EN ISO 19157:2013

SLOVENSKI STANDARD
01-februar-2015
1DGRPHãþD
SIST EN ISO 19113:2005
SIST EN ISO 19114:2005
SIST EN ISO 19114:2005/AC:2006
Geografske informacije - Kakovost podatkov (ISO 19157:2013)
Geographic information - Data quality (ISO 19157:2013)
Geoinformation - Datenqualität (ISO 19157:2013)
Information géographique - Qualité de données (ISO 19157:2013)
Ta slovenski standard je istoveten z: EN ISO 19157:2013
ICS:
03.120.99 Drugi standardi v zvezi s Other standards related to
kakovostjo quality
07.040 Astronomija. Geodezija. Astronomy. Geodesy.
Geografija Geography
35.240.70 Uporabniške rešitve IT v IT applications in science
znanosti
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

EUROPEAN STANDARD
EN ISO 19157
NORME EUROPÉENNE
EUROPÄISCHE NORM
December 2013
ICS 35.240.70 Supersedes EN ISO 19113:2005, EN ISO 19114:2005
English Version
Geographic information - Data quality (ISO 19157:2013)
Information géographique - Qualité des données (ISO Geoinformation - Datenqualität (ISO 19157:2013)
19157:2013)
This European Standard was approved by CEN on 9 November 2013.

CEN members are bound to comply with the CEN/CENELEC Internal Regulations which stipulate the conditions for giving this European
Standard the status of a national standard without any alteration. Up-to-date lists and bibliographical references concerning such national
standards may be obtained on application to the CEN-CENELEC Management Centre or to any CEN member.

This European Standard exists in three official versions (English, French, German). A version in any other language made by translation
under the responsibility of a CEN member into its own language and notified to the CEN-CENELEC Management Centre has the same
status as the official versions.

CEN members are the national standards bodies of Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia,
Finland, Former Yugoslav Republic of Macedonia, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania,
Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and United
Kingdom.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION

EUROPÄISCHES KOMITEE FÜR NORMUNG

CEN-CENELEC Management Centre: Avenue Marnix 17, B-1000 Brussels
© 2013 CEN All rights of exploitation in any form and by any means reserved Ref. No. EN ISO 19157:2013 E
worldwide for CEN national Members.

Contents Page
Foreword .3

Foreword
This document (EN ISO 19157:2013) has been prepared by Technical Committee ISO/TC 211 “Geographic
information/Geomatics” in collaboration with Technical Committee CEN/TC 287 “Geographic Information” the
secretariat of which is held by BSI.
This European Standard shall be given the status of a national standard, either by publication of an identical
text or by endorsement, at the latest by June 2014, and conflicting national standards shall be withdrawn at
the latest by June 2014.
Attention is drawn to the possibility that some of the elements of this document may be the subject of patent
rights. CEN [and/or CENELEC] shall not be held responsible for identifying any or all such patent rights.
This document supersedes EN ISO 19113:2005, EN ISO 19114:2005.
According to the CEN-CENELEC Internal Regulations, the national standards organizations of the following
countries are bound to implement this European Standard: Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech
Republic, Denmark, Estonia, Finland, Former Yugoslav Republic of Macedonia, France, Germany, Greece,
Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal,
Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and the United Kingdom.
Endorsement notice
The text of ISO 19157:2013 has been approved by CEN as EN ISO 19157:2013 without any modification.

INTERNATIONAL ISO
STANDARD 19157
First edition
2013-12-15
Geographic information — Data quality
Information géographique — Qualité des données
Reference number
ISO 19157:2013(E)
©
ISO 2013
ISO 19157:2013(E)
© ISO 2013
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized otherwise in any form
or by any means, electronic or mechanical, including photocopying, or posting on the internet or an intranet, without prior
written permission. Permission can be requested from either ISO at the address below or ISO’s member body in the country of
the requester.
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Tel. + 41 22 749 01 11
Fax + 41 22 749 09 47
E-mail copyright@iso.org
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Published in Switzerland
ii © ISO 2013 – All rights reserved

ISO 19157:2013(E)
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Conformance . 1
3 Normative references . 1
4 Terms and definitions . 2
5 Abbreviated terms . 4
5.1 Abbreviations . 4
5.2 Package abbreviations . 5
6 Overview of data quality . 5
7 Components of data quality . 6
7.1 Overview of the components . 6
7.2 Data quality unit . 7
7.3 Data quality elements . 8
7.4 Descriptors of data quality elements .11
7.5 Metaquality elements .14
7.6 Descriptors of a metaquality element .15
8 Data quality measures .16
8.1 General .16
8.2 Standardized data quality measures .16
8.3 User defined data quality measures .16
8.4 Catalogue of data quality measures .16
8.5 List of components .17
8.6 Component details .18
9 Data quality evaluation.20
9.1 The process for evaluating data quality .20
9.2 Data quality evaluation methods .21
9.3 Aggregation and derivation.23
10 Data quality reporting .23
10.1 General .23
10.2 Particular cases .24
Annex A (normative) Abstract test suites .26
Annex B (informative) Data quality concepts and their use .28
Annex C (normative) Data dictionary for data quality .34
Annex D (normative) List of standardized data quality measures .50
Annex E (informative) Evaluating and reporting data quality .96
Annex F (informative) Sampling methods for evaluating .119
Annex G (normative) Data quality basic measures .127
Annex H (informative) Management of data quality measures .132
Annex I (informative) Guidelines for the use of Quality Elements .135
Annex J (informative) Aggregation of data quality results .144
Bibliography .146
ISO 19157:2013(E)
Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
through ISO technical committees. Each member body interested in a subject for which a technical
committee has been established has the right to be represented on that committee. International
organizations, governmental and non-governmental, in liaison with ISO, also take part in the work.
ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. ISO shall not be held responsible for identifying any or all such patent rights. Details of
any patent rights identified during the development of the document will be in the Introduction and/or
on the ISO list of patent declarations received (see www.iso.org/patents).
Any trade name used in this document is information given for the convenience of users and does not
constitute an endorsement.
For an explanation on the meaning of ISO specific terms and expressions related to conformity
assessment, as well as information about ISO’s adherence to the WTO principles in the Technical Barriers
to Trade (TBT) see the following URL: Foreword - Supplementary information
The committee responsible for this document is ISO/TC 211, Geographic information/Geomatics
This edition of ISO 19157:2013 cancels and replaces ISO/TS 19138:2006, ISO 19114:2003 and
ISO 19113:2002, which have been technically revised.
iv © ISO 2013 – All rights reserved

ISO 19157:2013(E)
Introduction
Geographic data are increasingly being shared, interchanged and used for purposes other than their
producers’ intended ones. Information about the quality of available geographic data are vital to the
process of selecting a data set in that the value of data are directly related to its quality. A user of
geographic data may have multiple data sets from which to choose. Therefore, it is necessary to compare
the quality of the data sets to determine which best fulfils the requirements of the user.
The purpose of describing the quality of geographic data is to facilitate the comparison and selection
of the data set best suited to application needs or requirements. Complete descriptions of the quality
of a data set will encourage the sharing, interchange and use of appropriate data sets. Information on
the quality of geographic data allows a data producer to evaluate how well a data set meets the criteria
set forth in its product specification and assists data users in evaluating a product’s ability to satisfy
the requirements for their particular application. For the purpose of this evaluation, clearly defined
procedures are used in a consistent manner.
To facilitate comparisons, it is essential that the results of the quality reports are expressed in a
comparable way and that there is a common understanding of the data quality measures that have
been used. These data quality measures provide descriptors of the quality of geographic data through
comparison with the universe of discourse. The use of incompatible measures makes data quality
comparisons impossible to perform. This International Standard standardizes the components and
structures of data quality measures and defines commonly used data quality measures.
This International Standard recognizes that a data producer and a data user may view data quality
from different perspectives. Conformance quality levels can be set using the data producer’s product
specification or a data user’s data quality requirements. If the data user requires more data quality
information than that provided by the data producer, the data user can follow the data producer’s data
quality evaluation process flow to get the additional information. In this case the data user requirements
are treated as a product specification for the purpose of using the data producer process flow.
The objective of this International Standard is to provide principles for describing the quality for
geographic data and concepts for handling quality information for geographic data, and a consistent
and standard manner to determine and report a data set’s quality information. It aims also to provide
guidelines for evaluation procedures of quantitative quality information for geographic data.
INTERNATIONAL STANDARD ISO 19157:2013(E)
Geographic information — Data quality
1 Scope
This International Standard 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;
— establishes principles for reporting data quality.
This International 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 data set 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.
This International Standard does not attempt to define minimum acceptable levels of quality for
geographic data.
2 Conformance
Any product claiming conformance to this International Standard shall pass all the requirements
described in the abstract test suite presented in Annex A as follows:
a) A data quality evaluation process shall pass the tests outlined in A.1;
b) Data quality metadata shall pass the tests outlined in A.2 and A.3;
c) A standalone quality report shall pass the tests outlined in A.4;
d) A data quality measure shall pass the tests outlined in A.5.
3 Normative references
The following referenced documents, in whole or in part, are normatively referenced in this document
and are indispensable for its application. For dated references, only the edition cited applies. For undated
references, the latest edition of the referenced document (including any amendments) applies.
ISO/TS 19103:2005, Geographic information — Conceptual schema language
ISO 19108:2002, Geographic information — Temporal schema
1)
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 19135:2005, Geographic information — Procedures for item registration
1) Under preparation.
ISO 19157:2013(E)
4 Terms and definitions
4.1
accuracy
closeness of agreement between a test result or measurement result and the true value
Note 1 to entry: In this International Standard, the true value can be a reference value that is accepted as true.
[SOURCE: ISO 3534-2:2006, 3.3.1, modified – original Note has been deleted. New Note 1 to entry
has been added.]
4.2
catalogue
collection of items (4.18) or an electronic or paper document that contains information about the
collection of items
[SOURCE: ISO 10303-227:2005, 3.3.10, modified - Note has been deleted.]
4.3
conformance
fulfilment of specified requirements
[SOURCE: ISO 19105:2000, 3.8]
4.4
conformance quality level
threshold value or set of threshold values for data quality (4.21) results used to determine how well a
dataset (4.8) meets the criteria set forth in its data product specification (4.6) or user requirements
4.5
correctness
correspondence with the universe of discourse (4.24)
4.6
data product specification
detailed description of a dataset (4.8) or dataset series (4.9) together with additional information that
will enable it to be created, supplied to and used by another party
[SOURCE: ISO 19131:2007, 4.7, modified - Note has been deleted.]
4.7
data quality basic measure
generic data quality (4.21) measure used as a basis for the creation of specific data quality measures
Note 1 to entry: Data quality basic measures are abstract data types. They cannot be used directly when reporting
data quality.
4.8
dataset
identifiable collection of data
Note 1 to entry: A data set can be a smaller grouping of data which, though limited by some constraint such as
spatial extent or feature type (4.15), is located physically within a larger data set. Theoretically, a data set can be
as small as a single feature (4.11) or feature attribute (4.12) contained within a larger data set. A hardcopy map or
chart can be considered a data set.
2)
[SOURCE: ISO 19115-1:—, 4.3 ]
2) To be published.
2 © ISO 2013 – All rights reserved

ISO 19157:2013(E)
4.9
dataset series
collection of datasets (4.8) sharing common characteristics
3)
[SOURCE: ISO 19115-1:—, 4.10]
4.10
direct evaluation method
method of evaluating the quality (4.21) of a dataset (4.8) based on inspection of the items (4.18)
within the dataset
4.11
feature
abstraction of real world phenomena
Note 1 to entry: A feature may occur as a type or an instance. Feature type (4.15) or feature instance (4.13) will be
used when only one is meant.
[SOURCE: ISO 19101:2002, 4.11]
4.12
feature attribute
characteristic of a feature (4.11)
Note 1 to entry: A feature attribute has a name, a data type and a value domain associated with it. A feature
attribute for a feature instance (4.13) also has an attribute value taken from the value domain.
[SOURCE: ISO 19101:2002, 4.12, modified – Examples have been deleted. Note 1 to entry has been added.]
4.13
feature instance
individual of a given feature type (4.15) having specified feature attribute (4.12) values
4)
[SOURCE: ISO 19101-1:—, 4.1.14]
4.14
feature operation
operation that every instance of a feature type (4.15) may perform
[SOURCE: ISO 19110:2005, 4.5 - modified, Example and Note have been removed.]
4.15
feature type
class of features (4.11) having common characteristics
[SOURCE: ISO 19156:2011, 4.7]
4.16
geographic data
data with implicit or explicit reference to a location relative to the Earth
[SOURCE: ISO 19109:2005, 4.12, modified - Note has been deleted.]
4.17
indirect evaluation method
method of evaluating the quality (4.21) of a dataset (4.8) based on external knowledge
Note 1 to entry: Examples of external knowledge are data set lineage, such as production method or source data.
3) To be published.
4) To be published.
ISO 19157:2013(E)
4.18
item
anything that can be described and considered separately
Note 1 to entry: An item can be any part of a data set (4.8), such as a feature (4.11), feature relationship, feature
attribute (4.12), or combination of these.
[SOURCE: ISO 2859-5:2005, 3.4, modified – Original Example has been removed. Note 1 to entry has
been added.]
4.19
metadata
information about a resource
5)
[SOURCE: ISO 19115-1:—, 4.9]
4.20
metaquality
information describing the quality (4.21) of data quality
4.21
quality
degree to which a set of inherent characteristics fulfils requirements
[SOURCE: ISO 9000:2005, 3.1.1, modified - Original Notes have been removed.]
4.22
register
set of files containing identifiers assigned to items (4.18) with descriptions of the associated items
[SOURCE: ISO 19135:2005, 4.1.9]
4.23
standalone quality report
free text document providing fully detailed information about data quality (4.21) evaluations, results
and measures used
4.24
universe of discourse
view of the real or hypothetical world that includes everything of interest
[SOURCE: ISO 19101:2002, 4.29]
5 Abbreviated terms
5.1 Abbreviations
ADQR aggregated data quality results
AQL acceptance quality limit [ISO 3534-2:2006]
RMSE root mean square error
UML Unified Modeling Language
XML Extensible Markup Language
5) To be published.
4 © ISO 2013 – All rights reserved

ISO 19157:2013(E)
5.2 Package abbreviations
Abbreviations are used to denote the package that contains a class. Those abbreviations precede class
names, connected by a “_”. The standard in which those classes are located is indicated in parentheses.
A list of those abbreviations follows.
CI Citation [ISO 19115-1:2014]
CT Catalogues [ISO/TS 19139:2007]
DQ Data Quality [ISO 19157]
DQM Data Quality Measure [ISO 19157]
EX Extent [ISO 19115-1:2014]
GF General Feature [ISO 19109:2005]
MD Metadata [ISO 19115-1:2014]
QE Quality Extended [ISO 19115-2:2009]
RE Registration [ISO 19135:2005]
6 Overview of data quality
Working with data quality includes:
— understanding of the concepts of data quality related to geographic data. Annex B is a description of
data quality concepts used to establish the components for describing the quality of geographic data;
— defining data quality conformance levels in data product specifications or based on user
requirements. Establishment of data product specifications is described in ISO 19131:2007;
— specifying quality aspects in application schemas;
— evaluating data quality;
— reporting data quality.
NOTE 1 The development of application schemas is described in ISO 19109:2005.
A data quality evaluation can be applied to data set series, a data set or a subset of data within a data set,
sharing common characteristics so that its quality can be evaluated.
Data quality shall be described using the data quality elements. Data quality elements and their
descriptors are used to describe how well a data set meets the criteria set forth in its data product
specification or user requirements and provide quantitative quality information.
When data quality information describes data that have been created without a detailed data product
specification or with a data product specification that lacks quantitative measures and descriptors, the
data element may be evaluated in a non-quantitative subjective way as a descriptive result for each element.
ISO 19157:2013(E)
Some quality related information is provided by purpose, usage and lineage. This information is reported
as metadata in conformance with ISO 19115-1:2014.
NOTE 2 Purpose describes the rationale for creating a data set and contains information about its intended
use, which may not be the same as the actual use of the data set. Usage describes the application(s) for which a
data set has been used, either by the data producer or by other data users. Lineage describes the history of a data
set and recounts the life cycle of a data set from collection and acquisition through compilation and derivation to
its current form. This general, non-quantitative information is illustrative for users and can help assessing the
quality of a data set, especially in cases where it is used for a particular application that differs from the intended
application (see also 9.2.3).
This International Standard recognizes that quantitative data quality elements may have associated
quality which is termed metaquality. Metaquality describes the quality of the data quality results in
terms of defined characteristics.
NOTE 3 The concept of metaquality is described in 7.5.
Figure 1 provides an overview of data quality information.
co ncerns Standalone quality report
geog ra ph ic da ta
is re po rted in
de i ned by
Data quality scope Data quality
Metadata ISO19115
su bd ivid es in to is expresse d by
Result scope Data quality element
is de scri bed by
Data quality measureData quality ev aluation Data quality result Metaquality
Figure 1 — Conceptual model of quality for geographic data
7 Components of data quality
7.1 Overview of the components
The components of data quality are described in Clause 7. Figure 2 presents an overview of the
components and the connections between them. See the data dictionary defined in Annex C (normative)
for more details about components and their attributes.
6 © ISO 2013 – All rights reserved

ISO 19157:2013(E)
DQ_FullInspection DQ_ConformanceResult
DQ_SampleBasedInspection DQ_QuantitativeResult
DQ_IndirectEvaluation DQ_DescriptiveResult
DQ_DataEvaluation
DQ_AggregationDerivation
DQ_MeasureReference DQ_EvaluationMethod DQ_Result
+measure 0.1 +evaluationMethod 0.1 +result1.*
DQ_StandaloneQualityReportInformation
0.*
+standaloneQualityReport0.1
DQ_Metaquality DQ_Element
+elementReport
+relatedElement
+report
+derivedElement DQ_DataQuality
1.*
0.*
DQ_Confidence
DQ_Representativity
DQ_UsabilityElement
DQ_LogicalConsistency
DQ_Homogeneity
DQ_ConceptualConsistency DQ_PositionalAccuracy
DQ_Completeness
DQ_DomainConsistency
DQ_AbsoluteExternalPositionalAccuracy
DQ_CompletenessCommission
DQ_FormatConsistency
DQ_RelativeInternalPositionalAccuracy
DQ_CompletenessOmission
DQ_TopologicalConsistency
DQ_GriddedDataPositionalAccuracy
DQ_ThematicAccuracy
DQ_TemporalQuality
DQ_ThematicClassificationCorrectness
DQ_AccuracyOfATimeMeasurement
DQ_NonQuantitativeAttributeCorrectness
DQ_TemporalConsistency
DQ_QuantitativeAttributeAccuracy
DQ_TemporalValidity
Figure 2 — Overview of the components of data quality
7.2 Data quality unit
When describing the quality of geographic data, different quality elements and different subsets of the
data may be considered. In order to describe these, data quality units are used. A data quality unit is the
combination of a scope and data quality elements, see Figure 3.
ISO 19157:2013(E)
DQ_DataQuality DQ_Element
+report
+  scope :M D_ Scop e
1.*
Figure 3 — Data quality unit
The scope of the data quality unit(s) specifies the extent, spatial and/or temporal, and/or common
characteristic(s) that identify the data on which data quality is to be evaluated.
One data quality scope shall be specified for each data quality unit. One data quality report (metadata
or standalone quality report) may encompass several data quality units, since scopes are often different
for individual data quality elements. These different scopes may be, for example, spatially separate,
overlapping or even sharing the same extents.
The following are examples of what defines a data quality scope (see also MD_Scope in ISO 19115-1):
a) a data set series;
b) a data set;
c) a subset of data defined by one or more of the following characteristics:
1) types of items (sets of feature types, feature attributes, feature operations or feature
relationships);
2) specific items (sets of feature instances, attribute values or instances of feature relationships);
3) geographic extent;
4) temporal extent (the time frame of reference and accuracy of the time frame).
7.3 Data quality elements
7.3.1 General
A data quality element is a component describing a certain aspect of the quality of geographic data and
these have been organized into different categories. These categories are shown in Figure 4.
8 © ISO 2013 – All rights reserved

ISO 19157:2013(E)
DQ_Element
+derivedElement 0.*
DQ_UsabilityElement
DQ_Completeness DQ_LogicalConsistency
DQ_CompletenessCommission DQ_ConceptualConsistency DQ_PositionalAccuracy
DQ_DomainConsistency
DQ_CompletenessOmission
DQ_AbsoluteExternalPositionalAccuracy
DQ_FormatConsistency
DQ_RelativeInternalPositionalAccuracy
DQ_TopologicalConsistency
DQ_GriddedDataPositionalAccuracy
DQ_ThematicAccuracy
DQ_TemporalQuality
DQ_ThematicClassificationCorrectness
DQ_AccuracyOfATimeMeasurement
DQ_NonQuantitativeAttributeCorrectness
DQ_TemporalConsistency
DQ_QuantitativeAttributeAccuracy
DQ_TemporalValidity
Figure 4 — Overview of the data quality elements
7.3.2 Completeness
Completeness is defined as the presence and absence of features, their attributes and relationships. It
consists of two data quality elements:
— commission: excess data present in a data set;
— omission: data absent from a data set.
7.3.3 Logical consistency
Logical consistency is defined as the degree of adherence to logical rules of data structure, attribution
and relationships (data structure can be conceptual, logical or physical). If these logical rules are
documented elsewhere (for example, in a data product specification) then the source should be
referenced (for example, in the data quality evaluation). It consists of four data quality elements:
— conceptual consistency: adherence to rules of the conceptual schema;
— domain consistency: adherence of values to the value domains;
— format consistency: degree to which data are stored in accordance with the physical structure of
the data set;
— topological consistency: correctness of the explicitly encoded topological characteristics of a data set.
ISO 19157:2013(E)
7.3.4 Positional accuracy
Positional accuracy is defined as the accuracy of the position of features within a spatial reference
system. It consists of three data quality elements:
— absolute or external accuracy: closeness of reported coordinate values to values accepted as or
being true;
— relative or internal accuracy: closeness of the relative positions of features in a data set to their
respective relative positions accepted as or being true;
— gridded data positional accuracy: closeness of gridded data spatial position values to values accepted
as or being true.
7.3.5 Thematic accuracy
Thematic accuracy is defined as the accuracy of quantitative attributes and the correctness of non-
quantitative attributes and of the classifications of features and their relationships. It consists of three
data quality elements:
— classification correctness: comparison of the classes assigned to features or their attributes to a
universe of discourse (e.g. ground truth or reference data);
— non-quantitative attribute correctness: measure of whether a non-quantitative attribute is correct
or incorrect;
— quantitative attribute accuracy: closeness of the value of a quantitative attribute to a value accepted
as or known to be true.
7.3.6 Temporal quality
Temporal quality is defined as the quality of the temporal attributes and temporal relationships of
features. It consists of three data quality elements:
— accuracy of a time measurement: closeness of reported time measurements to values accepted as or
known to be true;
— temporal consistency: correctness of the order of events;
— temporal validity: validity of data with respect to time.
NOTE Time measurement can be either a defined point in time or a period.
EXAMPLE March 33 is an example of invalid data.
7.3.7 Usability element
Usability is based on user requirements. All quality elements may be used to evaluate usability.
Usability evaluation may be based on specific user requirements that cannot be described using the
quality elements described above. In this case, the usability element shall be used to describe specific
quality information about a data set’s suitability for a particular application or conformance to a set of
requirements.
It is recommended when using the usability element, to use all applicable quality elements descriptors
(see 7.4) and to define the quality measures applied in conformance with Clause 8 or Annex D, in order
to provide precise details on the evaluation.
EXAMPLE With this element, a data producer can show how a data set is suitable for various identified usages.
This element can be used to declare the conformance of the data set to a particular specification.
10 © ISO 2013 – All rights reserved

ISO 19157:2013(E)
7.4 Descriptors of data quality elements
7.4.1 General
An evaluation of a data quality element is described by the following:
— measure: the type of evaluation;
— evaluation method: the procedure used to evaluate the measure;
— result: the output of the evaluation.
These are shown in Figure 5, and are described in 7.4.2, 7.4.3 and 7.4.4.
DQ_Element
+m easure +evaluationM ethod +result
0.1 0.1 1.*
DQ_MeasureReference DQ_EvaluationMethod DQ_Result
Figure 5 — Data quality element descriptors
7.4.2 Measure
A data quality element should refer to one measure only, by means of a measure reference (see Figure 6),
providing an identifier of a measure fully described elsewhere (DQM_Measure.measureIdentifier,
see 8.6.1) and/or providing the name and a short description of the measure.
NOTE The whole description can be found within a measure register or catalogue, which can form part of a
data product specification or a standalone quality report.
DQ_Element
From IS O 19115-1:2014
+m ea su re 0.1
«DataT yp e»
MD_Identi ier
DQ_MeasureReference
+  au th ority :CI_ Ci ta ti on [0 .1 ]
+  me asureIden ti i ca ti on :M D_ Id en ti i er [0 .1]
+  co de :Cha ra cterStri ng
+  na me OfMe asure :Cha ra cterStri ng [0 .*]
+  co deSpace :Cha ra cterStri ng [0 .1]
+  me asureDescrip ti on :Cha ra cterStri ng [0 .1]
+  ve rsio n :Cha ra cterStri ng [0 .1 ]
constraints
+  de scri ptio n :Cha ra cterStri ng [0 .1]
{If me asureIdenti icatio n is no t provid ed ,then na me OfMe asure sh a ll be
provid ed }
Figure 6 — Data quality measure reference
Data quality measures are further described in Clause 8 of this International Standard. Annex D contains
a list of standardized data quality measures.
EXAMPLE The percentage of the values of an attribute which are correct.
ISO 19157:2013(E)
This International Standard recognizes that the quality of a data set is measured using a variety of
methods. A single data quality measure might be insufficient for fully evaluating the quality of the data
specified by a data quality scope and providing a measure of quality for all possible utilizations of a data
set. A combination of data quality measures can give useful information. Multiple data quality measures
may be reported for the data specified by a data quality scope. The data quality report should then
include one instance of DQ_Element for each measure applied.
7.4.3 Evaluation method
Data quality evaluation method describes those procedures and methods which are applied to the
geographic data to arrive at a data quality result, see Figure 7. Different evaluations are often used for
the various data quality elements.
Data quality evaluation method should be included for each applied data quality measure. Data quality
evaluation method is used for describing, or for referencing documentation describing, the methodology
used to apply a data quality measure to the data specified by a data quality scope.
NOTE Data quality evaluation is further described in Clause 9.
EXAMPLE Examples of documentation are data product specifications, published articles or accepted
industry standards.
One date or range of dates should be included for each evaluation. If the evaluation was carried out on
non-consecutive dates, each single date should be included. The dates shall be in conformance with
ISO 19108:2002.
Data quality::DQ_Element
+  standa lo neQ ual ityReportDetai ls :Cha ra cterStri ng [0 .1]
+d erivedEl em en t 0.*
+e va l uatio nM ethod 0 .1
DQ_EvaluationMethod
«CodeL ist»
DQ_EvaluationMethodTypeCode
+  da te Ti me :DateT im e [0 .*]
+  eval ua ti on Me th odDescrip ti on :Cha ra cterStri ng [0 .1]
+  di re ctIn te rn al
+  eval ua ti onProcedure :CI_ Ci ta ti on [0 .1 ]
+  di re ctExte rn al
+  re fe re nceDoc :CI_ Ci ta ti on [0 .*]
+  in di re ct
+  eval ua ti on Me th odT yp e :DQ_ Eval ua ti on Me th od Type Co de [0 .1]
Figure 7 — Data quality evaluation method
7.4.4 Result
7.4.4.1 General
At least one data quality result shall be provided for each data quality element. This could be a quantitative
result, a conformance result, a descriptive result or a coverage result, see also Figure 8.
NOTE 1 Different types of results can be provided for the same data quality element.
12 © ISO 2013 – All rights reserved

ISO 19157:2013(E)
DQ_Element
+resul t
1.*
DQ_Result
+  da te Ti me :DateT im e [0 .1]
+  re su ltScope :M D_ Scope [0 .1]
constraints
{resul tS co pe is a subset of DQ _DataQ ua li ty.sco pe }
DQ_Quantitativ eResult DQ_ConformanceResult DQ_DescriptiveResult
+  va lu e :Record [1 .*] +  pa ss :B oo le an +  statem ent :Cha ra cterStri ng
+  va lu eUnit :Uni tO fM ea su re [0 .1] +  sp eciicatio n :CI_ Ci ta ti on
+  va lu eRecordT yp e :RecordT yp e [0 .1 ] +  expl anatio n :Cha ra cterStri ng [0 .1 ]
Figure 8 — Data quality result
Quality frequently differs between various parts of the data set for which quality is evaluated. Therefore
several evaluations may be applied for the same data quality element to more completely and, in more
detail, describe quantitative data quality. To avoid repeating the measure and evaluation procedure
descriptions in several instances of data quality element (DQ_Element), several results with individual
result scopes can be used.
NOTE 2 The result scope is a subset of the data quality scope (see 7.2).
EXAMPLE A data set contains features of identical type but whose positions have been established with
separate methods yielding different positional accuracies. The same quality evaluation method and the same
measure are, however, applied for the whole data set, and provide different results depending of the data
acquisition method. In this case, it may be desirable to have several results with individual result scopes (the area
covered by each data acquisition method) and one data quality scope (the data set).
7.4
...