Difference between revisions of "ISO 19157:2013 Geographic information - Data quality"

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==Overview==
 
==Overview==
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{| class="wikitable sortable"
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{| class="wikitable"
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| Full name
 
| Full name
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|ISO 19157:2013, Geographic information – Data quality.
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| [http://www.iso.org/iso/home/store/catalogue_tc/catalogue_detail.htm?csnumber=32575 ISO 19157:2013, Geographic information - Data quality]
 
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| Version
 
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| Languages
 
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| English, French
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| English
 
|-
 
|-
 
| Online overview
 
| Online overview
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| https://www.iso.org/obp/ui/#iso:std:iso:19157:ed-1:v1:en  
+
| [https://www.iso.org/obp/ui/#iso:std:iso:19157:ed-1:v1:en https://www.iso.org/obp/ui/#iso:std:iso:19157:ed-1:v1:en]
 +
|-
 +
| Derived ontologies
 +
| https://github.com/ISO-TC211/GOM/tree/master/isotc211_GOM_harmonizedOntology/19157/2013
 
|-
 
|-
 
| Type of standard
 
| Type of standard
−
| ISO International Standard
+
| ISO International Standard<br/>Meta level
−
Meta level.
 
−
|-
 
−
| Related standard(s)
 
−
| ISO 19115-1:2013, Geographic information – Metadata – Part 1: Fundamentals
 
−
ISO 19115-2:2009, Geographic information – Metadata – Part 2: Extensions for imagery and gridded data
 
−
ISO 19158:2012, Geographic information – Quality assurance of data supply
 
 
|-
 
|-
 
| Application
 
| Application
 
| The standard specifies the description, evaluation and reporting of the quality of geographic data.  
 
| The standard specifies the description, evaluation and reporting of the quality of geographic data.  
 
|-
 
|-
−
| Conformance
+
| Conformance classes
−
classes
+
| Data quality evaluation process<br/>Data quality metadata<br/>Standalone quality report<br/>Data quality measure
−
|Data quality evaluation process
 
−
Data quality metadata
 
−
Standalone quality report
 
−
Data quality measure
 
 
|}
 
|}
  
−
==Scope==
+
== Scope ==
 +
ISO 19157:2013 establishes the principles for describing the quality of geographic data. It defines components for describing data quality; specifies components and content structure of a register for data quality measures; describes general procedures for evaluating the quality of geographic data; and establishes principles for reporting data quality.
  
−
ISO 19131:2007 describes requirements for the specification of geographic data products, based upon the concepts of other ISO 19100 International Standards. It also provides help in the creation of data product specifications, so that they are easily understood and fit for their intended purpose.
+
The standard also defines a set of data quality measures for use in evaluating and reporting data quality. It is applicable to data producers providing quality information to describe and assess how well a dataset conforms to its product specification and to data users attempting to determine whether or not specific geographic data are of sufficient quality for their particular application.
 +
 
 +
The standard does not attempt to define minimum acceptable levels of quality for geographic data.
  
 
==Implementation benefits==
 
==Implementation benefits==
 +
ISO 19157:2013 provides a standard way for describing the quality of geographic data. Such descriptions are useful when a producer has to evaluate how well a dataset meets the criteria described in its product specification. For example, if the producer outsourced the acquisition of the data, ISO 19157:2013 could be used to evaluate and describe the quality of the received data during acceptance testing.
  
−
ISO 19131:2007 describes in a structured way what the user wants, that is, the specification of the product required. While aimed primarily at specifying required datasets, the standard can also be used to specify services and other geospatial products. The standard is essentially the inverse of ISO 19115:2003 and uses the concepts and metadata elements and entities in ISO 19115:2003. Hence, it means that one can compare a product specification directly and in detail with the metadata of candidate offerings.
+
Geographic data are increasingly shared and exchanged. As a result, geographic data are often used for purposes that differ from the purpose for which it was originally captured. Complete descriptions of the quality of a dataset encourage and facilitate the sharing, interchange and use of appropriate datasets.
  
−
As the specification and metadata are both structured and contain many encoded elements, much of the matching can be done automatically, to filter out candidates that do not meet the specification. Candidate products can be obtained from within a user’s domain, but also from elsewhere. Hence, even an expert user might not be aware of possible sources for suitable products. This powerful capability enables of the ISO 19115:2003 and ISO 19131:2007 combination to filter out suitable candidates automatically.
+
Another benefit of implementing ISO 19157:2013 is that the quality information could assist a user who has to decide whether a specific dataset is appropriate for an intended use or application. If the user has to decide between two or more datasets, standardized quality descriptions simplify comparing the datasets. If ISO 19157:2013 is implemented, quality reports are expressed in a comparable way and there is a common understanding of the quality measures that have been used. A project to develop an XML of ISO 19157:2013 has begun.
 +
 
 +
==Implementation guidelines ==
 +
ISO 19157:2013 cancels and replaces [https://www.iso.org/standard/32556.html ISO/TS 19138:2006], [https://www.iso.org/standard/26019.html ISO 19114:2003] and [https://www.iso.org/standard/26018.html ISO 19113:2002]. According to ISO 19157:2013, data quality comprises six elements: completeness, thematic accuracy, logical consistency, temporal quality, positional accuracy and usability. Each element is comprised of a number of sub-elements, for example, completeness (commission and omission), logical consistency (conceptual, domain, format, topological), etc. These elements are used to describe data quality, i.e. how well a specific dataset meets the criteria for the different elements set forth in its product specification or user requirements. Evaluation against the criteria is done either quantitatively or subjectively (non-quantitatively). The latter case applies if a detailed data product specification does not exist or if the data product specification lacks quantitative measures and descriptors. Three metaquality elements – confidence, ‘representativity’ and homogeneity – provide quantitative and qualitative statements about the evaluation against the criteria and its result.
 +
 
 +
Quality information can be provided for different units of data, e.g. a dataset series, a dataset or a subset of a dataset with common characteristics. A data quality unit comprises of a scope and data quality elements. The scope specifies the extent, spatial and/or temporal and/or common characteristic(s) of the unit for which the quality information is provided.
 +
 
 +
In ISO 19157:2013, quality related information provided by purpose, usage and lineage of geographic data conforms to [[ISO 19115-1:2014 Geographic information - Metadata - Part 1: Fundamentals]].
 +
 
 +
ISO 19157:2013 specifies four conformance classes, i.e. the standard can be implemented for four different quality aspects of geographic datasets, each briefly described below.
 +
 
 +
 
 +
1. Implementing a data quality evaluation process conforming to ISO 19157:2013
 +
 
 +
A data quality evaluation process conforming to ISO 19157:2013 comprises of four steps:
 +
 
 +
* Step 1 - Specify the data quality units to be evaluated. Study the data product specification to identify applicable data quality units and their scope. For each data quality unit, identify the applicable data quality element(s). See example in Example: Data quality units.
 +
* Step 2 - Specify the data quality measures to be used to describe quality of each data quality element of a data quality unit. The requirements in the data product specification provide guidance on applicable data quality measures. See example in Example: Data quality measures. The data quality measures in the table are from the list of standardized data quality measures in ISO 19157:2013. It is also possible to describe user-defined quality measures, see further below, and to maintain a collection of such measures in a catalogue or register.
 +
* Step 3 - Specify the data quality evaluation procedures, i.e. the evaluation method(s) to be applied. The method can be direct (based on inspection of the items in the dataset) or indirect (based on external knowledge, such as lineage metadata). Direct evaluation is further classified by the source against which the evaluation is done: internal if only the data in the dataset is evaluated or external if there is reference to external data (e.g. satellite imagery or ground truth). ISO 19157:2013 includes guidance on how to sample data for evaluation.
 +
* Step 4 - Determine the output of the data quality evaluation, i.e. perform the data quality evaluation described in Steps 1-3 above. Additional results may be produced by aggregating or by deriving from existing results without carrying out a new evaluation. How to report the results of the data quality evaluation is described elsewhere in this chapter.
 +
 
 +
{| class="wikitable"
 +
|+Example: Data quality units
 +
| '''Data quality unit'''
 +
| '''Scope'''
 +
| '''Data quality elements'''
 +
|-
 +
| Topographic dataset
 +
| All features in the dataset
 +
| Completeness (commission and omission), thematic accuracy (correct classification)
 +
|-
 +
| Street network
 +
| Street features in the entire dataset
 +
| Logical inconsistency (topological inconsistency)
 +
|}
 +
 
 +
 
 +
{| class="wikitable"
 +
|+Example: Data quality measures
 +
| '''Data quality unit'''
 +
| '''Data quality element'''
 +
| '''Data quality measure'''
 +
| '''Method'''
 +
|-
 +
| Topographic dataset
 +
| Completeness (commission)
 +
| Measure 1: Excess item<br/>
 +
Measure 2: Number of excess items<br/>
 +
Measure 3: Number of duplicate feature instances
 +
| Direct external<br/>
 +
Direct external<br/>
 +
Direct internal
 +
|-
 +
| Topographic dataset
 +
| Completeness (omission)
 +
| Measure 1: Missing item
 +
Measure 2: Number of missing items
 +
| Direct external
 +
Direct external
 +
|-
 +
| Topographic dataset
 +
| Thematic accuracy (correct classification)
 +
| Measure 1: Number of incorrectly classified features<br/>
 +
Measure 2: Misclassification rate
 +
| Direct external<br/>
 +
Direct external
 +
|-
 +
| Street network
 +
| Logical inconsistency (topological inconsistency)
 +
| Measure 1: Number of missing connections due to undershoots<br/>
 +
Measure 2: Number of missing connections due to overshoots<br/>
 +
Measure 3: Number of invalid self-intersect errors<br/>
 +
Measure 4: Number of invalid self-overlap errors
 +
| Direct internal<br/>
 +
Direct internal<br/>
 +
Direct internal<br/>
 +
Direct internal
 +
|}
 +
 
 +
 
 +
''2. Implementing data quality metadata conforming to ISO 19157:2013''
 +
 
 +
Data quality metadata describes the quality of geographic data. ISO 19157:2013 specifies a conceptual model of the different components to be used when describing the quality of geographic data. Overview of the components to be used to describe data quality provides and overview of the components and their relationships to each other. A data dictionary, including definitions for all the components, is provided in the standard. Data quality metadata conforming to ISO 19157:2013 conforms to this conceptual model and is reported in conformance with [[ISO 19115:2003 Geographic information - Metadata]] and [[ISO 19115-2:2009 Geographic information - Metadata - Part 2: Extensions for imagery and gridded data]]
 +
 
 +
 
 +
[[File:MAfA_SectionC_Integrated_V10_html_10_1.png|center|thumb|Overview of the components to be used to describe data quality (Source: ISO 19157:2013)]]
 +
 
 +
 
 +
 
 +
''3. Implementing data quality reports conforming to ISO 19157:2013''
 +
 
 +
The first (and obvious) requirement is that the quality report comprises quality metadata conforming to ISO 19157:2013 (see 2. above), i.e. it includes sections on all appropriate aspects of quality and the description of components follow the rules defined in the standard. Additional information can be added to the report, but the structure of the report is not prescribed. Example: Section of a data quality report is an example of a section of a data quality report for the quality evaluation process described above.  
 +
 
 +
 
 +
{| class="wikitable"
 +
|+Example: Section of a data quality report
 +
| '''Data quality unit'''
 +
| '''Data quality element'''
 +
| '''Data quality measure'''
 +
| '''Result'''
 +
 
 +
|-
 +
| Topographic dataset
 +
| Completeness (commission)
 +
| Measure 2: Number of excess items<br/>
 +
Measure 3: Number of duplicate feature instances
 +
| 153<br/>
 +
1,036
 +
|-
 +
| Topographic dataset
 +
| Completeness (omission)
 +
| Measure 2: Number of missing items
 +
| 697
 +
|-
 +
| Topographic dataset
 +
| Thematic accuracy (correct classification)
 +
| Measure 1: Number of incorrectly classified features<br/>
 +
Measure 2: Misclassification rate
 +
| 8,774 <br/>
 +
10%
 +
|-
 +
| Street network
 +
| Logical inconsistency (topological inconsistency)
 +
| Measure 1: Number of missing connections due to undershoots<br/>
 +
Measure 2: Number of missing connections due to overshoots<br/>
 +
Measure 3: Number of invalid self-intersect errors<br/>
 +
Measure 4: Number of invalid self-overlap errors
 +
| 139<br/>
 +
57<br/>
 +
11<br/>
 +
6
 +
|}
  
−
An ISO 19131:2007 product specification can also be used to guide the development of a new product that meets the specification, and for others needing a similar product to see if the proposed product will also meet their needs. In South Africa, for example, the Committee for Spatial Information (CSI) is using ISO 19131:2007 for developing the form to be used by data custodians for informing the CSI of their planned data capture programmes, such as for aerial photography.
 
  
−
==Implementation guidelines==
+
''4. Implementing data quality measures conforming to ISO 19157:2013''
−
While ISO 19131:2007 does include annexes with UML class diagrams and data dictionaries as tables (as is done in ISO 19115:2003), it is probably still necessary for the user to consult ISO 19115:2003 when using ISO 19131:2007, as ISO 19115:2003 has more details about the metadata (and hence, product specification) concepts, elements and entities.
 
−
ISO 19131:2007 specifies that a data product specification shall describe the following aspects of the product:
 
  
−
# Overview: source and provenance of the specification, relevant terminology and an informal description of the required product, such as the dataset content, spatial and temporal extents, purpose, sources, production processes and maintenance.
+
A data quality measure conforming to ISO 19157:2013 is structurally and semantically well defined and described and modelled as specified in the standard. Such a measure is described by at least an identifier, a name, an element name, definition and a value type. Optional descriptors are an alias, description, a value structure, example, a basic measure and one or more source references and/or parameters. Note that full inspection is most appropriate for small populations or for tests that can be accomplished by automated means. For larger populations, checking a representative part of the data and reporting the quality result as a percentage rate is more appropriate and practical.
−
# Specification scopes: the scope of the required product, in terms of spatial and temporal extent, feature types, property types, property values, spatial representation, product hierarchy and partitioning (e.g. between the dynamic and static sorts of data in the required product), The concept ‘product hierarchy’ is not defined in the standard, but this applies to each of the partitions of the product being specified, as they can be at different levels: attribute, attribute type, feature, feature type, tile, dataset, series, etc. For each partition, the level code, level name, level description, extent and coverage are to be specified.
 
−
# Data product identification: title, abstract, topic category (one of the pre-defined themes that applies to the required product, such as farming, boundaries, elevation or transportation) and geographic description (actually, spatial extent) shall be provided and alternate title, purpose, spatial representation type (e.g. vector or raster), spatial resolution and supplemental information may be provided.
 
−
# Data content and structure: feature-based, coverage-based or imagery data. The content of a feature-based product shall be described in terms of an application schema (content, structure and constraints applicable) and a feature catalogue (or classification system). The application schema can be very complicated, catering for relationships between feature, property and attribute types, such as feature operations, feature association, inheritance relations and constraints. Imagery data are a form of coverage and a coverage is a sub-type of a feature, which behaves like a function returning one or more feature attribute values for some point within a spatiotemporal domain. A coverage requires an identifier, a description, the type and additional information.
 
−
# Reference systems: the spatial reference system (using coordinates or geographic identifiers) and the temporal reference system.
 
−
# Data quality: the data quality requirements, acceptable conformance quality levels and corresponding data quality measures. In ISO 19131:2007, the data quality requirements are specified in terms of ISO 19113 and ISO/TS 19138, but these have now been revised by ISO 19157:2013 (described in 10.7.3).
 
−
# Data capture: an optional specification of the sources and processes that shall or may be used for the data capture.
 
−
# Data maintenance: an optional specification of the principles and criteria to be applied in maintaining the product, such as maintenance and update frequency.
 
−
# Portrayal: an optional specification of the portrayal rules and a set of portrayal specifications, for specifying how the data may be represented graphically. This could be particularly important for a web service, for example.
 
−
# Data product delivery: delivery format (e.g. transfer standard) and delivery medium (e.g. CD-ROM). The delivery format details may include the name and version of the format; subset, profile or product specification; structure of the delivery file; language(s) and character encoding. The delivery medium details may include units of delivery (how the data are arranged on the medium), estimated sizes, name of the delivery medium and other delivery information.
 
−
# Additional information: a catchall for anything else to be specified for the product, such as constraint information regarding access and use.
 
−
# Metadata: the metadata that shall be provided with the product, defined in terms of ISO 19115:2003.
 
  
−
With the publication of ISO 19117:2012, Geographic information – Portrayal, ISO 19157:2013, Geographic information – Data quality, and ISO 19115-1:2014, Geographic information – Metadata – Part 1: Fundamentals, ISO 19131:2007 is due to be revised.
+
==See also==
 +
* [[ISO 19115-1:2014 Geographic information - Metadata - Part 1: Fundamentals]]
 +
* [[ISO 19115-2:2009 Geographic information - Metadata - Part 2: Extensions for imagery and gridded data]]
 +
* [[ISO 19158:2012 Geographic information - Quality assurance of data supply]]

Latest revision as of 11:26, 2 July 2017

Overview

Full name ISO 19157:2013, Geographic information - Data quality
Version Edition 1
Amendments None
Corrigenda None
Published by ISO/TC 211
Languages English
Online overview https://www.iso.org/obp/ui/#iso:std:iso:19157:ed-1:v1:en
Derived ontologies https://github.com/ISO-TC211/GOM/tree/master/isotc211_GOM_harmonizedOntology/19157/2013
Type of standard ISO International Standard
Meta level
Application The standard specifies the description, evaluation and reporting of the quality of geographic data.
Conformance classes Data quality evaluation process
Data quality metadata
Standalone quality report
Data quality measure

Scope

ISO 19157:2013 establishes the principles for describing the quality of geographic data. It defines components for describing data quality; specifies components and content structure of a register for data quality measures; describes general procedures for evaluating the quality of geographic data; and establishes principles for reporting data quality.

The standard also defines a set of data quality measures for use in evaluating and reporting data quality. It is applicable to data producers providing quality information to describe and assess how well a dataset conforms to its product specification and to data users attempting to determine whether or not specific geographic data are of sufficient quality for their particular application.

The standard does not attempt to define minimum acceptable levels of quality for geographic data.

Implementation benefits

ISO 19157:2013 provides a standard way for describing the quality of geographic data. Such descriptions are useful when a producer has to evaluate how well a dataset meets the criteria described in its product specification. For example, if the producer outsourced the acquisition of the data, ISO 19157:2013 could be used to evaluate and describe the quality of the received data during acceptance testing.

Geographic data are increasingly shared and exchanged. As a result, geographic data are often used for purposes that differ from the purpose for which it was originally captured. Complete descriptions of the quality of a dataset encourage and facilitate the sharing, interchange and use of appropriate datasets.

Another benefit of implementing ISO 19157:2013 is that the quality information could assist a user who has to decide whether a specific dataset is appropriate for an intended use or application. If the user has to decide between two or more datasets, standardized quality descriptions simplify comparing the datasets. If ISO 19157:2013 is implemented, quality reports are expressed in a comparable way and there is a common understanding of the quality measures that have been used. A project to develop an XML of ISO 19157:2013 has begun.

Implementation guidelines

ISO 19157:2013 cancels and replaces ISO/TS 19138:2006, ISO 19114:2003 and ISO 19113:2002. According to ISO 19157:2013, data quality comprises six elements: completeness, thematic accuracy, logical consistency, temporal quality, positional accuracy and usability. Each element is comprised of a number of sub-elements, for example, completeness (commission and omission), logical consistency (conceptual, domain, format, topological), etc. These elements are used to describe data quality, i.e. how well a specific dataset meets the criteria for the different elements set forth in its product specification or user requirements. Evaluation against the criteria is done either quantitatively or subjectively (non-quantitatively). The latter case applies if a detailed data product specification does not exist or if the data product specification lacks quantitative measures and descriptors. Three metaquality elements – confidence, ‘representativity’ and homogeneity – provide quantitative and qualitative statements about the evaluation against the criteria and its result.

Quality information can be provided for different units of data, e.g. a dataset series, a dataset or a subset of a dataset with common characteristics. A data quality unit comprises of a scope and data quality elements. The scope specifies the extent, spatial and/or temporal and/or common characteristic(s) of the unit for which the quality information is provided.

In ISO 19157:2013, quality related information provided by purpose, usage and lineage of geographic data conforms to ISO 19115-1:2014 Geographic information - Metadata - Part 1: Fundamentals.

ISO 19157:2013 specifies four conformance classes, i.e. the standard can be implemented for four different quality aspects of geographic datasets, each briefly described below.


1. Implementing a data quality evaluation process conforming to ISO 19157:2013

A data quality evaluation process conforming to ISO 19157:2013 comprises of four steps:

  • Step 1 - Specify the data quality units to be evaluated. Study the data product specification to identify applicable data quality units and their scope. For each data quality unit, identify the applicable data quality element(s). See example in Example: Data quality units.
  • Step 2 - Specify the data quality measures to be used to describe quality of each data quality element of a data quality unit. The requirements in the data product specification provide guidance on applicable data quality measures. See example in Example: Data quality measures. The data quality measures in the table are from the list of standardized data quality measures in ISO 19157:2013. It is also possible to describe user-defined quality measures, see further below, and to maintain a collection of such measures in a catalogue or register.
  • Step 3 - Specify the data quality evaluation procedures, i.e. the evaluation method(s) to be applied. The method can be direct (based on inspection of the items in the dataset) or indirect (based on external knowledge, such as lineage metadata). Direct evaluation is further classified by the source against which the evaluation is done: internal if only the data in the dataset is evaluated or external if there is reference to external data (e.g. satellite imagery or ground truth). ISO 19157:2013 includes guidance on how to sample data for evaluation.
  • Step 4 - Determine the output of the data quality evaluation, i.e. perform the data quality evaluation described in Steps 1-3 above. Additional results may be produced by aggregating or by deriving from existing results without carrying out a new evaluation. How to report the results of the data quality evaluation is described elsewhere in this chapter.
Example: Data quality units
Data quality unit Scope Data quality elements
Topographic dataset All features in the dataset Completeness (commission and omission), thematic accuracy (correct classification)
Street network Street features in the entire dataset Logical inconsistency (topological inconsistency)


Example: Data quality measures
Data quality unit Data quality element Data quality measure Method
Topographic dataset Completeness (commission) Measure 1: Excess item

Measure 2: Number of excess items
Measure 3: Number of duplicate feature instances

Direct external

Direct external
Direct internal

Topographic dataset Completeness (omission) Measure 1: Missing item

Measure 2: Number of missing items

Direct external

Direct external

Topographic dataset Thematic accuracy (correct classification) Measure 1: Number of incorrectly classified features

Measure 2: Misclassification rate

Direct external

Direct external

Street network Logical inconsistency (topological inconsistency) Measure 1: Number of missing connections due to undershoots

Measure 2: Number of missing connections due to overshoots
Measure 3: Number of invalid self-intersect errors
Measure 4: Number of invalid self-overlap errors

Direct internal

Direct internal
Direct internal
Direct internal


2. Implementing data quality metadata conforming to ISO 19157:2013

Data quality metadata describes the quality of geographic data. ISO 19157:2013 specifies a conceptual model of the different components to be used when describing the quality of geographic data. Overview of the components to be used to describe data quality provides and overview of the components and their relationships to each other. A data dictionary, including definitions for all the components, is provided in the standard. Data quality metadata conforming to ISO 19157:2013 conforms to this conceptual model and is reported in conformance with ISO 19115:2003 Geographic information - Metadata and ISO 19115-2:2009 Geographic information - Metadata - Part 2: Extensions for imagery and gridded data


Overview of the components to be used to describe data quality (Source: ISO 19157:2013)


3. Implementing data quality reports conforming to ISO 19157:2013

The first (and obvious) requirement is that the quality report comprises quality metadata conforming to ISO 19157:2013 (see 2. above), i.e. it includes sections on all appropriate aspects of quality and the description of components follow the rules defined in the standard. Additional information can be added to the report, but the structure of the report is not prescribed. Example: Section of a data quality report is an example of a section of a data quality report for the quality evaluation process described above.


Example: Section of a data quality report
Data quality unit Data quality element Data quality measure Result
Topographic dataset Completeness (commission) Measure 2: Number of excess items

Measure 3: Number of duplicate feature instances

153

1,036

Topographic dataset Completeness (omission) Measure 2: Number of missing items 697
Topographic dataset Thematic accuracy (correct classification) Measure 1: Number of incorrectly classified features

Measure 2: Misclassification rate

8,774

10%

Street network Logical inconsistency (topological inconsistency) Measure 1: Number of missing connections due to undershoots

Measure 2: Number of missing connections due to overshoots
Measure 3: Number of invalid self-intersect errors
Measure 4: Number of invalid self-overlap errors

139

57
11
6


4. Implementing data quality measures conforming to ISO 19157:2013

A data quality measure conforming to ISO 19157:2013 is structurally and semantically well defined and described and modelled as specified in the standard. Such a measure is described by at least an identifier, a name, an element name, definition and a value type. Optional descriptors are an alias, description, a value structure, example, a basic measure and one or more source references and/or parameters. Note that full inspection is most appropriate for small populations or for tests that can be accomplished by automated means. For larger populations, checking a representative part of the data and reporting the quality result as a percentage rate is more appropriate and practical.

See also

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