1、Adopted by INCITS (InterNational Committee for Information Technology Standards) as an American National Standard.Date of ANSI Approval: 12/24/2003Published by American National Standards Institute,25 West 43rd Street, New York, New York 10036Copyright 2003 by Information Technology Industry Council
2、 (ITI).All rights reserved.These materials are subject to copyright claims of International Standardization Organization (ISO), InternationalElectrotechnical Commission (IEC), American National Standards Institute (ANSI), and Information Technology Industry Council(ITI). Not for resale. No part of t
3、his publication may be reproduced in any form, including an electronic retrieval system, withoutthe prior written permission of ITI. All requests pertaining to this standard should be submitted to ITI, 1250 Eye Street NW,Washington, DC 20005.Printed in the United States of AmericaReference numberISO
4、 19114:2003(E)ISO 2003INTERNATIONAL STANDARD ISO19114First edition2003-08-15Geographic information Quality evaluation procedures Information gographique Procdures dvaluation de la qualit ISO 19114:2003(E) PDF disclaimer This PDF file may contain embedded typefaces. In accordance with Adobes licensin
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9、01 11 Fax + 41 22 749 09 47 E-mail copyrightiso.org Web www.iso.org Published in Switzerland ii ISO 2003 All rights reservedISO 19114:2003(E) ISO 2003 All rights reserved iiiContents Page Foreword. v Introduction . vi 1 Scope 1 2 Conformance . 1 3 Normative references . 1 4 Terms and definitions. 1
10、5 Abbreviated terms. 2 6 Process for evaluating data quality 3 6.1 General. 3 6.2 Components of the process. 3 7 Data quality evaluation methods. 4 7.1 Classification of data quality evaluation methods 4 7.2 Direct evaluation methods . 5 7.3 Indirect evaluation method 6 7.4 Data quality evaluation e
11、xamples . 7 8 Reporting data quality evaluation information 7 8.1 Reporting as metadata . 7 8.2 Reporting in a quality evaluation report . 7 8.3 Reporting aggregated data quality result. 7 Annex A (normative) Abstract test suites 8 A.1 Introduction . 8 A.2 Quality evaluation procedures 8 A.3 Evaluat
12、ing data quality. 8 A.4 Reporting data quality 8 Annex B (informative) Uses of quality evaluation procedures 9 B.1 Introduction . 9 B.2 Development of a product specification or user requirements . 9 B.3 Quality control during dataset creation 9 B.4 Inspection for conformance to a product specificat
13、ion 9 B.5 Evaluation of dataset conformance to user requirements . 9 B.6 Quality control during dataset update 9 Annex C (informative) Applying quality evaluation procedures to dynamic datasets 10 C.1 Introduction . 10 C.2 Determining and reporting the quality of a dynamic dataset. 10 C.3 Establishi
14、ng continuous quality evaluation procedures 10 C.4 Periodically re-establish the reference quality of the dataset 11 Annex D (informative) Examples of data quality measures . 12 D.1 Introduction . 12 D.2 Relationship of the data quality components 12 D.3 Examples of data quality completeness measure
15、s. 14 D.4 Examples of data quality logical consistency measures 15 D.5 Examples of data quality positional accuracy measures . 19 D.6 Examples of data quality temporal accuracy measures . 23 D.7 Examples of data quality thematic accuracy measures . 26 Annex E (informative) Guidelines for sampling me
16、thods applied to geographic datasets 30 ISO 19114:2003(E) iv ISO 2003 All rights reservedE.1 Introduction30 E.2 Lot and item .30 E.3 Sample size 30 E.4 Sampling strategies 31 E.5 Probability-based sampling .34 Annex F (informative) Example of testing for thematic accuracy and completeness .36 F.1 In
17、troduction36 F.2 Quality evaluation process.36 F.3 Method for data quality evaluation36 F.4 Inspection for quality 37 F.5 Determination of data quality results and conformance.38 F.6 Reporting quality results 39 Annex G (informative) Example of measurement and reporting of completeness and thematic
18、accuracy .42 G.1 Introduction42 G.2 Dataset description .42 G.3 Evaluation of data quality.47 G.4 Reporting quality results 50 Annex H (informative) Example of an aggregated data quality result.53 H.1 Introduction53 H.2 Dataset description .53 H.3 Universe of discourse.54 H.4 Dataset55 H.5 Aggregati
19、on of evaluation results and reporting.55 Annex I (normative) Reporting quality information in a quality evaluation report 57 I.1 Introduction57 I.2 Quality evaluation report components57 Annex J (informative) Aggregation of data quality results.61 J.1 Introduction61 J.2 100 % pass/fail.61 J.3 Weigh
20、ted pass/fail.61 J.4 Subset of results sufficient for product purpose.62 J.5 Maximum/minimum value.62 Bibliography63 ISO 19114:2003(E) ISO 2003 All rights reserved vForeword ISO (the International Organization for Standardization) is a worldwide federation of national standards bodies (ISO member bo
21、dies). 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 an
22、d 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,
23、 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 cas
24、ting 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 19114 was prepared by Technical Committee ISO/TC 211, Geographic information/Geomati
25、cs. ISO 19114:2003(E) vi ISO 2003 All rights reservedIntroduction For the purpose of evaluating the quality of a dataset, clearly defined procedures must be used in a consistent manner. This enables data producers to express how well their product meets the criteria set forth in its product specific
26、ation and enables data users to establish the extent to which a dataset meets their requirements. The quality of a dataset is described using two components: a quantitative component and a non-quantitative component. The objective of this International Standard is to provide guidelines for evaluatio
27、n procedures of quantitative quality information for geographic data in accordance with the quality principles described in ISO 19113. It also offers guidance on reporting quality information. This International Standard recognizes that a data producer and a data user may view data quality from diff
28、erent perspectives. Conformance quality levels can be set using the data producers product specification or a data users data quality requirements. If the data user requires more data quality information than that provided by the data producer, the data user may follow the data producers data qualit
29、y evaluation process flow to get the additional information. In this case, the data user requirements are treated as a product specification for the purpose of using the data producer process flow. The quality evaluation procedures described in this International Standard, when applied in accordance
30、 with ISO 19113, provide a consistent and standard manner to determine and report the quality information in a dataset. INTERNATIONAL STANDARD ISO 19114:2003(E) ISO 2003 All rights reserved 1Geographic information Quality evaluation procedures 1 Scope This International Standard provides a framework
31、 of procedures for determining and evaluating quality that is applicable to digital geographic datasets, consistent with the data quality principles defined in ISO 19113. It also establishes a framework for evaluating and reporting data quality results, either as part of data quality metadata only,
32、or also as a quality evaluation report. This International Standard is applicable to data producers when providing quality information on how well a dataset conforms to the product specification, and to data users attempting to determine whether or not the dataset contains data of sufficient quality
33、 to be fit for use in their particular applications. Although this International Standard is applicable to all types of digital geographic data, its principles can be extended to many other forms of geographic data such as maps, charts and textual documents. 2 Conformance This International Standard
34、 defines three classes of conformance: one for quality evaluation procedures, one for evaluating data quality, and one for reporting quality information. The abstract test suites for the three classes of conformance are given in Annex A. 3 Normative references The following referenced documents are
35、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 19113:2002, Geographic information Quality principles ISO 19115:2003, Geographic inf
36、ormation Metadata 4 Terms and definitions For the purposes of this document, the terms and definitions given in ISO 19113 and ISO 19115 (some of which are repeated for convenience) and the following apply. 4.1 conformance quality level threshold value or set of threshold values for data quality resu
37、lts used to determine how well a dataset meets the criteria set forth in its product specification or user requirements 4.2 dataset identifiable collection of data ISO 19115 ISO 19114:2003(E) 2 ISO 2003 All rights reservedNOTE A dataset may be a smaller grouping of data which, though limited by some
38、 constraint such as spatial extent or feature type, is located physically within a larger dataset. For purposes of data quality evaluation, a dataset may be as small as a single feature or feature attribute contained within a larger dataset. 4.3 dataset series collection of datasets sharing the same
39、 product specification ISO 19115 4.4 direct evaluation method method of evaluating the quality of a dataset based on inspection of the items within the dataset 4.5 full inspection inspection of every item in a dataset NOTE Full inspection is also known as 100 % inspection. 4.6 indirect evaluation me
40、thod method of evaluating the quality of a dataset based on external knowledge NOTE Examples of external knowledge are dataset lineage, such as production method or source data. 4.7 item that which can be individually described or considered ISO 2859-1 NOTE An item can be any part of a dataset, such
41、 as a feature, feature relationship, feature attribute, or combination of these. 4.8 population totality of items under consideration ISO 3534-2 EXAMPLE 1 All points in a dataset. EXAMPLE 2 Names of all roads in a certain geographic area. 4.9 reference data data accepted as representing the universe
42、 of discourse, to be used as reference for direct external quality evaluation methods 5 Abbreviated terms ADQR aggregated data quality results AQL acceptance quality limit ISO 3534-2 RMSE root mean square error ISO 19114:2003(E) ISO 2003 All rights reserved 36 Process for evaluating data quality 6.1
43、 General A quality evaluation process may be used in different phases of a product life cycle, having different objectives in each phase. The phases of the life cycle considered here are specification, production, delivery, use and update. Annex B describes some specific dataset-related operations t
44、o which quality evaluation procedures are applicable. The process for evaluating data quality is a sequence of steps to produce and report a data quality result. A quality evaluation process consists of the application of quality evaluation procedures to specific dataset-related operations performed
45、 by the dataset producer and the dataset user. Processes for evaluating data quality are applicable to static datasets and to dynamic datasets. Dynamic datasets are datasets that receive updates so frequently that for all practical purposes they are continuously changing. Annex C describes the appli
46、cation of the process to evaluate data quality to dynamic datasets. 6.2 Components of the process 6.2.1 Process flow The quality evaluation process is a sequence of steps taken to produce a quality evaluation result. Figure 1 illustrates the process flow for evaluating and reporting data quality res
47、ults. Figure 1 Evaluating and reporting data quality results ISO 19114:2003(E) 4 ISO 2003 All rights reserved6.2.2 Process steps Table 1 specifies the process steps. Table 1 Process steps Process step Action Description 1 Identify an applicable data quality element, data quality sub-element, and dat
48、a quality scope The data quality element, data quality sub-element, and data quality scope to be tested is identified in accordance with the requirements of ISO 19113. This is repeated for as many different tests as required by the product specification or user requirements. 2 Identify a data qualit
49、y measure A data quality measure, data quality value type and, if applicable, a data quality value unit is identified for each test to be performed. Annex D provides examples of data quality measures for the data quality elements and data quality sub-elements given in ISO 19113. Annex D, by these examples, provides assistance to the user in selection of a measure. 3 Select and apply a data quality evaluation method A data quality evaluation method for each identified data quality measure is selected. NOTE A spatial de
