ISO TR 21707-2008 Intelligent transport systems - Integrated transport information management and control - Data quality in ITS systems《智能运输系统 集成的运输信息、管理和控制 ITS.pdf

1、 Reference number ISO/TR 21707:2008(E) ISO 2008TECHNICAL REPORT ISO/TR 21707 First edition 2008-06-01 Intelligent transport systems Integrated transport information, management and control Data quality in ITS systems Systmes intelligents de transport (SIT) Information des transports intgre, gestion

2、et commande Qualit de donnes dans les systmes SIT ISO/TR 21707:2008(E) PDF disclaimer This PDF file may contain embedded typefaces. In accordance with Adobes licensing policy, this file may be printed or viewed but shall not be edited unless the typefaces which are embedded are licensed to and insta

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5、lease inform the Central Secretariat at the address given below. COPYRIGHT PROTECTED DOCUMENT ISO 2008 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 microfil

6、m, without permission in writing from either ISO at the address below or ISOs 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 copyrightiso.org Web www.iso.org Published in Switzerland ii ISO 2008

7、All rights reservedISO/TR 21707:2008(E) ISO 2008 All rights reserved iii Contents Page Foreword iv Introduction v 1 Scope . 1 2 Abbreviated terms 2 3 General requirements. 3 3.1 What is data quality? 3 3.2 What should a data quality standard define? 3 3.3 Data quality meta-data overview. 4 4 Data qu

8、ality meta-data 5 4.1 Service completeness 5 4.2 Service availability 6 4.3 Service grade 6 4.4 Veracity 7 4.5 Precision 8 4.6 Timeliness . 9 4.7 Location measurement. 9 4.8 Measurement source 10 4.9 Ownership . 11 5 Summary of data quality objects and their meta-data parameters . 11 ISO/TR 21707:20

9、08(E) iv ISO 2008 All rights reservedForeword 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

10、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 Electrotech

11、nical 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 t

12、he 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 exceptional circumstances, when a technical committee has collected data of a different kind from that which is

13、normally published as an International Standard (“state of the art”, for example), it may decide by a simple majority vote of its participating members to publish a Technical Report. A Technical Report is entirely informative in nature and does not have to be reviewed until the data it provides are

14、considered to be no longer valid or useful. 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/TR 21707 was prepared by Technical Committee ISO/TC 2

15、04, Intelligent transport systems. ISO/TR 21707:2008(E) ISO 2008 All rights reserved v Introduction The publication and assessment of the quality of data that may be used by or exchanged between ITS systems and centres via integrated networks is vitally important. Without a knowledge of the quality

16、of the data being exchanged, the usefulness of that data 1)is severely restricted, and whether it is fit for the intended purpose can not be established. In the worst case, it could lead to incorrect decisions being made due to wrong interpretations of the real occurrences upon which the data is bas

17、ed. All data that does not have a stated quality should therefore be classed as unqualified and should be treated with appropriate caution. Knowledge of the quality of data is relevant to all stages in the communication chain and is especially important where open systems are in place which have no

18、knowledge of the recipient or ultimate use to which the data may be put. In particular, data quality is now a key issue for service providers who need to deliver accurate information to their clients. A high level of quality is needed for the information services to retain credibility with their cus

19、tomers (rebuilding trust is a very hard task). Simply stating a measurement of quality associated with a piece of data does not in itself guarantee that the data source meets that quality. However, that is more a question of the monitoring and enforcement of service level agreements between data sup

20、pliers and data consumers and is outside the scope of this Technical Report. This Technical Report sets out only a framework for the publication and assessment of data quality. The intention is that each type of data-application domain should have its own annex setting out the quality meta- data tha

21、t are appropriate for their type of data and application. 1) Note that the term “data” is used throughout this document to mean the collective for data (plural). TECHNICAL REPORT ISO/TR 21707:2008(E) ISO 2008 All rights reserved 1 Intelligent transport systems Integrated transport information, manag

22、ement and control Data quality in ITS systems 1 Scope This Technical Report specifies a set of standard terminology for defining the quality of data being exchanged between data suppliers and data consumers in the ITS domain. This applies to Traffic and Travel Information Services and Traffic Manage

23、ment and Control Systems, specifically where open interfaces exist between systems. It may of course be applicable for other types of interfaces, including internal interfaces, but this Technical Report is aimed solely at open interfaces between systems. This Technical Report identifies a set of par

24、ameters or meta-data such as accuracy, precision and timeliness, which can give a measure of the quality of the data exchanged and the overall service on an interface. Data quality is applicable to interfaces between any data supplier and data consumer, but is vitally important on open interfaces. I

25、t includes the quality of the service as a whole or any component part of the service that a supplying or publishing system can provide. For instance, this may give a measure of the availability and reliability of the data service in terms of uptime against downtime and the responsiveness of the ser

26、vice, or it may give a measure of the precision and accuracy of individual attributes in the published data. In the majority of ITS applications, data is routinely exchanged between disparate systems. Where this data is being exchanged on a closed circuit between known senders and recipients, the pa

27、rties concerned need to understand the quality of the data being exchanged and any resultant restrictions on its subsequent use by the recipient. In most cases, this is dealt with on a case-by-case basis and all parties to the agreement to exchange data will understand the quality parameters and res

28、trictions. However, transport and travel information is frequently being provided now via interfaces onto open networks for use by external users and it may not always be known from where this data has originated or for what purposes it is suitable. In these circumstances, a stated quality of the da

29、ta becomes important and it is critical for users to understand the quality parameters so that accurate information can be derived from the data by itself or in combination with data from other sources. Data quality meta-data includes the usual range of parameters normally associated with the measur

30、ement of quality such as accuracy, precision and timeliness of the data. However, there are other important quality meta-data such as ownership of the data. Ownership is important in many applications, and data suppliers may wish to restrict the usage of their data to certain classes of users. Measu

31、res of data quality may also be important in determining the relative monetary value of data in a commercial situation and so it is important that there is a common understanding of these measures. It should be noted that, in the context of this Technical Report, data may be taken to be either raw d

32、ata as initially collected, or as processed data, both of which may be made available via an interface to data consumers. The data consumer may be internal or external to the organization which is making the data available. Additionally, the data may be derived from real time data (e.g. live traffic

33、 event data, traffic measurement data or live camera images) or may be static data which has been derived and validated off-line (e.g. a location table defining a network). Measurements of data quality are of importance in all such cases. This report is suitable for application to all open ITS inter

34、faces in the Traffic and Travel Information Services domain and the Traffic Management and Control Systems domain. ISO/TR 21707:2008(E) 2 ISO 2008 All rights reserved2 Abbreviated terms For the purposes of this document, the following abbreviated terms apply. AE Mean Absolute Error AP Availability P

35、eriod BC Business Rules Coverage CA Calculation/Estimation Method CM Collection Method CP Calculation Period DL Standard Deviation Of Data Latency ED Error Standard Deviation CV Cross-Verified DC Data Correctness DO Data Owner DP Number of Decimal Places DT Data Type(s) Covered DV Data Validity Peri

36、od EM Estimation/Simulation Model Identity EP Error Probability ET Equipment Type FC Physical Coverage GC Geographic Coverage ITS Intelligent Transport Systems LR Location Referencing Standard Identification LT Location Types LV Location Verification Standard ME Mean Error ML Mean Data Latency MS Me

37、asurement Source Identity NP Number of Data Points OR Data Owners Original Reference PC Percentage Occurrence Coverage ISO/TR 21707:2008(E) ISO 2008 All rights reserved 3 RL Reliability RU Restricted Use of Data SF Number of Significant Figures SG Service Grade SL Source of Location Data SS Spatial

38、Data Set TF Mean Time Between Failures (MTBF) TP Time Precision TR Mean Time To Repair (MTTR) TS Data Time Stamping Regime UI Data Update Interval UM Data Update Mode VP Validation Process 3 General requirements 3.1 What is data quality? Data quality is a slight misnomer since the “perception of qua

39、lity” or “measurement of excellence” is not what we really mean here. These terms actually relate to the perception of quality by the data consumer and are terms used to assess the fitness for purpose of the received data. What we mean in this Technical Report by the term “data quality” is a set of

40、meta-data which defines parameters relating to the supplied data or service that allows data consumers to make their own assessment as to whether the data is fit for their intended application. Different applications require different aspects of data quality and so it is not possible to say, for ins

41、tance, that a data set with a reporting interval of one minute is of a higher quality than one with a reporting interval of 3 min. Only the data consumer can make this judgement of “perceived quality” since it must be based on the needs of their application (e.g. in terms of timeliness, accuracy, co

42、mpleteness, etc.). 3.2 What should a data quality standard define? From the previous section it is clear that any standard for data quality should not be trying to define how measurements of excellence can be defined, but instead needs to identify what types of meta-data are appropriate and useful f

43、or a data supplier to provide and how this data may be structured and promulgated. Different application and data domains within ITS may have very different requirements for data quality meta- data. It is therefore the intention that this data quality Technical Report specifies only a framework whic

44、h each application and data domain can follow for identifying data quality requirements within their respective domain. Each ITS application and data domain will be required to define its own quality meta-data profile in a specific annex. ISO/TR 21707:2008(E) 4 ISO 2008 All rights reserved3.3 Data q

45、uality meta-data overview Measurements of data quality are applicable to different levels within the structure of information flows across an interface. At the lowest level, data quality meta-data is a measurement of the accuracy, precision or probability of correctness of any attribute within the d

46、ata structure exchanged across an interface. For instance, this could be a measure of the accuracy of a location, a length of a queue or a timestamp, or it could be the probability of correctness of a severity estimate (selected from an enumerated list). But data quality is also applicable at the hi

47、gher level of data objects that flow across an interface. These data objects can be things like records defining an event or situation on a road, measurement of traffic flow or a camera image from a road video information system. The data quality meta-data which is applicable to these high level dat

48、a objects is an assessment of the combined data quality of the individual attributes that go to make up the high level data object; for instance, does an accident event really exist or not. Finally, an assessment of the quality of the data service as a whole or sub-parts of a data service that a sup

49、plier can offer to a data consumer is also an important measure. This is to do with the availability and reliability of the service as a whole and a definition of how well the data supplier covers the information in the live domain. However, another way of classifying quality meta-data parameters is to determine whether they relate to the measurement of the quality of specific instances of data items, or whether they relate to the measurement of quality of data items, objects, the whole data service or parts of the whole service speci