SIST-TS ISO/TS 19138:2009
Geographic information - Data quality measures
Geographic information - Data quality measures
This Technical Specification defines a set of data quality measures. These can be used when reporting data quality for the data quality subelements identified in ISO 19113. Multiple measures are defined for each data quality subelement, and the choice of which to use will depend on the type of data and its intended purpose. The data quality measures are structured so that they can be maintained in a register established in conformance with ISO 19135.
Information géographique - Mesures de la qualité des données
Geografske informacije - Kakovostne mere za prostorske podatke
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TECHNICAL ISO/TS
SPECIFICATION 19138
First edition
2006-12-01
Geographic information — Data quality
measures
Information géographique — Mesures de la qualité des données
Reference number
ISO/TS 19138:2006(E)
©
ISO 2006
---------------------- Page: 1 ----------------------
ISO/TS 19138:2006(E)
PDF disclaimer
This PDF file may contain embedded typefaces. In accordance with Adobe's licensing policy, this file may be printed or viewed but
shall not be edited unless the typefaces which are embedded are licensed to and installed on the computer performing the editing. In
downloading this file, parties accept therein the responsibility of not infringing Adobe's licensing policy. The ISO Central Secretariat
accepts no liability in this area.
Adobe is a trademark of Adobe Systems Incorporated.
Details of the software products used to create this PDF file can be found in the General Info relative to the file; the PDF-creation
parameters were optimized for printing. Every care has been taken to ensure that the file is suitable for use by ISO member bodies. In
the unlikely event that a problem relating to it is found, please inform the Central Secretariat at the address given below.
© ISO 2006
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized in any form or by any means,
electronic or mechanical, including photocopying and microfilm, without permission in writing from either ISO at the address below or
ISO's member body in the country of the requester.
ISO copyright office
Case postale 56 • CH-1211 Geneva 20
Tel. + 41 22 749 01 11
Fax + 41 22 749 09 47
E-mail copyright@iso.org
Web www.iso.org
Published in Switzerland
ii © ISO 2006 – All rights reserved
---------------------- Page: 2 ----------------------
ISO/TS 19138:2006(E)
Contents Page
Foreword. iv
Introduction . v
1 Scope .1
2 Conformance.1
3 Normative references .1
4 Terms and definitions .1
5 Relationships to other standards.2
6 Register.3
7 Components of a data quality measure .3
7.1 List of components.3
7.2 Component details.4
7.3 Standardized data quality measures .6
Annex A (normative) Abstract test suite.7
A.1 Test case identifier: Component test.7
A.2 Test case identifier: Name test.7
A.3 Test case identifier: Data quality element and subelement test.7
A.4 Test case identifier: Data quality basic measure test.8
A.5 Test case identifier: Definition test.8
A.6 Test case identifier: Description test.8
A.7 Test case identifier: Parameter test.8
A.8 Test case identifier: Data quality value type test .8
A.9 Test case identifier: Source reference test .9
A.10 Test case identifier: Example test.9
Annex B (normative) Structure of data quality measures.10
B.1 Components defining a data quality measure.10
B.2 Mapping of the components to ISO 19115 and ISO 19135 .11
B.3 UML-diagram for data quality measure .11
Annex C (normative) Data quality basic measures .14
C.1 Purpose of data quality basic measures.14
C.2 Counting-related data quality basic measures.14
C.3 Uncertainty-related data quality basic measures.15
Annex D (normative) List of data quality measures .19
D.1 Completeness .19
D.2 Logical consistency .23
D.3 Positional accuracy .37
D.4 Temporal accuracy .58
D.5 Thematic accuracy.61
Bibliography .68
© ISO 2006 – All rights reserved iii
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ISO/TS 19138:2006(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.
International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2.
The main task of technical committees is to prepare International Standards. Draft International Standards
adopted by the technical committees are circulated to the member bodies for voting. Publication as an
International Standard requires approval by at least 75 % of the member bodies casting a vote.
In other circumstances, particularly when there is an urgent market requirement for such documents, a
technical committee may decide to publish other types of normative document:
⎯ an ISO Publicly Available Specification (ISO/PAS) represents an agreement between technical experts in
an ISO working group and is accepted for publication if it is approved by more than 50 % of the members
of the parent committee casting a vote;
⎯ an ISO Technical Specification (ISO/TS) represents an agreement between the members of a technical
committee and is accepted for publication if it is approved by 2/3 of the members of the committee casting
a vote.
An ISO/PAS or ISO/TS is reviewed after three years in order to decide whether it will be confirmed for a
further three years, revised to become an International Standard, or withdrawn. If the ISO/PAS or ISO/TS is
confirmed, it is reviewed again after a further three years, at which time it must either be transformed into an
International Standard or be withdrawn.
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.
ISO/TS 19138 was prepared by Technical Committee ISO/TC 211, Geographic information/Geomatics.
iv © ISO 2006 – All rights reserved
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ISO/TS 19138:2006(E)
Introduction
Knowledge of the quality of geographic data is often crucial for the application of the data, as different users
and different applications often have different data quality requirements. A user of geographic data may have
multiple datasets from which to choose. Therefore, it is necessary to compare the quality of the datasets to
determine which best fulfils the requirements of the user. To facilitate such 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.
Data quality needs to be reported by the producer and evaluated by the user against his or her requirements
for different criteria and data quality measures. It is essential that reported quality for a dataset contains the
quality measurements that may be of interest to a potential user of the dataset, and that the metrics used to
determine the quality are reported and available to the user.
ISO 19113 establishes the principles for the description of geographic data quality and specifies components
for reporting quality information. Procedures for the evaluation of geographic data quality are described in
ISO 19114.
The objective of this Technical Specification is to guide the producer in choosing the right data quality
measures for data quality reporting, and the user in the evaluation of the usefulness of a dataset by
standardizing the components and structures of data quality measures and by defining commonly used data
quality measures.
© ISO 2006 – All rights reserved v
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TECHNICAL SPECIFICATION ISO/TS 19138:2006(E)
Geographic information — Data quality measures
1 Scope
This Technical Specification defines a set of data quality measures. These can be used when reporting data
quality for the data quality subelements identified in ISO 19113. Multiple measures are defined for each data
quality subelement, and the choice of which to use will depend on the type of data and its intended purpose.
The data quality measures are structured so that they can be maintained in a register established in
conformance with ISO 19135.
This Technical Specification does not attempt to describe every possible data quality measure, only a set of
commonly used ones.
2 Conformance
Any set of data quality measures claiming conformance with this Technical Specification shall pass all of the
conditions specified in the abstract test suite (Annex A).
3 Normative references
The following referenced documents are indispensable for the application of this document. 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 19113:2002, Geographic information — Quality principles
ISO 19115:2003, Geographic information — Metadata
ISO 19135:2005, Geographic information — Procedures for item registration
4 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
4.1
correctness
correspondence with the universe of discourse
4.2
data quality basic measure
generic data quality measure used as a basis for the creation of specific data quality measures
NOTE Data quality basic measures are abstract data types. They cannot be used directly when reporting data
quality.
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ISO/TS 19138:2006(E)
4.3
data quality scope
extent or characteristic(s) of the data for which quality information is reported
[ISO 19113]
NOTE A data quality scope for a dataset can comprise a dataset series to which the dataset belongs, the dataset
itself, or a smaller grouping of data located physically within the dataset sharing common characteristics. Common
characteristics can be an identified feature type, feature attribute, or feature relationship; data collection criteria; original
source; or a specified geographic or temporal extent.
4.4
error
discrepancy with the universe of discourse
4.5
measurand
particular quantity subject to measurement
[International Vocabulary of Basic and General Terms in Metrology (VIM)]
4.6
universe of discourse
view of the real or hypothetical world that includes everything of interest
[ISO 19101]
5 Relationships to other standards
ISO 19113 describes relevant data quality elements and their corresponding data quality subelements and it
indicates how quality should be reported. ISO 19114 describes procedures for the evaluation of quantitative
quality. ISO 19115 contains elements and classes for data quality reporting within the UML models and data
dictionaries.
ISO 19113 specifies a set of descriptors for a data quality subelement, for use in recording data quality. One
of these descriptors is the data quality measure. A data quality measure is described by the components listed
in 7.1.
Table 1 provides a list of data quality elements and data quality subelements as defined in ISO 19113.
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ISO/TS 19138:2006(E)
Table 1 — Data quality elements and data quality subelements with definitions (ISO 19113)
Data quality element Data quality subelement Definition
completeness commission excess data present in a dataset
omission data absent from a dataset
logical consistency conceptual consistency adherence to rules of the conceptual schema
domain consistency adherence of values to the value domains
format consistency degree to which data is stored in accordance
with the physical structure of the dataset
topological consistency correctness of the explicitly encoded
topological characteristics of a dataset
positional accuracy 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 dataset to their respective relative positions
accepted as or being true
gridded data position accuracy closeness of gridded data position values to
values accepted as or being true
temporal accuracy accuracy of a time measurement correctness of the temporal references of an
item (reporting of error in time measurement)
temporal consistency correctness of ordered events or sequences, if
reported
temporal validity validity of data with respect to time
thematic accuracy classification correctness comparison of the classes assigned to features
or their attributes to a universe of discourse
(e.g. ground truth or reference dataset)
non-quantitative attribute correctness correctness of non-quantitative attribute
quantitative attribute accuracy accuracy of quantitative attributes
6 Register
A register of data quality measures shall contain a set of data quality measures, described using the
components listed in 7.1. The registration procedures shall be performed according to ISO 19135.
Annex D of this Technical Specification contains the list of standardized data quality measures. A register
shall contain these data quality measures and may also contain additional data quality measures submitted
through the procedures defined within ISO 19135. The registration process also allows retiring data quality
measures.
7 Components of a data quality measure
7.1 List of components
Each data quality measure shall be described using the following technical components:
⎯ name (7.2.1)
⎯ alias (7.2.2)
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ISO/TS 19138:2006(E)
⎯ data quality element (7.2.3)
⎯ data quality subelement (7.2.4)
⎯ data quality basic measure (7.2.5)
⎯ definition (7.2.6)
⎯ description (7.2.7)
⎯ parameter (7.2.8)
⎯ data quality value type (7.2.9)
⎯ data quality value structure (7.2.10)
⎯ source reference (7.2.11)
⎯ example (7.2.12)
⎯ identifier (7.2.13)
7.2 Component details
7.2.1 Name
Name refers to the name of the data quality measure.
If the data quality measure already has a commonly used name, this name should be used. If no name exists,
a name shall be chosen that reflects the nature of the measure.
NOTE The component name is specified in the base standard for registers, ISO 19135.
7.2.2 Alias
Alias refers to other recognized name for the same data quality measure. It may be a different commonly used
name, or an abbreviation or a short name.
More than one alias may be provided.
7.2.3 Data quality element
Data quality element refers to the name of the data quality element to which this data quality measure applies.
NOTE A list of data quality elements is provided in Table 1.
7.2.4 Data quality subelement
Data quality subelement refers to the name of the data quality subelement to which this data quality measure
applies.
NOTE A list of data quality subelements is provided in Table 1.
7.2.5 Data quality basic measure
Each data quality basic measure is described by its name, definition and value type. Data quality basic
measures are identified by their names.
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ISO/TS 19138:2006(E)
A variety of data quality measures are based on counting of erroneous items. There are also several data
quality measures dealing with the uncertainty of numerical values. In order to avoid repetition, all possible
methods of constructing counting-related data quality measures as well as general statistical measures for
one- and two-dimensional random variables shall be defined in terms of data quality basic measures.
The data quality basic measures are defined in Annex C.
If a data quality measure is based on one of the set of data quality basic measures, the name of the data
quality basic measure shall be provided in the field data quality basic measure. If the data quality measure is
not based on a data quality basic measure, it shall be indicated in this field that a data quality basic measure
is not applicable. The data quality basic measures shall also be used as appropriate for creating new data
quality measures, for instance for reporting unclosed surface patches or other application-dependent data
quality measures.
7.2.6 Definition
Definition states the fundamental concept of the data quality measure.
If the data quality measure is derived from a data quality basic measure, the definition is based on the data
quality basic measure definition and specialized for this data quality measure.
NOTE The component definition is specified in the base standard for registers, ISO 19135.
7.2.7 Description
Description refers to the description of the data quality measure including methods of calculation, with all
formulae and/or illustrations needed to establish the result of applying the measure.
If the data quality measure uses the concept of errors, it shall be stated how an item shall be classified as
incorrect.
NOTE The component description is specified in the base standard for registers, ISO 19135.
7.2.8 Parameter
Parameter refers to an auxiliary variable used by the data quality measure. It shall include name, definition
and description.
More than one parameter may be provided.
7.2.9 Data quality value type
Data quality value type refers to the value type for reporting a data quality result.
A data quality value type shall be provided for a data quality result. The data types defined in ISO/TS 19103
shall be used when appropriate.
Table 2 — Examples of data quality value types
Boolean
Real
Integer
Ratio (numerator of type integer : denominator of type integer)
Percentage
Measure(s) [value(s) + unit(s)]
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ISO/TS 19138:2006(E)
7.2.10 Data quality value structure
Data quality value structure gives the structure for reporting a complex data quality result.
A data quality result may consist of multiple values. In this case, the data quality result shall be structured
using the data quality value structures as given in Table 3. The structure may consist of homogeneous or
heterogeneous data quality value types. The possible data quality value types are given in 7.2.9.
Table 3 — Data quality value structures
Bag
Set
Sequence
Table
Matrix
Coverage
NOTE The values within a structure can be multiple. For example, the covariance matrix as given in Table D.32 is
reported as matrix of measure, where the matrix elements may have different units of measure. A list may consist of
different data quality value types.
7.2.11 Source reference
Source reference gives the citation of the source of the data quality measure.
When a data quality measure for which additional information is provided in an external source is added to the
list of standardized data quality measures, a reference to that source may be provided here.
NOTE The component source reference is specified in the base standard for registers, ISO 19135.
7.2.12 Example
Example may provide examples of applying the data quality measure or the result obtained for the data quality
measure.
More than one example may be provided.
7.2.13 Identifier
Identifier consists of an integer number that uniquely identifies a data quality measure.
If data quality measures are administered in a register, then identifiers may only be assigned by the register
manager.
NOTE The component identifier is specified in the base standard for registers, ISO 19135.
7.2.14 Obligation of the above-listed components
Some of the components are mandatory, others are conditional or optional. Table B.1 provides further
information on the obligation of each technical component.
7.3 Standardized data quality measures
In order to make data quality related metadata and data quality reports comparable, standardized data quality
measures shall be used in evaluating and reporting data quality, where appropriate. Annex D gives a list of
commonly used data quality measures with all required components for data quality measures as specified in
this Technical Specification.
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ISO/TS 19138:2006(E)
Annex A
(normative)
Abstract test suite
A.1 Test case identifier: Component test
a) Test purpose: to determine conformance by ensuring that all necessary components of a data quality
measure are provided.
b) Test method: examine the entry for the data quality measure and verify that the components have been
provided as required by Table B.1.
c) Reference: 7.2 and Annex B.
d) Test type: Capability.
A.2 Test case identifier: Name test
a) Test purpose: to determine if a distinct name for the data quality measure is used.
b) Test method: determine if the name for the data quality measure is distinct from other measures with
different concepts, and if the name is not in conflict with other data quality basic measures, their
definitions and descriptions.
c) Reference: 7.2.1.
d) Test type: Capability.
A.3 Test case identifier: Data quality element and subelement test
a) Test purpose: to determine
⎯ if data quality element and subelement are assigned;
⎯ if they are taken from the list of data quality elements and subelements in ISO 19113 or if they are an
additional data quality element and subelement created in conformance with the rules of ISO 19113;
⎯ if the data quality measure is relevant for the given data quality element and subelement.
b) Test method: check if proper values are assigned to the data quality element and subelement
components and if the data quality measure has bearing on these.
c) Reference: 7.2.3 and 7.2.4.
d) Test type: Capability.
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ISO/TS 19138:2006(E)
A.4 Test case identifier: Data quality basic measure test
a) Test purpose: to determine if a data quality measure is properly derived from a data quality basic
measure.
b) Test method: check if an appropriate data quality basic measure for the data quality measure exists and,
if it does, that the data quality measure is utilizing this data quality basic measure in conformance with
this Technical Specification.
c) Reference: 7.2.5.
d) Test type: Capability.
A.5 Test case identifier: Definition test
a) Test purpose: to determine if a fitting, correct and complete definition is provided.
b) Test method: check that the given definition contains no ambiguities and that it is in conformance with
characteristics of a definition as stated in ISO 19135:2005, 7.3.1.
c) Reference: 7.2.6 and ISO 19135:2005, 7.3.1.
d) Test type: Capability.
A.6 Test case identifier: Description test
a) Test purpose: to determine if an exhaustive description is provided.
b) Test method: check if the description contains a comprehensive explanation with all required formulae to
facilitate the application of the data quality measure.
c) Reference: 7.2.7.
d) Test type: Capability.
A.7 Test case identifier: Parameter test
a) Test purpose: to determine if required parameters are provided.
b) Test method: check if all parameters occurring in the description are provided in the parameter
component.
c) Reference: 7.2.8.
d) Test type: Capability.
A.8 Test case identifier: Data quality value type test
a) Test purpose: to determine if a proper data quality value type is provided.
b) Test method: check if the provided data quality value type is included in the list in Table 3.
c) Reference: 7.2.9.
d) Test type: Capability.
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ISO/TS 19138:2006(E)
A.9 Test case identifier: Source reference test
a) Test purpose: to determine if a proper source reference is provided.
b) Test method: check if the cited reference source exists and if it reflects the concept of the provided data
quality measure.
c) Reference: 7.2.11.
d) Test type: Capability.
A.10 Test case identifier: Example test
a) Test purpose: to determine if the example, if provided, is a valid example for the data quality measure.
b) Test method: check if the example is free of errors and if it is representative of the usage of the data
quality measure.
c) Reference: 7.2.12.
d) Test type: Capability.
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ISO/TS 19138:2006(E)
Annex B
(normative)
Structure of data quality measures
B.1 Components defining a data quality measure
Table B.1 shall be used for the technical specification of every data quality measure. The descriptor for
obligation/condition may have the following values: M (mandatory), C (conditional), or O (optional).
Table B.1 — Components defining a data quality measure
Line Component Description Obligation/condition
1 Name Name of the data quality measure applied to the M
data
a
2 Alias Another recognized name, an abbreviation or a O
short name for the same data quality measure
3 Data quality element Name of the data quality element for which M
quality is reported
4 Data quality subelement Name of the data quality subelement for which M
quality is reported
5 Data quality basic Name of the data quality basic measure from C/if derived from basic measure
measure which the data quality measure is derived
6 Definition Definition of the fundamental concept for the M
data quality measure
7 Description Description of the data quality measure, C/if the definition is not sufficient
including
...
SLOVENSKI STANDARD
SIST-TS ISO/TS 19138:2009
01-september-2009
Geografske informacije - Kakovostne mere za prostorske podatke
Geographic information - Data quality measures
Information géographique - Mesures de la qualité des données
Ta slovenski standard je istoveten z: ISO/TS 19138:2006
ICS:
35.240.70 Uporabniške rešitve IT v IT applications in science
znanosti
SIST-TS ISO/TS 19138:2009 en
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
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SIST-TS ISO/TS 19138:2009
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SIST-TS ISO/TS 19138:2009
TECHNICAL ISO/TS
SPECIFICATION 19138
First edition
2006-12-01
Geographic information — Data quality
measures
Information géographique — Mesures de la qualité des données
Reference number
ISO/TS 19138:2006(E)
©
ISO 2006
---------------------- Page: 3 ----------------------
SIST-TS ISO/TS 19138:2009
ISO/TS 19138:2006(E)
PDF disclaimer
This PDF file may contain embedded typefaces. In accordance with Adobe's licensing policy, this file may be printed or viewed but
shall not be edited unless the typefaces which are embedded are licensed to and installed on the computer performing the editing. In
downloading this file, parties accept therein the responsibility of not infringing Adobe's licensing policy. The ISO Central Secretariat
accepts no liability in this area.
Adobe is a trademark of Adobe Systems Incorporated.
Details of the software products used to create this PDF file can be found in the General Info relative to the file; the PDF-creation
parameters were optimized for printing. Every care has been taken to ensure that the file is suitable for use by ISO member bodies. In
the unlikely event that a problem relating to it is found, please inform the Central Secretariat at the address given below.
© ISO 2006
All rights reserved. Unless otherwise specified, no part of this publication may be reproduced or utilized in any form or by any means,
electronic or mechanical, including photocopying and microfilm, without permission in writing from either ISO at the address below or
ISO's member body in the country of the requester.
ISO copyright office
Case postale 56 • CH-1211 Geneva 20
Tel. + 41 22 749 01 11
Fax + 41 22 749 09 47
E-mail copyright@iso.org
Web www.iso.org
Published in Switzerland
ii © ISO 2006 – All rights reserved
---------------------- Page: 4 ----------------------
SIST-TS ISO/TS 19138:2009
ISO/TS 19138:2006(E)
Contents Page
Foreword. iv
Introduction . v
1 Scope .1
2 Conformance.1
3 Normative references .1
4 Terms and definitions .1
5 Relationships to other standards.2
6 Register.3
7 Components of a data quality measure .3
7.1 List of components.3
7.2 Component details.4
7.3 Standardized data quality measures .6
Annex A (normative) Abstract test suite.7
A.1 Test case identifier: Component test.7
A.2 Test case identifier: Name test.7
A.3 Test case identifier: Data quality element and subelement test.7
A.4 Test case identifier: Data quality basic measure test.8
A.5 Test case identifier: Definition test.8
A.6 Test case identifier: Description test.8
A.7 Test case identifier: Parameter test.8
A.8 Test case identifier: Data quality value type test .8
A.9 Test case identifier: Source reference test .9
A.10 Test case identifier: Example test.9
Annex B (normative) Structure of data quality measures.10
B.1 Components defining a data quality measure.10
B.2 Mapping of the components to ISO 19115 and ISO 19135 .11
B.3 UML-diagram for data quality measure .11
Annex C (normative) Data quality basic measures .14
C.1 Purpose of data quality basic measures.14
C.2 Counting-related data quality basic measures.14
C.3 Uncertainty-related data quality basic measures.15
Annex D (normative) List of data quality measures .19
D.1 Completeness .19
D.2 Logical consistency .23
D.3 Positional accuracy .37
D.4 Temporal accuracy .58
D.5 Thematic accuracy.61
Bibliography .68
© ISO 2006 – All rights reserved iii
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SIST-TS ISO/TS 19138:2009
ISO/TS 19138:2006(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.
International Standards are drafted in accordance with the rules given in the ISO/IEC Directives, Part 2.
The main task of technical committees is to prepare International Standards. Draft International Standards
adopted by the technical committees are circulated to the member bodies for voting. Publication as an
International Standard requires approval by at least 75 % of the member bodies casting a vote.
In other circumstances, particularly when there is an urgent market requirement for such documents, a
technical committee may decide to publish other types of normative document:
⎯ an ISO Publicly Available Specification (ISO/PAS) represents an agreement between technical experts in
an ISO working group and is accepted for publication if it is approved by more than 50 % of the members
of the parent committee casting a vote;
⎯ an ISO Technical Specification (ISO/TS) represents an agreement between the members of a technical
committee and is accepted for publication if it is approved by 2/3 of the members of the committee casting
a vote.
An ISO/PAS or ISO/TS is reviewed after three years in order to decide whether it will be confirmed for a
further three years, revised to become an International Standard, or withdrawn. If the ISO/PAS or ISO/TS is
confirmed, it is reviewed again after a further three years, at which time it must either be transformed into an
International Standard or be withdrawn.
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.
ISO/TS 19138 was prepared by Technical Committee ISO/TC 211, Geographic information/Geomatics.
iv © ISO 2006 – All rights reserved
---------------------- Page: 6 ----------------------
SIST-TS ISO/TS 19138:2009
ISO/TS 19138:2006(E)
Introduction
Knowledge of the quality of geographic data is often crucial for the application of the data, as different users
and different applications often have different data quality requirements. A user of geographic data may have
multiple datasets from which to choose. Therefore, it is necessary to compare the quality of the datasets to
determine which best fulfils the requirements of the user. To facilitate such 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.
Data quality needs to be reported by the producer and evaluated by the user against his or her requirements
for different criteria and data quality measures. It is essential that reported quality for a dataset contains the
quality measurements that may be of interest to a potential user of the dataset, and that the metrics used to
determine the quality are reported and available to the user.
ISO 19113 establishes the principles for the description of geographic data quality and specifies components
for reporting quality information. Procedures for the evaluation of geographic data quality are described in
ISO 19114.
The objective of this Technical Specification is to guide the producer in choosing the right data quality
measures for data quality reporting, and the user in the evaluation of the usefulness of a dataset by
standardizing the components and structures of data quality measures and by defining commonly used data
quality measures.
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TECHNICAL SPECIFICATION ISO/TS 19138:2006(E)
Geographic information — Data quality measures
1 Scope
This Technical Specification defines a set of data quality measures. These can be used when reporting data
quality for the data quality subelements identified in ISO 19113. Multiple measures are defined for each data
quality subelement, and the choice of which to use will depend on the type of data and its intended purpose.
The data quality measures are structured so that they can be maintained in a register established in
conformance with ISO 19135.
This Technical Specification does not attempt to describe every possible data quality measure, only a set of
commonly used ones.
2 Conformance
Any set of data quality measures claiming conformance with this Technical Specification shall pass all of the
conditions specified in the abstract test suite (Annex A).
3 Normative references
The following referenced documents are indispensable for the application of this document. 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 19113:2002, Geographic information — Quality principles
ISO 19115:2003, Geographic information — Metadata
ISO 19135:2005, Geographic information — Procedures for item registration
4 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
4.1
correctness
correspondence with the universe of discourse
4.2
data quality basic measure
generic data quality measure used as a basis for the creation of specific data quality measures
NOTE Data quality basic measures are abstract data types. They cannot be used directly when reporting data
quality.
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4.3
data quality scope
extent or characteristic(s) of the data for which quality information is reported
[ISO 19113]
NOTE A data quality scope for a dataset can comprise a dataset series to which the dataset belongs, the dataset
itself, or a smaller grouping of data located physically within the dataset sharing common characteristics. Common
characteristics can be an identified feature type, feature attribute, or feature relationship; data collection criteria; original
source; or a specified geographic or temporal extent.
4.4
error
discrepancy with the universe of discourse
4.5
measurand
particular quantity subject to measurement
[International Vocabulary of Basic and General Terms in Metrology (VIM)]
4.6
universe of discourse
view of the real or hypothetical world that includes everything of interest
[ISO 19101]
5 Relationships to other standards
ISO 19113 describes relevant data quality elements and their corresponding data quality subelements and it
indicates how quality should be reported. ISO 19114 describes procedures for the evaluation of quantitative
quality. ISO 19115 contains elements and classes for data quality reporting within the UML models and data
dictionaries.
ISO 19113 specifies a set of descriptors for a data quality subelement, for use in recording data quality. One
of these descriptors is the data quality measure. A data quality measure is described by the components listed
in 7.1.
Table 1 provides a list of data quality elements and data quality subelements as defined in ISO 19113.
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Table 1 — Data quality elements and data quality subelements with definitions (ISO 19113)
Data quality element Data quality subelement Definition
completeness commission excess data present in a dataset
omission data absent from a dataset
logical consistency conceptual consistency adherence to rules of the conceptual schema
domain consistency adherence of values to the value domains
format consistency degree to which data is stored in accordance
with the physical structure of the dataset
topological consistency correctness of the explicitly encoded
topological characteristics of a dataset
positional accuracy 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 dataset to their respective relative positions
accepted as or being true
gridded data position accuracy closeness of gridded data position values to
values accepted as or being true
temporal accuracy accuracy of a time measurement correctness of the temporal references of an
item (reporting of error in time measurement)
temporal consistency correctness of ordered events or sequences, if
reported
temporal validity validity of data with respect to time
thematic accuracy classification correctness comparison of the classes assigned to features
or their attributes to a universe of discourse
(e.g. ground truth or reference dataset)
non-quantitative attribute correctness correctness of non-quantitative attribute
quantitative attribute accuracy accuracy of quantitative attributes
6 Register
A register of data quality measures shall contain a set of data quality measures, described using the
components listed in 7.1. The registration procedures shall be performed according to ISO 19135.
Annex D of this Technical Specification contains the list of standardized data quality measures. A register
shall contain these data quality measures and may also contain additional data quality measures submitted
through the procedures defined within ISO 19135. The registration process also allows retiring data quality
measures.
7 Components of a data quality measure
7.1 List of components
Each data quality measure shall be described using the following technical components:
⎯ name (7.2.1)
⎯ alias (7.2.2)
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⎯ data quality element (7.2.3)
⎯ data quality subelement (7.2.4)
⎯ data quality basic measure (7.2.5)
⎯ definition (7.2.6)
⎯ description (7.2.7)
⎯ parameter (7.2.8)
⎯ data quality value type (7.2.9)
⎯ data quality value structure (7.2.10)
⎯ source reference (7.2.11)
⎯ example (7.2.12)
⎯ identifier (7.2.13)
7.2 Component details
7.2.1 Name
Name refers to the name of the data quality measure.
If the data quality measure already has a commonly used name, this name should be used. If no name exists,
a name shall be chosen that reflects the nature of the measure.
NOTE The component name is specified in the base standard for registers, ISO 19135.
7.2.2 Alias
Alias refers to other recognized name for the same data quality measure. It may be a different commonly used
name, or an abbreviation or a short name.
More than one alias may be provided.
7.2.3 Data quality element
Data quality element refers to the name of the data quality element to which this data quality measure applies.
NOTE A list of data quality elements is provided in Table 1.
7.2.4 Data quality subelement
Data quality subelement refers to the name of the data quality subelement to which this data quality measure
applies.
NOTE A list of data quality subelements is provided in Table 1.
7.2.5 Data quality basic measure
Each data quality basic measure is described by its name, definition and value type. Data quality basic
measures are identified by their names.
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A variety of data quality measures are based on counting of erroneous items. There are also several data
quality measures dealing with the uncertainty of numerical values. In order to avoid repetition, all possible
methods of constructing counting-related data quality measures as well as general statistical measures for
one- and two-dimensional random variables shall be defined in terms of data quality basic measures.
The data quality basic measures are defined in Annex C.
If a data quality measure is based on one of the set of data quality basic measures, the name of the data
quality basic measure shall be provided in the field data quality basic measure. If the data quality measure is
not based on a data quality basic measure, it shall be indicated in this field that a data quality basic measure
is not applicable. The data quality basic measures shall also be used as appropriate for creating new data
quality measures, for instance for reporting unclosed surface patches or other application-dependent data
quality measures.
7.2.6 Definition
Definition states the fundamental concept of the data quality measure.
If the data quality measure is derived from a data quality basic measure, the definition is based on the data
quality basic measure definition and specialized for this data quality measure.
NOTE The component definition is specified in the base standard for registers, ISO 19135.
7.2.7 Description
Description refers to the description of the data quality measure including methods of calculation, with all
formulae and/or illustrations needed to establish the result of applying the measure.
If the data quality measure uses the concept of errors, it shall be stated how an item shall be classified as
incorrect.
NOTE The component description is specified in the base standard for registers, ISO 19135.
7.2.8 Parameter
Parameter refers to an auxiliary variable used by the data quality measure. It shall include name, definition
and description.
More than one parameter may be provided.
7.2.9 Data quality value type
Data quality value type refers to the value type for reporting a data quality result.
A data quality value type shall be provided for a data quality result. The data types defined in ISO/TS 19103
shall be used when appropriate.
Table 2 — Examples of data quality value types
Boolean
Real
Integer
Ratio (numerator of type integer : denominator of type integer)
Percentage
Measure(s) [value(s) + unit(s)]
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7.2.10 Data quality value structure
Data quality value structure gives the structure for reporting a complex data quality result.
A data quality result may consist of multiple values. In this case, the data quality result shall be structured
using the data quality value structures as given in Table 3. The structure may consist of homogeneous or
heterogeneous data quality value types. The possible data quality value types are given in 7.2.9.
Table 3 — Data quality value structures
Bag
Set
Sequence
Table
Matrix
Coverage
NOTE The values within a structure can be multiple. For example, the covariance matrix as given in Table D.32 is
reported as matrix of measure, where the matrix elements may have different units of measure. A list may consist of
different data quality value types.
7.2.11 Source reference
Source reference gives the citation of the source of the data quality measure.
When a data quality measure for which additional information is provided in an external source is added to the
list of standardized data quality measures, a reference to that source may be provided here.
NOTE The component source reference is specified in the base standard for registers, ISO 19135.
7.2.12 Example
Example may provide examples of applying the data quality measure or the result obtained for the data quality
measure.
More than one example may be provided.
7.2.13 Identifier
Identifier consists of an integer number that uniquely identifies a data quality measure.
If data quality measures are administered in a register, then identifiers may only be assigned by the register
manager.
NOTE The component identifier is specified in the base standard for registers, ISO 19135.
7.2.14 Obligation of the above-listed components
Some of the components are mandatory, others are conditional or optional. Table B.1 provides further
information on the obligation of each technical component.
7.3 Standardized data quality measures
In order to make data quality related metadata and data quality reports comparable, standardized data quality
measures shall be used in evaluating and reporting data quality, where appropriate. Annex D gives a list of
commonly used data quality measures with all required components for data quality measures as specified in
this Technical Specification.
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Annex A
(normative)
Abstract test suite
A.1 Test case identifier: Component test
a) Test purpose: to determine conformance by ensuring that all necessary components of a data quality
measure are provided.
b) Test method: examine the entry for the data quality measure and verify that the components have been
provided as required by Table B.1.
c) Reference: 7.2 and Annex B.
d) Test type: Capability.
A.2 Test case identifier: Name test
a) Test purpose: to determine if a distinct name for the data quality measure is used.
b) Test method: determine if the name for the data quality measure is distinct from other measures with
different concepts, and if the name is not in conflict with other data quality basic measures, their
definitions and descriptions.
c) Reference: 7.2.1.
d) Test type: Capability.
A.3 Test case identifier: Data quality element and subelement test
a) Test purpose: to determine
⎯ if data quality element and subelement are assigned;
⎯ if they are taken from the list of data quality elements and subelements in ISO 19113 or if they are an
additional data quality element and subelement created in conformance with the rules of ISO 19113;
⎯ if the data quality measure is relevant for the given data quality element and subelement.
b) Test method: check if proper values are assigned to the data quality element and subelement
components and if the data quality measure has bearing on these.
c) Reference: 7.2.3 and 7.2.4.
d) Test type: Capability.
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A.4 Test case identifier: Data quality basic measure test
a) Test purpose: to determine if a data quality measure is properly derived from a data quality basic
measure.
b) Test method: check if an appropriate data quality basic measure for the data quality measure exists and,
if it does, that the data quality measure is utilizing this data quality basic measure in conformance with
this Technical Specification.
c) Reference: 7.2.5.
d) Test type: Capability.
A.5 Test case identifier: Definition test
a) Test purpose: to determine if a fitting, correct and complete definition is provided.
b) Test method: check that the given definition contains no ambiguities and that it is in conformance with
characteristics of a definition as stated in ISO 19135:2005, 7.3.1.
c) Reference: 7.2.6 and ISO 19135:2005, 7.3.1.
d) Test type: Capability.
A.6 Test case identifier: Description test
a) Test purpose: to determine if an exhaustive description is provided.
b) Test method: check if the description contains a comprehensive explanation with all required formulae to
facilitate the application of the data quality measure.
c) Reference: 7.2.7.
d) Test type: Capability.
A.7 Test case identifier: Parameter test
a) Test purpose: to determine if required parameters are provided.
b) Test method: check if all parameters occurring in the description are provided in the parameter
component.
c) Reference: 7.2.8.
d) Test type: Capability.
A.8 Test case identifier: Data quality value type test
a) Test purpose: to determine if a proper data quality value type is provided.
b) Test method: check if the provided data quality value type is included in the list in Table 3.
c) Reference: 7.2.9.
d) Test type: Capability.
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A.9 Test case identifier: Source reference test
a) Test purpose: to determine if a proper source reference is provided.
b) Test method: check if the cited reference source exists and if it reflects the concept of the provided data
quality measure.
c) Reference: 7.2.11.
d) Test type: Capability.
A.10 Test case identifier: Example test
a) Test purpose: to determine if the example, if provided, is a valid example for the data quality measure.
b) Test method: check if the example is free of errors and if it is representative of the usage of the data
quality measure.
c) Reference: 7.2.12.
d) Test type: Capability.
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