-readable labeling of
classes, properties and entities”, the percentage of entities
having an rdfs:label or rdfs:comment) or boolean (e.g. whether or
not a SPARQL endpoint is accessible).</li>
</ul>
<p>For example, a dimension could be "multilinguality" and two
metrics could be "ratio of literals with language tags" and "number
of different language tags".</p-->
<p>
The following properties should be used on this class: <a
href="#dqv:isMeasurementOf">dqv:isMeasurementOf</a>, <a href="#dqv:value">dqv:value</a>,
<a href="#qb:dataSet">qb:dataSet</a>.
</p>
<div class="issue">
<p>
Should (and if yes, how) DQV represent parameters for a metric
applied for computing a specific quality measurement (e.g.,a specific
setting of weights)? (<a
href="https://www.w3.org/2013/dwbp/track/issues/223">Issue-223</a>)
</p>
</div>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:QualityMeasurement">dqv:QualityMeasurement</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>A quality measurement represents the evaluation of a given
dataset (or dataset distribution) against a specific quality
metric.</td>
</tr>
<tr>
<td class="prop">Subclass of:</td>
<td><a href="http://purl.org/linked-data/cube#Observation">qb:Observation</a></td>
</tr>
<tr>
<td class="prop">Equivalent class</td>
<td><a href="http://purl.org/eis/vocab/daq#Observation">daq:Observation</a></td>
</tr>
<tr><td class="prop">Usage note:</td><td>The unit of measure in quality measurement should be specified through the property <a href="http://purl.org/linked-data/sdmx/2009/attribute#unitMeasure">sdmx-attribute:unitMeasure</a> as recommended by RDF Data Cube [[Vocab-Data-Cube]].
The <a href="http://www.wurvoc.org/vocabularies/om-1.8/">Ontology of units of Measure (OM)</a> [[RijgersbergEtAl]] provides a list of HTTP dereferenceable unit of measures which can be exploited as values for <a href="http://purl.org/linked-data/sdmx/2009/attribute#unitMeasure">sdmx-attribute:unitMeasure</a>.</td></tr>
</tbody>
</table>
<section id="dqv:isMeasurementOf">
<h4>Property: isMeasurementOf</h4>
<table class="definition">
<thead>
<tr>
<th>RDF Property:</th>
<th><a href="#dqv:isMeasurementOf">dqv:isMeasurementOf</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Indicates the metric being observed.</td>
</tr>
<tr>
<td class="prop">Instance of:</td>
<td><a
href="http://purl.org/linked-data/cube#DimensionProperty">qb:DimensionProperty</a>
</td>
</tr>
<tr>
<td class="prop">Domain:</td>
<td><a href="http://purl.org/linked-data/cube#Observation">qb:Observation</a></td>
</tr>
<tr>
<td class="prop">Range:</td>
<td><a href="#dqv:Metric">dqv:Metric</a></td>
</tr>
<!--tr><td class="prop">Minimum cardinality:</td><td>1</td></tr-->
<tr>
<td class="prop">Equivalent Property</td>
<td><a href="http://purl.org/eis/vocab/daq#metric">daq:metric</a></td>
</tr>
</tbody>
</table>
</section>
<section id="qb:dataSet">
<h4>Property: dataSet</h4>
<table class="definition">
<thead>
<tr>
<th>RDF Property:</th>
<th><a href="http://purl.org/linked-data/cube#dataSet">qb:dataSet</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Indicates the dataset to a quality measurement (which is an
RDF Data Cube observation) belongs.</td>
</tr>
<tr>
<td class="prop">Domain:</td>
<td><a href="http://purl.org/linked-data/cube#Observation">qb:Observation</a></td>
</tr>
<tr>
<td class="prop">Range:</td>
<td><a href="http://purl.org/linked-data/cube#Observation">qb:DataSet</a></td>
</tr>
</tbody>
</table>
</section>
<section id="dqv:computedOn">
<h4>Property: computedOn</h4>
<table class="definition">
<thead>
<tr>
<th>RDF Property:</th>
<th><a href="#dqv:computedOn">dqv:computedOn</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Refers to the resource (e.g., a dataset, a linkset, a
graph, a set of triples) on which the quality measurement is
performed. In the DQV context, this property is generally
expected to be used in statements in which objects are instances
of <a href="http://www.w3.org/TR/vocab-dcat/#class-dataset">dcat:Dataset</a>
and <a
href="http://www.w3.org/TR/vocab-dcat/#class-distribution">dcat:Distribution</a>.
</td>
</tr>
<tr>
<td class="prop">Instance of:</td>
<td><a
href="http://purl.org/linked-data/cube#DimensionProperty">qb:DimensionProperty</a>
</td>
</tr>
<tr>
<td class="prop">Domain:</td>
<td><a href="#dqv:QualityMeasurement">dqv:QualityMeasurement</a></td>
</tr>
<tr><td class="prop">Range:</td><td><a href="http://www.w3.org/2000/01/rdf-schema#Resource">rdfs:Resource</a></td></tr>
<tr>
<td class="prop">Equivalent property:</td>
<td><a href="http://purl.org/eis/vocab/daq#computedOn">daq:computedOn</a></td>
</tr>
<tr>
<td class="prop">Inverse property:</td>
<td><a href="#dqv:hasQualityMeasurement">dqv:hasQualityMeasurement</a></td>
</tr>
<!--tr><td class="prop">Minimum cardinality:</td><td>1</td></tr-->
<!--tr><td class="prop">Maximum cardinality:</td><td>1</td></tr-->
</tbody>
</table>
</section>
<section id="dqv:value">
<h4>Property: value</h4>
<table class="definition">
<thead>
<tr>
<th>RDF Property:</th>
<th><a href="#dqv:value">dqv:value</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Refers to values computed by metric.</td>
</tr>
<tr>
<td class="prop">Instance of:</td>
<td><a
href="http://purl.org/linked-data/cube#MeasureProperty">qb:MeasureProperty</a>,
<a href="http://www.w3.org/2002/07/owl#DatatypeProperty">owl:DatatypeProperty</a>
</td>
</tr>
<tr>
<td class="prop">Domain:</td>
<td><a href="#dqv:QualityMeasurement">dqv:QualityMeasurement</a></td>
</tr>
<!--tr><td class="prop">Range:</td><td><a href="ttp://www.w3.org/2000/01/rdf-schema#Resource">rdfs:Resource</a></td></tr-->
<tr>
<td class="prop">Equivalent property:</td>
<td><a href="http://purl.org/eis/vocab/daq#value">daq:value</a></td>
</tr>
<!--tr><td class="prop">Minimum cardinality:</td><td>1</td></tr>
<tr><td class="prop">Maximum cardinality:</td><td>1</td></tr-->
</tbody>
</table>
</section>
</section>
<section id="dqv:Metric">
<h3>Class: Metric</h3>
<p>
The following properties should be used on this class: <a
href="#dqv:inDimension">dqv:inDimension</a>.
</p>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:Metric">dqv:Metric</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>A standard to measure a quality dimension. An observation
(instance of dqv:QualityMeasurement) assigns a value in a given unit
to a Metric. <!--Specific metrics are defined as subclasses of this abstract class.-->
</td>
</tr>
<!--<tr><td class="prop">Usage note:</td><td>@@TODO@@</td></tr>-->
<tr>
<td class="prop">Equivalent class</td>
<td><a href="http://purl.org/eis/vocab/daq#Metric">daq:Metric</a></td>
</tr>
</tbody>
</table>
<section id="dqv:expectedDataType">
<h4>Property: expectedDataType</h4>
<table class="definition">
<thead>
<tr>
<th>RDF Property:</th>
<th><a href="#dqv:expectedDataType">dqv:expectedDataType</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents the expected data type for metric's observed value (e.g. xsd:boolean, xsd:double etc...) </td>
</tr>
<tr>
<td class="prop">Domain:</td>
<td><a href="#dqv:Metric">dqv:Metric</a></td>
</tr>
<tr>
<td class="prop">Range:</td>
<td> <a href="https://www.w3.org/TR/xmlschema11-1/#sec-anySimpleType">xsd:anySimpleType</a>
</td>
</tr>
<tr>
<td class="prop">Equivalent property</td>
<td><a href="http://purl.org/eis/vocab/daq#expectedDataType">daq:expectedDataType</a></td>
</tr>
</tbody>
</table>
</section>
</section>
<section id="dqv:Dimension">
<h3>Class: Dimension</h3>
<p>
The following properties should be used on this class: <a
href="#dqv:inCategory">dqv:inCategory</a>.
</p>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:Dimension">dqv:Dimension</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents criteria relevant for assessing quality. Each
quality dimension must have one or more metric to measure it. <!-- Dimensions are provided as subclasses of this abstract class, which is not intended for direct usage.-->
A dimension is linked with a category using the dqv:inDimension
property.
</td>
</tr>
<tr>
<td class="prop">Subclass of:</td>
<td><a href="https://www.w3.org/TR/skos-reference/#concepts">skos:Concept</a></td>
</tr>
<!--<tr><td class="prop">Usage note:</td><td>@@TODO@@</td></tr>-->
<tr>
<td class="prop">Equivalent class</td>
<td><a href="http://purl.org/eis/vocab/daq#Dimension">daq:Dimension</a></td>
</tr>
</tbody>
</table>
<section id="dqv:inCategory">
<h4>Property: inCategory</h4>
<table class="definition">
<thead>
<tr>
<th>RDF Property:</th>
<th><a href="#dqv:inCategory">dqv:inCategory</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents the category a dimension is grouped in.</td>
</tr>
<tr>
<td class="prop">Domain:</td>
<td><a href="#dqv:Dimension">dqv:Dimension</a></td>
</tr>
<tr>
<td class="prop">Range:</td>
<td><a href="#dqv:Category">dqv:Category</a></td>
</tr>
<tr>
<td class="prop">Inverse:</td>
<td><a href="http://purl.org/eis/vocab/daq#hasDimension">daq:hasDimension</a></td>
</tr>
<!--tr><td class="prop">Minimum cardinality:</td><td></td></tr>
<tr><td class="prop">Maximum cardinality:</td><td>1</td></tr-->
<tr>
<td class="prop">Usage note:</td>
<td>Categories are meant to systematically organize
dimensions. The Data Quality Vocabulary defines no specific
cardinality constraints for dqv:inCategory, since distinct
quality frameworks might have different perspectives over a
dimension. A dimension may therefore be associated to more than
one category. However, those who define new quality metrics
should try to avoid this as much as possible and assign only one
category to the dimensions they define.</td>
</tr>
</tbody>
</table>
</section>
</section>
<section id="dqv:Category">
<h3>Class: Category</h3>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:Category">dqv:Category</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents a group of quality dimensions in which a
common type of information is used as quality indicator. <!--Categories are provided as subclasses of this abstract class, which is not intended for direct usage.-->
</td>
</tr>
<!--<tr><td class="prop">Usage note:</td><td>@@TODO@@</td></tr>-->
<tr>
<td class="prop">Subclass of:</td>
<td><a href="https://www.w3.org/TR/skos-reference/#concepts">skos:Concept</a></td>
</tr>
<tr>
<td class="prop">Equivalent class</td>
<td><a href="http://purl.org/eis/vocab/daq#Category">daq:Category</a></td>
</tr>
</tbody>
</table>
</section>
<div class="note">
<p>
Dimension and category are abstract entities. We represent instances dqv:Dimension and dqv:Category as instances of <code>skos:Concept</code>, which we think enable similar features as these for dimensions and categories in daQ. Our representation choice differs more significantly for metrics, however. daQ uses RDFS/OWL classes and subclasses to represent constraints on measurements (e.g., on the type of values). RDFS/OWL however makes an 'open world' assumption that does not allow one to capture entirely all constraints. Additionally, languages are currently being defined to represent constraints in more appropriate ways (SHACL). We think it is therefore not appropriate now to recommend to treat specific metrics as subclasses of dqv:Metric, and we refer implementers to future progress on SHACL and related technology.
</p>
</div>
<section id="dqv:QualityMeasurementDataset">
<h3>Class: Quality Measurement Dataset</h3>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:QualityMeasurementDataset">dqv:QualityMeasurementDataset</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents a dataset of quality measurements, evaluations of
a given dataset (or dataset distribution) against a specific
quality metric.</td>
</tr>
<tr>
<td class="prop">Subclass of:</td>
<td><a
href="http://www.w3.org/TR/vocab-data-cube/#ref_qb_DataSet">qb:DataSet</a></td>
</tr>
<!--<tr><td class="prop">Usage note:</td><td>@@TODO@@</td></tr>-->
<tr>
<td class="prop">Equivalent class</td>
<td><a href="http://purl.org/eis/vocab/daq#QualityGraph">daq:QualityGraph</a></td>
</tr>
</tbody>
</table>
</section>
<section id="dqv:QualityPolicy">
<h3>Class: Quality Policy</h3>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:QualityPolicy">dqv:QualityPolicy</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents a policy or agreement that is chiefly governed by data quality concerns.</td>
</tr>
</tbody>
</table>
</section>
<section id="dqv:QualityAnnotation">
<h3>Class: Quality Annotation</h3>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:QualityAnnotation">dqv:QualityAnnotation</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents quality annotations, including rating, quality
certificate, feedback that can be associated to datasets or
distributions. Quality annotations must have one oa:motivatedBy
statement with an instance of oa:Motivation (and skos:Concept),
which reflects a quality assessment purpose. We define this
instance as dqv:qualityAssessment.</td>
</tr>
<tr>
<td class="prop">Subclass of:</td>
<td><a href="http://www.w3.org/ns/oa#d4e434">oa:Annotation</a></td>
</tr>
<!--<tr><td class="prop">Usage note:</td><td>@@TODO@@</td></tr>-->
<tr>
<td class="prop">Equivalent class</td>
<td><pre class="highlight">
EquivalentClasses(
dqv:QualityAnnotation
ObjectHasValue( oa:motivatedBy dqv:qualityAssessment )
)</pre></td>
</tr>
</tbody>
</table>
<div class="note">
<p>To make the document more self-contained we might consider to
describe some properties of oa:Annotation, such as hasBody,
hasTarget.</p>
</div>
</section>
<section id="dqv:QualityCertificate">
<h3>Class: Quality Certificate</h3>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:UserQualityFeedback">dqv:QualityCertificate</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>An annotation that associates a resource (especially, a dataset or a distribution) to another resource (for example, a document) that certifies the resource's quality according to a set of quality assessment rules.</td>
</tr>
<tr>
<td class="prop">Subclass of:</td>
<td><a href="#dqv:QualityAnnotation">dqv:QualityAnnotation</a> </td>
</tr>
</tbody>
</table>
</section>
<section id="dqv:UserQualityFeedback">
<h3>Class: User Quality Feedback</h3>
<table class="definition">
<thead>
<tr>
<th>RDF Class:</th>
<th><a href="#dqv:UserQualityFeedback">dqv:UserQualityFeedback</a></th>
</tr>
</thead>
<tbody>
<tr>
<td class="prop">Definition:</td>
<td>Represents feedback users might want to associate to datasets or distributions. Besides <a href="#dqv:qualityAssessment">dqv:qualityAssessment</a> which is the motivation required by all quality annotations, one of the <a href="https://www.w3.org/TR/2016/WD-annotation-model-20160331/#motivation-and-purpose">predefined instances of oa:Motivation</a> should be indicated as motivation to distinguish among the different kinds of feedback, e.g, classifications, questions.</td>
</tr>
<tr>
<td class="prop">Subclass of:</td>
<td><a href="#dqv:QualityAnnotation">dqv:QualityAnnotation</a>
<a href="">duv:UserFeedback</a></td>
</tr>
</tbody>
</table>
</section>
<section id="dqv:QualityMetadata">
<h3>Class: Quality Metadata</h3>
<table class="definition">
<thead>
<tr>