Quality Indicators Dictionary and Markup Language
The scenario of rapidly growing geodata catalogues requires tools focused on facilitate users the choice of products. Having quality fields populated in metadata allow the users to rank and then select the best fit-for-purpose products. In this direction, QualityML is a dictionary that contains hierarchically structured concepts to precisely define and relate quality levels: from quality classes to quality measurements. This levels are used to encode quality semantics for geospatial data by mapping them to the corresponding metadata schemas. The benefits of having encoded quality semantics, in the case of data producers, are related with improvements in their product discovery and better transmission of their characteristics. In the case of data users, they would better compare quality and uncertainty measures to take the best selection of data as well as to perform dataset intercomparison. Also it allows other components (such as visualization, discovery, or comparison tools) to be quality-aware and interoperable.
On one hand, the QualityML is a profile of the ISO geospatial metadata standards (e.g. ISO 19157) providing a set of rules for precisely documenting quality measure parameters that is structured in 5 levels. On the other hand, QualityML includes semantics and vocabularies for the quality concepts. Whenever possible, it uses statistic expressions from the UncertML dictionary (http://www.uncertml.org) encoding. However it also extends UncertML to provide a list of alternative metrics that are commonly used to quantify quality beyond the uncertainty concept. Unfortunatelly the website of UncertML was shotdown in 2016. It still can be queried from the Web Archive project. Given the situation, in 2018 QualityML decided to duplicated all UncertML records that were used at that time.
Finally, keep in mind that QualityML is not just suitable for encoding geospatial dataset level quality but also considers pixel and object level uncertainties. This is done by linking the metadata quality descriptions with layers representing not just the data but the uncertainty values associated with each geospatial element.
This page is structured in the following sections:
- Generic quality element
- Quality classes
- Quality indicators
- Quality measures by quality class (linked to classes, indicators, domains and matrices)
- Quality domains
- Quality metrics
- Quality metrics sets
- Reserved words
- XML encoding
Both metrics and domain have a URI.
All relative URIs in this page refer to http://www.qualityml.org/1.0/
Generic quality element
A Quality element is a combination of a quality class, a quality indicator, a quality domain, a quality metric (which include a metrics name, metrics description, metrics parameters, its values and units of measure). The combination of a quality domain and a quality metrics are commonly known as quality measures. We suggest 2 ways to map the QualityML concepts to ISO 19139 and ISO 19115-3. The first way makes a simple use of the ISO values keeping the structure of Record as simple as possible. The second one extends Record to allow a more structured encoding:
Without extending Record (RECOMMENDED as implemetation does not support extending the XML encoding)
| Concept | ISO 19139 mapping | ISO 19115-3 mapping | Example |
| Quality class and quality indicator |
Name of the DQ_Element | Name of the DQ_Element | ISO 19139: gmd:DQ_CompletenessComission ISO 19115-3: mdq:DQ_CompletenessOmission |
| Quality measure name, Quality domain name | gmd:nameOfMeasure | mdq:nameOfMeasure | Excess,NonConformance |
| Quality measure identification, domain identification | gmd:measureIdentification/gmd:MD_Identifier/gmd:code | mdq:measureIdentification/mcc:MD_Identifier/mcc:code mdq:measureIdentification/mcc:MD_Identifier/mcc:version |
http://qualityml.geoviqua.org/1.0/measure/Excess?domain=NonConformance |
| Quality measure and domain description (domain value list if necessary) | gmd:measureDescription | mdq:measureDescription | Indication of elements within the dataset or sample that should not have been present, the conformance or non-conformance can be expressed as a boolean, count or rate. Non conformance field of measurement |
| Metrics identifier | gmd:result/gmd:DQ_QuantitativeResult/gmd:errorStatistic | mdq:result/mdq:DQ_QuantitativeResult/mdq:errorStatistic | http://www.qualityml.org/metrics/items |
| Metrics parameters | gmd:result/gmd:DQ_QuantitativeResult/gmd:ValueType | mdq:result/mdq:DQ_QuantitativeResult/mdq:ValueType | rate (max=100) |
| Metrics values | gmd:value/gco:Record | mdq:value/gco:Record | 3 |
| Units of measure | gmd:valueUnit@xlink:href | mdq:valueUnit@xlink:href | urn:ogc:def:uom:OGC:1.0:percent |
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| Concept | ISO 19139 mapping | ISO 19115-3 mapping | Example |
| Quality class and quality indicator |
Name of the DQ_Element | Name of the DQ_Element | ISO 19139: gmd:DQ_CompletenessComission ISO 19115-3: mdq:DQ_CompletenessOmission |
| Quality measure name | gmd:nameOfMeasure | mdq:nameOfMeasure | Excess |
| Quality measure identification |
gmd:measureIdentification/gmd:MD_Identifier/ gmd:code/gmx:Anchor@xlink:href |
mdq:measureIdentification/mcc:MD_Identifier/mcc:code/gcx:Anchor@xlink:href mdq:measureIdentification/mcc:MD_Identifier/mcc:codeSpace/gcx:Anchor@xlink:href mdq:measureIdentification/mcc:MD_Identifier/mcc:version |
http://qualityml.geoviqua.org/1.0/measure/Excess http://www.qualityml.org (Only in ISO 19115-3) 1.0 (Only in ISO 19115-3) |
| Quality measure description | gmd:measureDescription | mdq:measureDescription | Indication of elements within the dataset or sample that should not have been present. The conformance or non-conformance can be expressed as a boolean, count or rate. |
| Quality domain | gmd:value/gco:Record/* | mdq:value/gco:Record/* | qmld:NonConformance |
| Quality domain parameters |
gmd:value/gco:Record/qmld:NonConformance/* qmld:range/qmld:min and/or qmld:range/qmld:max and/or qmld:rule |
mdq:value/gco:Record/qmld:NonConformance/* qmld:range/qmld:min and/or qmld:range/qmld:max and/or qmld:rule |
qmld:rule: Indication of excess items Usually parameters for the domain are not needed |
| Metrics description | gmd:valueType/gco:RecordType | mdq:valueRecordType/gco:RecordType | Excess items |
| Metrics identifier | gmd:valueType/gco:RecordType@xlink:href | mdq:valueRecordType/gco:RecordType@xlink:href | http://www.qualityml.org/metrics/items |
| Metrics parameters | gmd:value/gco:Record/qml:Items/* | mdq:value/gco:Record/qml:Items/* | qml:rate and qml:max "qml:indicator" or "qml:count" are also options |
| Metrics values | gmd:value/gco:Record/qml:Items/qml:rate gmd:value/gco:Record/qml:Items/qml:rate@max |
mdq:value/gco:Record/qml:Items/qml:rate mdq:value/gco:Record/qml:Items/qml:rate@max |
66 100 |
| Units of measure | gmd:valueUnit@xlink:href | mdq:valueUnit@xlink:href | urn:ogc:def:uom:OGC:1.0:percent |
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Quality classes
The ISO 19157:2013 Geographic information - Data quality defines 7 data quality elements (or classes) describing a certain aspect of the quality of geographic data in which quality elements can be classified. In 2022, we added a new class called "certainly" that is applicable to decision ready information. This class provide simple indicators for decision makers in an standardized language and it is inspired by the IPCC
Quality indicators
The ISO 19157:2013 Geographic information - Data quality defines 18 quality indicators (or sub-classes) in which quality elements can be classified.
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Data quality elements recommended by INSPIRE spatial data theme Hydrography
| Quality class | Quality indicator | Description |
| Completeness | Completeness commission | Excess data present in the dataset, as described by the scope |
| Completeness | Completeness omission | Data absent from the dataset, as described by the scope |
| Logical consistency | Conceptual consistency | Adherence to rules of the conceptual schema |
| Logical consistency | Domain consistency | Adherence of values to the value domains |
| Logical consistency | Topological consistency | Correctness of the explicitly encoded topological characteristics of the dataset as described by the scope |
| Positional accuracy | Absolute external positional accuracy | Closeness of reported coordinate values to values accepted as or being true |
| Positional accuracy | Relative internal positional accuracy | Closeness of the relative positions of features in the scope to their respective relative positions accepted as or being true |
| Thematic accuracy | Non quantitative attribute accuracy | Accuracy of non-quantitative attributes |
| Thematic accuracy | Quantitative attribute accuracy | Accuracy of quantitative attributes |
INSPIRE recommendation
Where it is impossible to express the evaluation of a data quality element in a quantitative way, the evaluation of the element should be expressed with a textual statement as a data quality descriptive result.Quality measures matrices
We provide a matrix of the combinations of indicators, measures and metrics commonly used for each quality class. Both ISO 19157 and ISO 19138 have a list of metrics in the Annex D and share the same identifier (last field in the tables). Actually ISO 19157 supersedes ISO 19138 and contains all metrics in ISO 19138 but adds the new Id. 119 (Physical structure conflicts), Id. 128 (Bias of positions), Id. 159 (Chronological error) and Ids. 101 to 104 (Aggregation Measures).Quality domain
This section contains the definition of the domain where quality metrics are applied (including link to the schema).
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Quality Metrics
Whenever possible, UncertML statistics are used. When needed new metrics are defined here based on uncertml basic types. In some sense QualityML extends UncertML.
XML schemas and examples are available here (for convinience a exact copy of uncertml is included).
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Quality metrics sets
This table provides a way to aggregate some quality metrics in a single element that can group them. This is particularly useful when using several related metrics in the ISO 19139 encoding.
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Other reserved words
This table provides a list of keywords that are useful for the WMS-Q specification.URI |
Name | Meaning |
Values |
Parameter or component that more closely represent the actual values measured | |
Quality collection |
Variable that is decomposed in components or parameters | |
Quality composition |
Component that represents a composition of other components for visualization purposes |
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XML encoding
Here, some examples on how to encode quality metadata in ISO 19139 metadata documents using the qualityML framework and the qualityML URIsExample using QualityML in an ISO metadata, without extending Record (so, without the need for the qml or uml namespace) for dataset level quality (Recommended: e.g. a GeoNetwork record using ISO 19115:2003 template)
Example using QualityML in an ISO metadata, without extending Record (so, without the need for the qml or uml namespace) for dataset level quality (Recommended: e.g. a GeoNetwork record using ISO 19115:2003 template) with conventional units of measure
- List of UoM (voabulary) Unified Code for Units of Measure (UCUM), also in https://github.com/ucum-org/ucum
- How to encode UoM namespace: https://confluence.csiro.au/display/seegrid/OGC+URN+Scheme
- Base units are the fundamental units defined in the uniternational system
- Conventional units are units derived from other units by conversion factors (eg: a minute is derive from 60 seconds)
- Derived units are units derived from combination of basic units (e.g. an acceletation is derived from m and s squared: m/s2)
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Example using UncertML in an ISO metadata extending "Record" (extending XML is not commonly supported by implementations)
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Example using QualityML in an ISO metadata extending "record" for dataset level quality (extending XML is not commonly supported by implementations)
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Example using QualityML in an ISO metadata extending "Record" at pixel level quality (extending XML is not commonly supported by implementations)
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The research leading to these results has been carried out in the GeoViQua project that has received funding from the European Union Seventh Framework Programme (FP7/2010-2013) under grant agreement no. 265178