ISO/TR 21707:2008
(Main)Intelligent transport systems — Integrated transport information, management and control — Data quality in ITS systems
Intelligent transport systems — Integrated transport information, management and control — Data quality in ITS systems
ISO/TR 21707:2008 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 Management 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. ISO/TR 21707:2008 identifies a set of parameters or meta-data such as accuracy, precision and timeliness etc. 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. It 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 service or it may give a measure of the precision and accuracy of individual attributes in the published data. It should be noted that in the context of ISO/TR 21707:2008 data may be taken to be either raw data 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 organisation which is making the data available. Additionally the data may be derived from real time data (e.g. live traffic 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. ISO/TR 21707:2008 is suitable for application to all open ITS interfaces in the Traffic and Travel Information Services domain and the Traffic Management and Control Systems domain.
Systèmes intelligents de transport (SIT) — Information des transports intégrée, gestion et commande — Qualité de données dans les systèmes SIT
General Information
Standards Content (Sample)
TECHNICAL ISO/TR
REPORT 21707
First edition
2008-06-01
Intelligent transport systems —
Integrated transport information,
management and control — Data quality
in ITS systems
Systèmes intelligents de transport (SIT) — Information des transports
intégrée, gestion et commande — Qualité de données dans les
systèmes SIT
Reference number
©
ISO 2008
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ii © ISO 2008 – All rights reserved
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 quality 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
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 exceptional circumstances, when a technical committee has collected data of a different kind from that
which is 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 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 204, Intelligent transport systems.
iv © ISO 2008 – All rights reserved
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 of the data
1)
being exchanged, the usefulness of that data 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 based.
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 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 customers (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 suppliers 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 that 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)
Intelligent transport systems — Integrated transport
information, management 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 Management 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 parameters 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. It 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 service, 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 parties 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 restrictions.
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 data 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 measurement 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. Measures 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 data 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 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 interfaces in the Traffic and Travel Information Services
domain and the Traffic Management and Control Systems domain.
2 Abbreviated terms
For the purposes of this document, the following abbreviated terms apply.
AE Mean Absolute Error
AP Availability Period
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 Period
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 Measurement Source Identity
NP Number of Data Points
OR Data Owner’s Original Reference
PC Percentage Occurrence Coverage
2 © ISO 2008 – All rights reserved
RL Reliability
RU Restricted Use of Data
SF Number of Significant Figures
SG Service Grade
SL Source of Location Data
SS Spatial 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 quality” 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 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. Dif
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