SIST ISO 19113:2003
(Main)Geographic information -- Quality principles
Geographic information -- Quality principles
ISO 19113:2002 establishes the principles for describing the quality of geographic data and specifies components for reporting quality information. It also provides an approach to organizing information about data quality.
ISO 19113:2002 is applicable to data producers providing quality information to describe and assess how well a dataset meets its mapping of the universe of discourse as specified in the product specification, formal or implied, and to data users attempting to determine whether or not specific geographic data is of sufficient quality for their particular application. This International Standard should be considered by organizations involved in data acquisition and purchase, in such a way that it makes it possible to fulfil the intentions of the product specification. It can additionally be used for defining application schemas and describing quality requirements.
As well as being applicable to digital geographic data, the principles of ISO 19113:2002 can be extended to identify, collect and report the quality information for a geographic dataset, its principles can be extended and used to identify, collect and report quality information for a dataset series or smaller groupings of data that are a subset of a dataset.
Although ISO 19113:2002 is applicable to digital geographic data, its principles can be extended to many other forms of geographic data such as maps, charts and textual documents.
ISO 19113:2002 does not attempt to define a minimum acceptable level of quality for geographic data.
Information géographique -- Principes qualité
Geografske informacije – Načela kakovosti
General Information
Relations
Standards Content (Sample)
INTERNATIONAL ISO
STANDARD 19113
First edition
2002-12-01
Geographic information — Quality
principles
Information géographique — Principes qualité
Reference number
ISO 19113:2002(E)
©
ISO 2002
---------------------- Page: 1 ----------------------
ISO 19113:2002(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 2002
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 2002 — All rights reserved
---------------------- Page: 2 ----------------------
ISO 19113:2002(E)
Contents Page
Foreword. iv
Introduction . v
1 Scope. 1
2 Conformance . 1
3 Normative references . 1
4 Terms and definitions. 2
5 Principles for describing the quality of geographic data . 4
5.1 Components of data quality description . 4
5.2 Data quality elements and data quality subelements . 5
5.3 Data quality overview elements. 7
6 Identifying the quality of geographic information . 8
6.1 Identifying quantitative quality information . 8
6.2 Identifying non-quantitative quality information . 10
7 Reporting quality information. 10
7.1 Reporting quantitative quality information .10
7.2 Reporting non-quantitative quality information . 10
Annex A (normative) Abstract test suite. 11
Annex B (informative) Data quality concepts and their use. 14
Annex C (informative) Data quality elements, data quality subelements and data quality overview
elements. 19
© ISO 2002 — All rights reserved iii
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ISO 19113:2002(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.
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 19113 was prepared by Technical Committee ISO/TC 211, Geographic information/Geomatics.
iv © ISO 2002 — All rights reserved
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ISO 19113:2002(E)
Introduction
Geographic datasets are increasingly being shared, interchanged and used for purposes other than their
producers’ intended ones. Information about the quality of available geographic datasets is vital to the process
of selecting a dataset in that the value of data is directly related to its quality. Data users confront situations
requiring different levels of data quality. Extremely accurate data is required by some data users for certain
needs and less accurate data are sufficient for other needs. Information about the quality of geographic data is
becoming a decisive factor for its utilization as technological advances allow the collection and use of
geographic datasets whose quality can exceed that which is needed and requested by data users.
The purpose of describing the quality of geographic data is to facilitate the selection of the geographic dataset
best suited to application needs or requirements. Complete descriptions of the quality of a dataset will
encourage the sharing, interchange and use of appropriate geographic datasets. A geographic dataset can be
viewed as a commodity or product. Information on the quality of geographic data allows a data producer or
vendor to validate how well a dataset meets the criteria set forth in its product specification and assists a data
user in determining a product’s ability to satisfy the requirements for their particular application.
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.
© ISO 2002 — All rights reserved v
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INTERNATIONAL STANDARD ISO 19113:2002(E)
Geographic information — Quality principles
1 Scope
This International Standard establishes the principles for describing the quality of geographic data and
specifies components for reporting quality information. It also provides an approach to organizing information
about data quality.
This International Standard is applicable to data producers providing quality information to describe and
assess how well a dataset meets its mapping of the universe of discourse as specified in the product
specification, formal or implied, and to data users attempting to determine whether or not specific geographic
data is of sufficient quality for their particular application. This International Standard should be considered by
organizations involved in data acquisition and purchase, in such a way that it makes it possible to fulfil the
intentions of the product specification. It can additionally be used for defining application schemas and
describing quality requirements.
As well as being applicable to digital geographic data, the principles of this International Standard can be
extended to identify, collect and report the quality information for a geographic dataset, its principles can be
extended and used to identify, collect and report quality information for a dataset series or smaller groupings
of data that are a subset of a dataset.
Although this International Standard is applicable to digital geographic data, its principles can be extended to
many other forms of geographic data such as maps, charts and textual documents.
This International Standard does not attempt to define a minimum acceptable level of quality for geographic
data.
2 Conformance
Any product claiming conformance with this International Standard shall pass all the requirements described
in the abstract test suite presented in 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 19108:2002, Geographic information — Temporal schema
1)
ISO 19109:— , Geographic information — Rules for application schema
1)
ISO 19114:— , Geographic information — Quality evaluation procedures
1)
ISO 19115:— , Geographic information — Metadata
1) To be published.
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ISO 19113:2002(E)
4 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
4.1
accuracy
closeness of agreement between a test result and the accepted reference value [ISO 3534-1]
NOTE A test result can be observations or measurements.
4.2
conformance
fulfilment of specified requirements [ISO 19105]
4.3
conformance quality level
threshold value or set of threshold values for data quality results used to determine how well a dataset meets
the criteria set forth in its product specification or user requirements [ISO 19114]
4.4
data quality date
date or range of dates on which a data quality measure is applied
4.5
data quality element
quantitative component documenting the quality of a dataset [ISO 19101]
NOTE The applicability of a data quality element to a dataset depends on both the dataset’s content and its product
specification, the result being that all data quality elements may not be applicable to all datasets.
4.6
data quality evaluation procedure
operation(s) used in applying and reporting quality evaluation methods and their results
4.7
data quality measure
evaluation of a data quality subelement
EXAMPLE The percentage of the values of an attribute that are correct.
4.8
data quality overview element
non-quantitative component documenting the quality of a dataset [ISO 19101]
NOTE Information about the purpose, usage and lineage of a dataset is non-quantitative quality information.
4.9
data quality result
value or set of values resulting from applying a data quality measure or the outcome of evaluating the
obtained value or set of values against a specified conformance quality level
EXAMPLE A data quality result of “90” with a data quality value type of “percentage” reported for the data quality
element and its data quality subelement “completeness, commission” is an example of a value resulting from applying a
data quality measure to the data specified by a data quality scope. A data quality result of “true” with a data quality value
type of “boolean variable” is an example of comparing the value (90) against a specified acceptable conformance quality
level (85) and reporting an evaluation of a kind, pass or fail.
4.10
data quality scope
extent or characteristic(s) of the data for which quality information is reported
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ISO 19113:2002(E)
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.
4.11
data quality subelement
component of a data quality element describing a certain aspect of that data quality element
4.12
data quality value type
value type for reporting a data quality result
EXAMPLE “boolean variable”, “percentage”, “ratio”
NOTE A data quality value type is always provided for a data quality result.
4.13
data quality value unit
value unit for reporting a data quality result
EXAMPLE “metre”
NOTE A data quality value unit is provided only when applicable for a data quality result.
4.14
dataset
identifiable collection of data [ISO 19115]
NOTE A dataset may be a smaller grouping of data which, though limited by some constraint such as spatial extent
or feature type, is located physically within a larger dataset. Theoretically, a dataset may be as small as a single feature or
feature attribute contained within a larger dataset.
4.15
dataset series
collection of datasets sharing the same product specification [ISO 19115]
4.16
feature
abstraction of real world phenomena [ISO 19101]
NOTE A feature may occur as a type or an instance. Feature type or feature instance should be used when only one
is meant.
4.17
feature attribute
characteristic of a feature [ISO 19101]
NOTE A feature attribute has a name, a data type and a value domain associated with it. A feature attribute for a
feature instance also has an attribute value taken from the value domain.
4.18
feature operation
operation that every instance of a feature type may perform [ISO 19110]
EXAMPLE 1 An operation upon the feature type “dam” is to raise the dam. The result of this operation is to raise the
level of water in a reservoir.
EXAMPLE 2 An operation by the feature type “dam” might be to block vessels from navigating along a watercourse.
NOTE Feature operations provide a basis for feature type definitions.
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ISO 19113:2002(E)
4.19
metadata
data about data [ISO 19115]
4.20
product specification
description of the universe of discourse and a specification for mapping the universe of discourse to a dataset
4.21
quality
totality of characteristics of a product that bear on its ability to satisfy stated and implied needs [ISO 19101]
4.22
universe of discourse
view of the real or hypothetical world that includes everything of interest [ISO 19101]
5 Principles for describing the quality of geographic data
5.1 Components of data quality description
This International Standard can be used when
identifying and reporting quality information;
evaluating the quality of a dataset;
developing product specifications and user requirements;
specifying application schemas.
ISO 19114 and ISO 19115 describe schemas for reporting quality information.
ISO 19114 provides the framework for evaluating the quality of a dataset.
ISO 19109 describes the development of application schemas.
A quality description can be applied to a dataset series, a dataset or a smaller grouping of data located
physically within the dataset sharing common characteristics so that its quality can be evaluated.
The quality of a dataset shall be described using two components:
data quality elements;
data quality overview elements.
Data quality elements, together with data quality subelements and the descriptors of a data quality
subelement, describe how well a dataset meets the criteria set forth in its product specification and provide
quantitative quality information.
Data quality overview elements provide general, non-quantitative information.
NOTE Data quality overview elements are critical for assessing the quality of a dataset for a particular application
that differs from the intended application.
This International Standard recognizes that quantitative and non-quantitative quality information may have
associated quality.
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ISO 19113:2002(E)
The quality about quality information may include a measure of the confidence or the reliability of the quality
information. This type of information is recorded in ISO 19114’s quality evaluation report.
Figure 1 provides an overview of data quality information.
Annex B provides a discussion of data quality concepts used to establish the components for describing the
quality of geographic data.
Figure 1 — An overview of data quality information
5.2 Data quality elements and data quality subelements
5.2.1 Data quality elements
The following data quality elements, where applicable, shall be used to describe how well a dataset meets the
criteria set forth in its product specification:
completeness: presence and absence of features, their attributes and relationships;
logical consistency: degree of adherence to logical rules of data structure, attribution and relationships
(data structure can be conceptual, logical or physical);
positional accuracy: accuracy of the position of features;
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ISO 19113:2002(E)
temporal accuracy: accuracy of the temporal attributes and temporal relationships of features;
thematic accuracy: accuracy of quantitative attributes and the correctness of non-quantitative attributes
and of the classifications of features and their relationships.
Additional data quality elements may be created to describe a component of the quantitative quality of a
dataset not addressed in this International Standard.
5.2.2 Data quality subelements
For the data quality elements identified in 5.2.1, the following data quality subelements where applicable shall
be used to describe aspects of the quantitative quality of a dataset:
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 attributes,
quantitative attribute accuracy: accuracy of quantitative attributes.
Additional data quality subelements may be created for any of the data quality elements.
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ISO 19113:2002(E)
5.2.3 Descriptors of a data quality subelement
Quality information shall be recorded for each applicable data quality subelement. The mechanism for
completely recording information for a data quality subelement shall be the use of the seven descriptors of a
data quality subelement:
data quality scope;
data quality measure;
data quality evaluation procedure;
data quality result;
data quality value type;
data quality value unit;
data quality date.
NOTE The descriptors of a data quality subelement are defined in Clause 4.
5.3 Data quality overview elements
The following data quality overview elements where applicable shall be used to describe the non-quantitative
quality of a dataset:
purpose;
usage;
lineage.
Purpose shall describe the rationale for creating a dataset and contain information about its intended use.
NOTE A dataset’s intended use is not necessarily the same as its actual use. Actual use is described using the data
quality overview element usage.
Usage shall describe the application(s) for which a dataset has been used. Usage describes uses of the
dataset by the data producer or by other, distinct, data users.
Lineage shall describe the history of a dataset and, in as much as is known, recount the life cycle of a dataset
from collection and acquisition through compilation and derivation to its current form.
Lineage may contain two unique components:
source information shall describe the parentage of a dataset;
process step or history information shall describe a record of events or transformations in the life of a
dataset, including the process used to maintain the dataset whether continuous or periodic, and the lead
time.
Additional data quality overview element(s) shall describe an area of non-quantitative quality of a dataset not
addressed in this International Standard.
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ISO 19113:2002(E)
6 Identifying the quality of geographic information
6.1 Identifying quantitative quality information
6.1.1 General
Clause 6.1 describe the general process for identifying quantitative quality information. Some of the
subclauses may not be relevant in all cases.
6.1.2 Identifying applicable data quality elements
All data quality elements applicable to a dataset shall be identified. Some data quality elements may not be
applicable for a particular type of dataset.
NOTE 1 Applicability of a data quality element should be determined by reference to a dataset’s product specification.
EXAMPLE A dataset whose spatial references are postal references only will not have a data quality element of
positional accuracy.
NOTE 2 Annex C contains examples of identifying applicable data quality elements.
6.1.3 Creating additional data quality elements
New data quality element(s) may be named and defined if the data quality elements listed in this International
Standard do not sufficiently address a component of quality. The name and definition of an additional data
quality element shall be included as a part of a dataset’s quality information.
6.1.4 Identifying applicable data quality subelements
All applicable data quality subelements for each applicable data quality element shall be identified (at least
one data quality subelement shall be identified as applicable for each applicable data quality element). Some
of an applicable data quality element’s data quality subelements may not be applicable to a particular type of
dataset.
NOTE 1 Applicability of a data quality subelement should be determined by reference to a dataset’s product
specification.
NOTE 2 Annex C contains examples of identifying applicable data quality subelements.
6.1.5 Creating additional data quality subelements
New data quality subelement(s) may be named and defined if the data quality subelements listed in this
International Standard do not sufficiently address an aspect of quality. The name and definition of an
additional data quality subelement shall be included as a part of a dataset’s quality information.
6.1.6 Using the descriptors of a data quality subelement
6.1.6.1 Data quality scope
At least one data quality scope shall be identified for each applicable data quality subelement. A data quality
scope may be a dataset series to which a dataset belongs, the dataset or a smaller grouping of data located
physically within the dataset sharing common characteristics. If a data quality scope cannot be identified, the
data quality scope shall be the dataset.
NOTE Data quality scope(s) should be determined by reference to a dataset’s product specification and the
non-quantitative quality information provided for data quality overview elements.
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ISO 19113:2002(E)
Quality can vary within a dataset. Multiple data quality scopes may be identified for each applicable data
quality subelement to more completely describe quantitative quality information. A data quality scope shall be
adequately described. The following can be used to describe a data quality scope:
the level (a dataset series to which a dataset belongs, the dataset or a smaller grouping of data located
physically within the dataset sharing common characteristics);
the types of items (lists of feature types, feature attributes and feature relationships) or specific items (lists
of feature instances, attribute values and instances of feature relationships);
the geographic extent;
the temporal extent (the time frame of reference and accuracy of the time frame).
6.1.6.2 Data quality measure
One data quality measure shall be provided for each data quality scope. A data quality measure shall briefly
describe and name, where a name exists, the type of test being applied to the data specified by a data quality
scope and shall include bounding or limiting parameters.
NOTE 1 Examples of bounding or limiting parameters are confidence intervals and error rates.
This International Standard recognizes that the quality of a dataset is measured using a variety of tests. 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 dataset. A combination of data
quality measures can give useful information. Multiple data quality measures may be provided for the data
specified by a data quality scope.
NOTE 2 ISO 19114 includes examples of names and descriptions of types of data quality measures.
6.1.6.3 Data quality evaluation procedure
One data quality evaluation procedure shall be provided for each data quality measure. A data quality
evaluation procedure shall describe, or reference documentation describing, the methodology used to apply a
data quality measure to the data specified by a data quality scope and shall include the reporting of the
methodology.
NOTE 1 Examples of documentation are published articles or accepted industry standards.
NOTE 2 ISO 19114 includes a data quality evaluation procedure framework applicable to datasets and further clarifies
the type of information to be reported in a data quality evaluation procedure.
6.1.6.4 Data quality result
One data quality result shall be provided for each data quality measure. The data quality result shall be either
the value or set of values obtained from applying a data quality measure to the data specified by a data
quality scope, or
the outcome of evaluating the value or set of values obtained from applying a data quality measure to the
data specified by a data quality scope against a specified acceptable conformance quality level. This type
of data quality result is referred to in this International Standard as pass-fail.
Both types of data quality results identified in this International Standard may be provided.
NOTE ISO 19114 addresses the determination of conformance quality levels.
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ISO 19113:2002(E)
6.1.6.5 Data quality value type
One data quality value type shall be provided for each data quality result.
NOTE The data quality value type for pass-fail is “boolean variable”.
6.1.6.6 Data quality value unit
One data quality value unit, if applicable, shall be provided for each data quality result.
6.1.6.7 Data quality date
One data quality date shall be provided for each data quality measure in conformance with the requirements
of ISO 19108’s temporal schema.
6.2 Identifying non-quantitative quality information
6.2.1 Identifying applicable data quality overview elements
Purpose of a dataset shall always be applicable.
All usage of a dataset that the producer is aware of shall be applicable.
Lineage of a dataset shall always be applicable. In extreme cases, informatio
...
SLOVENSKI STANDARD
SIST ISO 19113:2003
01-november-2003
*HRJUDIVNHLQIRUPDFLMH±1DþHODNDNRYRVWL
Geographic information -- Quality principles
Information géographique -- Principes qualité
Ta slovenski standard je istoveten z: ISO 19113:2002
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
SIST ISO 19113:2003 en
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
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SIST ISO 19113:2003
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SIST ISO 19113:2003
INTERNATIONAL ISO
STANDARD 19113
First edition
2002-12-01
Geographic information — Quality
principles
Information géographique — Principes qualité
Reference number
ISO 19113:2002(E)
©
ISO 2002
---------------------- Page: 3 ----------------------
SIST ISO 19113:2003
ISO 19113:2002(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 2002
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 2002 — All rights reserved
---------------------- Page: 4 ----------------------
SIST ISO 19113:2003
ISO 19113:2002(E)
Contents Page
Foreword. iv
Introduction . v
1 Scope. 1
2 Conformance . 1
3 Normative references . 1
4 Terms and definitions. 2
5 Principles for describing the quality of geographic data . 4
5.1 Components of data quality description . 4
5.2 Data quality elements and data quality subelements . 5
5.3 Data quality overview elements. 7
6 Identifying the quality of geographic information . 8
6.1 Identifying quantitative quality information . 8
6.2 Identifying non-quantitative quality information . 10
7 Reporting quality information. 10
7.1 Reporting quantitative quality information .10
7.2 Reporting non-quantitative quality information . 10
Annex A (normative) Abstract test suite. 11
Annex B (informative) Data quality concepts and their use. 14
Annex C (informative) Data quality elements, data quality subelements and data quality overview
elements. 19
© ISO 2002 — All rights reserved iii
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SIST ISO 19113:2003
ISO 19113:2002(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.
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 19113 was prepared by Technical Committee ISO/TC 211, Geographic information/Geomatics.
iv © ISO 2002 — All rights reserved
---------------------- Page: 6 ----------------------
SIST ISO 19113:2003
ISO 19113:2002(E)
Introduction
Geographic datasets are increasingly being shared, interchanged and used for purposes other than their
producers’ intended ones. Information about the quality of available geographic datasets is vital to the process
of selecting a dataset in that the value of data is directly related to its quality. Data users confront situations
requiring different levels of data quality. Extremely accurate data is required by some data users for certain
needs and less accurate data are sufficient for other needs. Information about the quality of geographic data is
becoming a decisive factor for its utilization as technological advances allow the collection and use of
geographic datasets whose quality can exceed that which is needed and requested by data users.
The purpose of describing the quality of geographic data is to facilitate the selection of the geographic dataset
best suited to application needs or requirements. Complete descriptions of the quality of a dataset will
encourage the sharing, interchange and use of appropriate geographic datasets. A geographic dataset can be
viewed as a commodity or product. Information on the quality of geographic data allows a data producer or
vendor to validate how well a dataset meets the criteria set forth in its product specification and assists a data
user in determining a product’s ability to satisfy the requirements for their particular application.
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.
© ISO 2002 — All rights reserved v
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SIST ISO 19113:2003
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SIST ISO 19113:2003
INTERNATIONAL STANDARD ISO 19113:2002(E)
Geographic information — Quality principles
1 Scope
This International Standard establishes the principles for describing the quality of geographic data and
specifies components for reporting quality information. It also provides an approach to organizing information
about data quality.
This International Standard is applicable to data producers providing quality information to describe and
assess how well a dataset meets its mapping of the universe of discourse as specified in the product
specification, formal or implied, and to data users attempting to determine whether or not specific geographic
data is of sufficient quality for their particular application. This International Standard should be considered by
organizations involved in data acquisition and purchase, in such a way that it makes it possible to fulfil the
intentions of the product specification. It can additionally be used for defining application schemas and
describing quality requirements.
As well as being applicable to digital geographic data, the principles of this International Standard can be
extended to identify, collect and report the quality information for a geographic dataset, its principles can be
extended and used to identify, collect and report quality information for a dataset series or smaller groupings
of data that are a subset of a dataset.
Although this International Standard is applicable to digital geographic data, its principles can be extended to
many other forms of geographic data such as maps, charts and textual documents.
This International Standard does not attempt to define a minimum acceptable level of quality for geographic
data.
2 Conformance
Any product claiming conformance with this International Standard shall pass all the requirements described
in the abstract test suite presented in 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 19108:2002, Geographic information — Temporal schema
1)
ISO 19109:— , Geographic information — Rules for application schema
1)
ISO 19114:— , Geographic information — Quality evaluation procedures
1)
ISO 19115:— , Geographic information — Metadata
1) To be published.
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4 Terms and definitions
For the purposes of this document, the following terms and definitions apply.
4.1
accuracy
closeness of agreement between a test result and the accepted reference value [ISO 3534-1]
NOTE A test result can be observations or measurements.
4.2
conformance
fulfilment of specified requirements [ISO 19105]
4.3
conformance quality level
threshold value or set of threshold values for data quality results used to determine how well a dataset meets
the criteria set forth in its product specification or user requirements [ISO 19114]
4.4
data quality date
date or range of dates on which a data quality measure is applied
4.5
data quality element
quantitative component documenting the quality of a dataset [ISO 19101]
NOTE The applicability of a data quality element to a dataset depends on both the dataset’s content and its product
specification, the result being that all data quality elements may not be applicable to all datasets.
4.6
data quality evaluation procedure
operation(s) used in applying and reporting quality evaluation methods and their results
4.7
data quality measure
evaluation of a data quality subelement
EXAMPLE The percentage of the values of an attribute that are correct.
4.8
data quality overview element
non-quantitative component documenting the quality of a dataset [ISO 19101]
NOTE Information about the purpose, usage and lineage of a dataset is non-quantitative quality information.
4.9
data quality result
value or set of values resulting from applying a data quality measure or the outcome of evaluating the
obtained value or set of values against a specified conformance quality level
EXAMPLE A data quality result of “90” with a data quality value type of “percentage” reported for the data quality
element and its data quality subelement “completeness, commission” is an example of a value resulting from applying a
data quality measure to the data specified by a data quality scope. A data quality result of “true” with a data quality value
type of “boolean variable” is an example of comparing the value (90) against a specified acceptable conformance quality
level (85) and reporting an evaluation of a kind, pass or fail.
4.10
data quality scope
extent or characteristic(s) of the data for which quality information is reported
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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.
4.11
data quality subelement
component of a data quality element describing a certain aspect of that data quality element
4.12
data quality value type
value type for reporting a data quality result
EXAMPLE “boolean variable”, “percentage”, “ratio”
NOTE A data quality value type is always provided for a data quality result.
4.13
data quality value unit
value unit for reporting a data quality result
EXAMPLE “metre”
NOTE A data quality value unit is provided only when applicable for a data quality result.
4.14
dataset
identifiable collection of data [ISO 19115]
NOTE A dataset may be a smaller grouping of data which, though limited by some constraint such as spatial extent
or feature type, is located physically within a larger dataset. Theoretically, a dataset may be as small as a single feature or
feature attribute contained within a larger dataset.
4.15
dataset series
collection of datasets sharing the same product specification [ISO 19115]
4.16
feature
abstraction of real world phenomena [ISO 19101]
NOTE A feature may occur as a type or an instance. Feature type or feature instance should be used when only one
is meant.
4.17
feature attribute
characteristic of a feature [ISO 19101]
NOTE A feature attribute has a name, a data type and a value domain associated with it. A feature attribute for a
feature instance also has an attribute value taken from the value domain.
4.18
feature operation
operation that every instance of a feature type may perform [ISO 19110]
EXAMPLE 1 An operation upon the feature type “dam” is to raise the dam. The result of this operation is to raise the
level of water in a reservoir.
EXAMPLE 2 An operation by the feature type “dam” might be to block vessels from navigating along a watercourse.
NOTE Feature operations provide a basis for feature type definitions.
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4.19
metadata
data about data [ISO 19115]
4.20
product specification
description of the universe of discourse and a specification for mapping the universe of discourse to a dataset
4.21
quality
totality of characteristics of a product that bear on its ability to satisfy stated and implied needs [ISO 19101]
4.22
universe of discourse
view of the real or hypothetical world that includes everything of interest [ISO 19101]
5 Principles for describing the quality of geographic data
5.1 Components of data quality description
This International Standard can be used when
identifying and reporting quality information;
evaluating the quality of a dataset;
developing product specifications and user requirements;
specifying application schemas.
ISO 19114 and ISO 19115 describe schemas for reporting quality information.
ISO 19114 provides the framework for evaluating the quality of a dataset.
ISO 19109 describes the development of application schemas.
A quality description can be applied to a dataset series, a dataset or a smaller grouping of data located
physically within the dataset sharing common characteristics so that its quality can be evaluated.
The quality of a dataset shall be described using two components:
data quality elements;
data quality overview elements.
Data quality elements, together with data quality subelements and the descriptors of a data quality
subelement, describe how well a dataset meets the criteria set forth in its product specification and provide
quantitative quality information.
Data quality overview elements provide general, non-quantitative information.
NOTE Data quality overview elements are critical for assessing the quality of a dataset for a particular application
that differs from the intended application.
This International Standard recognizes that quantitative and non-quantitative quality information may have
associated quality.
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The quality about quality information may include a measure of the confidence or the reliability of the quality
information. This type of information is recorded in ISO 19114’s quality evaluation report.
Figure 1 provides an overview of data quality information.
Annex B provides a discussion of data quality concepts used to establish the components for describing the
quality of geographic data.
Figure 1 — An overview of data quality information
5.2 Data quality elements and data quality subelements
5.2.1 Data quality elements
The following data quality elements, where applicable, shall be used to describe how well a dataset meets the
criteria set forth in its product specification:
completeness: presence and absence of features, their attributes and relationships;
logical consistency: degree of adherence to logical rules of data structure, attribution and relationships
(data structure can be conceptual, logical or physical);
positional accuracy: accuracy of the position of features;
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temporal accuracy: accuracy of the temporal attributes and temporal relationships of features;
thematic accuracy: accuracy of quantitative attributes and the correctness of non-quantitative attributes
and of the classifications of features and their relationships.
Additional data quality elements may be created to describe a component of the quantitative quality of a
dataset not addressed in this International Standard.
5.2.2 Data quality subelements
For the data quality elements identified in 5.2.1, the following data quality subelements where applicable shall
be used to describe aspects of the quantitative quality of a dataset:
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 attributes,
quantitative attribute accuracy: accuracy of quantitative attributes.
Additional data quality subelements may be created for any of the data quality elements.
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5.2.3 Descriptors of a data quality subelement
Quality information shall be recorded for each applicable data quality subelement. The mechanism for
completely recording information for a data quality subelement shall be the use of the seven descriptors of a
data quality subelement:
data quality scope;
data quality measure;
data quality evaluation procedure;
data quality result;
data quality value type;
data quality value unit;
data quality date.
NOTE The descriptors of a data quality subelement are defined in Clause 4.
5.3 Data quality overview elements
The following data quality overview elements where applicable shall be used to describe the non-quantitative
quality of a dataset:
purpose;
usage;
lineage.
Purpose shall describe the rationale for creating a dataset and contain information about its intended use.
NOTE A dataset’s intended use is not necessarily the same as its actual use. Actual use is described using the data
quality overview element usage.
Usage shall describe the application(s) for which a dataset has been used. Usage describes uses of the
dataset by the data producer or by other, distinct, data users.
Lineage shall describe the history of a dataset and, in as much as is known, recount the life cycle of a dataset
from collection and acquisition through compilation and derivation to its current form.
Lineage may contain two unique components:
source information shall describe the parentage of a dataset;
process step or history information shall describe a record of events or transformations in the life of a
dataset, including the process used to maintain the dataset whether continuous or periodic, and the lead
time.
Additional data quality overview element(s) shall describe an area of non-quantitative quality of a dataset not
addressed in this International Standard.
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6 Identifying the quality of geographic information
6.1 Identifying quantitative quality information
6.1.1 General
Clause 6.1 describe the general process for identifying quantitative quality information. Some of the
subclauses may not be relevant in all cases.
6.1.2 Identifying applicable data quality elements
All data quality elements applicable to a dataset shall be identified. Some data quality elements may not be
applicable for a particular type of dataset.
NOTE 1 Applicability of a data quality element should be determined by reference to a dataset’s product specification.
EXAMPLE A dataset whose spatial references are postal references only will not have a data quality element of
positional accuracy.
NOTE 2 Annex C contains examples of identifying applicable data quality elements.
6.1.3 Creating additional data quality elements
New data quality element(s) may be named and defined if the data quality elements listed in this International
Standard do not sufficiently address a component of quality. The name and definition of an additional data
quality element shall be included as a part of a dataset’s quality information.
6.1.4 Identifying applicable data quality subelements
All applicable data quality subelements for each applicable data quality element shall be identified (at least
one data quality subelement shall be identified as applicable for each applicable data quality element). Some
of an applicable data quality element’s data quality subelements may not be applicable to a particular type of
dataset.
NOTE 1 Applicability of a data quality subelement should be determined by reference to a dataset’s product
specification.
NOTE 2 Annex C contains examples of identifying applicable data quality subelements.
6.1.5 Creating additional data quality subelements
New data quality subelement(s) may be named and defined if the data quality subelements listed in this
International Standard do not sufficiently address an aspect of quality. The name and definition of an
additional data quality subelement shall be included as a part of a dataset’s quality information.
6.1.6 Using the descriptors of a data quality subelement
6.1.6.1 Data quality scope
At least one data quality scope shall be identified for each applicable data quality subelement. A data quality
scope may be a dataset series to which a dataset belongs, the dataset or a smaller grouping of data located
physically within the dataset sharing common characteristics. If a data quality scope cannot be identified, the
data quality scope shall be the dataset.
NOTE Data quality scope(s) should be determined by reference to a dataset’s product specification and the
non-quantitative quality information provided for data quality overview elements.
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Quality can vary within a dataset. Multiple data quality scopes may be identified for each applicable data
quality subelement to more completely describe quantitative quality information. A data quality scope shall be
adequately described. The following can be used to describe a data quality scope:
the level (a dataset series to which a dataset belongs, the dataset or a smaller grouping of data located
physically within the dataset sharing common characteristics);
the types of items (lists of feature types, feature attributes and feature relationships) or specific items (lists
of feature instances, attribute values and instances of feature relationships);
the geographic extent;
the temporal extent (the time frame of reference and accuracy of the time frame).
6.1.6.2 Data quality measure
One data quality measure shall be provided for each data quality scope. A data quality measure shall briefly
describe and name, where a name exists, the type of test being applied to the data specified by a data quality
scope and shall include bounding or limiting parameters.
NOTE 1 Examples of bounding or limiting parameters are confidence intervals and error rates.
This International Standard recognizes that the quality of a dataset is measured using a variety of tests. 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 dataset. A combination of data
quality measures can give useful information. Multiple data quality measures may be provided for the data
specified by a data quality scope.
NOTE 2 ISO 19114 includes examples of names and descriptions of types of data quality measures.
6.1.6.3 Data quality evaluation procedure
One data quality evaluation procedure shall be provided for each data quality measure. A data quality
evaluation procedure shall describe, or reference documentation describing, the methodology used to apply a
data quality measure to the data specified by a data quality scope and shall include the reporting of the
methodology.
NOTE 1 Examples of documentation are published articles or accepted industry standards.
NOTE 2 ISO 19114 includes a data quality evaluation procedure framework applicable to datasets and further clarifies
the type of information to be reported in a data quality evaluation procedure.
6.1.6.4 Data quality result
One data quality result shall be provided for each data quality measure. The data quality result shall be either
the value or set of values obtained from applying a data quality measure to the data specified by a data
quality scope, or
the outcome of evaluating the value or set of values obtained from applying a data quality measure to the
data specified by a data quality scope against a specified acceptable conformance quality level. This type
of data quality result
...
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