SIST-TP CEN/TR 17370:2019

SLOVENSKI STANDARD
01-september-2019
Javni prevoz - Neobdelani operativni podatki in izmenjava statističnih podatkov
Public transport - Operating raw data and statistics exchange
Öffenlicher Verkehr - Betriebliche Rohdaten und Austausch statistischer Daten
Ta slovenski standard je istoveten z: CEN/TR 17370:2019
ICS:
03.220.99 Druge oblike transporta Other forms of transport
35.240.60 Uporabniške rešitve IT v IT applications in transport
prometu
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.

CEN/TR 17370
TECHNICAL REPORT
RAPPORT TECHNIQUE
July 2019
TECHNISCHER BERICHT
ICS 35.240.60; 03.220.99
English Version
Public transport - Operating raw data and statistics
exchange
Transports publics – Échange de données brutes Öffenlicher Verkehr - Betriebliche Rohdaten und
d’exploitation et de données statistiques Austausch statistischer Daten

This Technical Report was approved by CEN on 3 June 2019. It has been drawn up by the Technical Committee CEN/TC 278.

CEN members are the national standards bodies of Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia,
Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway,
Poland, Portugal, Republic of North Macedonia, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey and
United Kingdom.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATIO N

EUROPÄISCHES KOMITEE FÜR NORMUN G

CEN-CENELEC Management Centre: Rue de la Science 23, B-1040 Brussels
© 2019 CEN All rights of exploitation in any form and by any means reserved Ref. No. CEN/TR 17370:2019 E
worldwide for CEN national Members.

Contents Page
European foreword . 4
0 Introduction . 5
1 Scope . 10
1.1 Introduction . 10
1.2 Assessment phase . 10
1.3 Use cases definition and classification phase . 12
1.4 Indicators definition phase . 12
1.5 Raw data identification phase . 12
2 Normative references . 12
3 Terms and definitions . 12
4 Symbols and abbreviations . 15
5 National scenarios for Public Transport raw data and statistics exchange . 16
5.1 General. 16
5.2 France . 16
5.2.1 General. 16
5.2.2 Rail reporting . 16
5.2.3 Local public transport reporting . 17
5.2.4 Quality, economic and sociologic management . 18
5.2.5 Security analysis. 18
5.3 Hungary . 19
5.4 Italy . 20
5.5 The Netherlands . 21
5.5.1 General. 21
5.5.2 Monitoring . 22
5.5.3 Reporting . 23
5.6 Slovenia . 24
5.6.1 General. 24
5.6.2 Collecting and reporting of Public Transport raw data (operational statistics) . 24
5.7 Slovakia . 26
5.8 Spain . 28
6 Public Transport KPI definition in research projects . 31
6.1 General. 31
6.2 EBSF — European Bus System of the Future (2008 to 2013) . 32
6.3 KPI description . 32
6.4 MEDIATE — Methodology for describing the Accessibility of Transport in Europe
(2008 to 2010) . 35
6.4.1 General. 35
6.4.2 KPI description . 35
6.5 CONDUITS — Coordination of Network Descriptors for Urban Intelligent
Transportation Systems (2009 to 2011) . 37
6.5.1 General. 37
6.5.2 KPI description . 37
6.6 METPEX — a MEasurement Tool to determine the quality of Passenger Experience
(2012 to 2015) . 39
6.6.1 General. 39
6.6.2 KPI description . 40
6.7 TIDE — Transport Innovation Deployment for Europe (2012-2015) . 46
6.7.1 General . 46
6.7.2 KPI description . 47
6.8 D3IMPACT — Data-driven decisions for intelligent management of public
transportation (2015 to 2016) . 49
6.8.1 General . 49
6.8.2 KPI description . 50
6.9 CELSO — Low-cost and high-performance pocket Automated Vehicle Monitoring
system for Public Transport (2016) . 50
6.9.1 General . 50
6.9.2 KPI description . 51
6.10 MOP — Mobility Operation Platform: an Italian research and development project . 51
6.10.1 General . 51
6.10.2 Operation Monitoring Control: Status and Process KPI in PT Systems . 52
6.10.3 Evaluation standards of the PT service . 53
6.10.4 MOP Outline: indicators and methodologies for monitoring public transport services
............................................................................................................................................................................. 54
7 Use cases . 54
7.1 Purpose . 54
7.2 Actors and use case categories . 55
7.2.1 Actors . 55
7.2.2 Use case categories . 55
7.2.3 Collection of use cases. 56
8 Compatibility with existing standards and recommendations . 105
8.1 Compatibility with Transmodel . 105
8.1.1 General . 105
8.1.2 Raw data and indicators . 106
8.1.3 Data structure representation . 106
8.2 Compatibility with EN 13816:2002 — Service Quality Definition, Targeting and
Measurement . 111
8.3 Compatibility with EN 15140:2006 — Basic requirements and recommendations for
systems that measure delivered service quality . 112
9 OpRa Generic Physical Model and XSD early draft . 113
9.1 General . 113
9.2 What is a physical model. 113
9.3 First input toward an XML (XSD) model implementation . 114
Annex A (informative) Data Dictionary . 116
Annex B (informative) Research Projects vs. OpRa KPI . 119
Bibliography . 130

European foreword
This document (CEN/TR 17370:2019) has been prepared by Technical Committee CEN/TC 278
“Intelligent transport systems”, the secretariat of which is held by NEN.
Attention is drawn to the possibility that some of the elements of this document may be the subject of
patent rights. CEN shall not be held responsible for identifying any or all such patent rights.
This document is the Technical Report (TR) of Operating raw data and statistics exchange (OpRa) that
contains information needed to define precisely the contents of what could be the scope of the following
Technical Specification (TS) or European Norm (EN).
0 Introduction
0.1 General
The Public Transport (PT) sector, particularly for Public Transport Operators (PTO) and Public Transport
Authorities (PTA), has identified the necessity to develop a data strategy, based on the cost and value,
focusing on the strategic benefits of data. It is crucial that mobility stakeholders are not only able to
compete against potential new market entrants, but also need a suitable environment to develop new
business models and services. Public transport is becoming a data-enabled or data-driven business and
should answer different local conditions.
This led to the need to standardize data analysis in Public Transport to understand formally how
information can be created as added value and indicator calculation can facilitate moving from a
qualitative analysis of the PT service towards a quantitative one.
In this perspective, OpRa (Operating raw data and statistics exchange) defines a minimum set of Public
Transport raw data needed as PT quantitative analysis enabling factor.
This document is an informative document that describes the approach followed to perceive this goal and
the results got.
0.2 Transport modes
OpRa takes most public transport modes, except air transport, into account. This specifically includes rail,
bus, metro, tramway, trolleybus, ferry, coach, funicular railway, suspension railway, and rack railway.
0.3 OpRa management information
Management information deals with functions analysing production data in order to evaluate the service
quality or to take corrective measures in planning and managing operations. In PT, for instance, the study
of operational data (e.g. observed run times, passenger load) collected during service operations is an
input for strategic planning (e.g. how and when to amend the schedules), tactical planning (e.g. when to
undertake a certain control action), quality follow-up, etc.
Management information uses, therefore, two main types of data:
— data resulting from the planning stages, i.e. theoretical data on the production orders (e.g. timetables,
run times, driver rosters, etc.);
— data describing the daily actual production (e.g. observed passing times, actual number of
passengers, missed interchanges, modifications operated to the plan, etc.).
Advances in technology, in particular as regards data storage, allow the provision of all the necessary
underlying data in production databases, against which the desired requests can be made by PT
managers. Consistent data structures for management data will make the design of such requests easier,
and offer the flexibility required to OpRa exchange PT raw data, in order to enable indicators calculation.
Raw data is identified according to specific use cases and, where applicable, defined and described in
Transmodel format. In this perspective, the exchange will be performed using similar NeTEx modalities,
for compatibility reasons.
0.4 OpRa exchanging data modality
Similarly, to NeTEx, the primary software resource from implementing an OpRa interface will be based
on XML schema; at this stage, a full schema has not been designed yet.
Two main variants of the schema will be available each providing a different protocol for embedding the
same content model subschemas.
a) Simple OpRa documents exchange: (see NeTEx _publication.xsd). A schema to use with NeTEx
documents input or output by a system that are exchanged as files using FTP, email etc.
b) OpRa document exchange using SIRI HTTP requests: (see NeTEx_siri_SG.xsd). A schema that
embeds the OpRa elements in a sequence of HTTP messages that define request/response and
publish/subscribe interchanges for exchanging data. Requests use OpRa elements to specify the
desired data. Responses wrap in version frames. The messages are specializations of the SIRI
framework.
0.5 Motivation
Measured Public Transport data describing the public transport network fulfilment are essential for
studies, control, service improvement and contractual relations between stakeholders. It is important
that they can be shared among PTO, PTA, engineering and design office, researchers, and other actors in
a clear and unambiguous way, in order to provide accurate and intelligible information.
Furthermore, the OpRa covered scope is fully complementary to other existing exchange standards and
allows covering one of the small remaining gaps of public transport standardization, with particular
references to Transmodel, NeTEx and SIRI.
NeTEx (CEN/TS 16614-1 to 3) is an exchange protocol dedicated to scheduled public transport data,
based on the Transmodel (EN 12896) conceptual data model. NeTEx supports the exchange of
information relevant to public transport services for passenger information and AVM systems and is
divided into three parts:
— Part 1: network topology exchange;
— Part 2: timetables exchange;
— Part 3: fare information exchange.
SIRI (EN 15531-1 to 5) is complementary with NeTEx and provides operators and manufacturers with a
standard framework for exchanging data concerning public transport real-time information, along with
a set of functional services for specific types of real-time data. As for NeTEx, the underlying conceptual
definitions used by SIRI are provided by Transmodel. SIRI and NeTEx share the same communication
protocol.
Using these standards, scheduled and real-time information can be made available for passenger
information, and for operations and for process review. However, there is still one final aspect missing,
just after real-time: to provide information about what has actually been performed, with the same
overall view as for scheduled information. Such data allows a feedback loop to improve existing services.
The OpRa work is therefore about operating raw data and statistics, regularly requested by PTA, aims to
meet that need.
0.6 CEN Standards context
OpRa work has been developed under the aegis of CEN draws on a number of existing national Public
Transport Service scenarios and EU standards.
The keystone is the Transmodel standard, a conceptual model that names and represents PT info
concepts for a wide set of functional areas and can be used to compare and understand different models.
Transmodel project outputs have been used both to underpin a number of CEN concrete data standards
such as NeTEx, SIRI or IFOPT . It underpins many national standards to allow for harmonization and
interoperability. Transmodel generic model has been used to develop OpRa and OpRa-specific
requirements itself being updated to include OpRa additions provided also some of Transmodel
enhancements (present in prEN 12896-8, concerning Management Information and Statistics).
CEN (Comité Européen de Normalization) is Europe’s standardization body. It divides its work into
committees covering different aspects of industry and technology. OpRa work is formally produced by
Technical Committee 278, Work Group 3, Sub-Group 10. Other TC 278 WG 3 sub-groups handle the
related standards, in particular, Transmodel (SG4 Reference data model), SIRI (SG5 Service Interface for
Real-time Information) and NeTEx (SG9 NEtwork and Timetable EXchange).

Figure 1 — CEN TC 278 WG 3 Sub-groups
0.7 CEN process and participants
The CEN process requires a working sub-group to develop a candidate specification, which is then sent
to national mirror groups for review and comment, with voting stages for approval and adoption. Work
on OpRa has involved delegates from France, Hungary, and Italy. Evolution of EU PT standards and OpRa
for rail with TAP/TSI compatibility.
The following countries have shown interest for the activation of OpRa work:
1) Austria (ASI);
2) Czech Republic (UNMZ);
3) Denmark (DS);
4) France (AFNOR);
5) Hungary (MSZT);
6) Italy (UNI);
7) Netherlands (NEN);
IFOPT has been included in Transmodel Part 2: Public Transport Network (EN 12896-2) and is no more a
standalone standard.
8) Norway (SN);
9) Slovakia (SOSMT);
10) Slovenia (SIST);
11) Spain (UNE);
12) United Kingdom (BSI).
The following map shows the distribution of the stakeholders by country, based on whether they are
already active or just interested in the results.

Figure 2 — OpRa stakeholders' involvement
The development of OpRa has drawn on PT national scenarios, in particular to identifies needs and
validate the OpRa detailed use cases by establishing mappings with studied national PT scenarios.
The development of OpRa also coincided with an interest by the European Rail Authority (ERA), UITP
and other stakeholders in seeking a degree of data interoperability between different modes of Public
Transport such as rail, metro and bus, that is, the ability to exchange PT raw data about routes, timetables
and fares between systems and to supply external third-party users.
0.8 Evolution of EU PT standards and OpRa
This document describes the results of preliminary analysis phase covering the following main topics:
— national scenarios for Public Transport raw data and statistics exchange (needs and usage);
— Public Transport Quality of Service (QoS) in EU projects;
— use cases definition and classifications;
— compliance with CEN TC 278 WG 3 standards (Transmodel).
The subsequent work consists in the definition of a Technical Specification (TS) for OpRa data exchange
format and associated services. In this perspective, it has been proposed to insert this standardization
activity among those included in the EU ICT Rolling Plan 2019.
0.9 Further information
In the case of long-distance train, OpRa work takes into account the requirements formulated by the ERA
(European Rail Agency) — TAP/TSI (Telematics Applications for Passenger / Technical Specification for
Interoperability), entered into force on 13 May 2011 as the Commission Regulation (EU No 454/2011),
and based on UIC directives.
1 Scope
1.1 Introduction
The OpRa work scope is the definition of a minimum set of Public Transport raw data needed as PT
quantitative analysis enabling factor. To obtain this considering all the several aspects involved in this
complex domain, the work has been conducted through the following phases:
1) assessment;
2) use cases definition and classification;
3) indicators definition;
4) raw data identification.
OpRa work does not go into the field of service quality measurement and reporting: service quality
analysis will of course use data provided by OpRa, but quality definition remains a contractual level issue
between a Public Transport Authority and a Public Transport Operator or an operator’s internal choice
for a purely private service. OpRa mainly only reports unbiased actual data (i.e. measured or observed),
described and aggregated in a shared and understandable way.
The OpRa work documented in detail in this document is coherent with EU Directive 2010/40. In
particular, it relates to the Article 4 of the Delegated Regulation EU 2017/1926 [33], as regards the
historic data. OpRa proposes to complement NeTEx (dedicated to the static scheduled information), for
the historic data based on the underlying conceptual data reference model Transmodel EN 12896,
similarly to the requirement of the Delegated Regulation EU 2017/1926 referring to the static scheduled
.
information
1.2 Assessment phase
The assessment phase has been conducted studying the following aspects:
• national scenarios for public transport raw data and statistics exchange, to identify indicators needs
and usage;
• public transport KPI definition in research projects to consider what has been already done in
literature and research;
• relations with public transport EU norms, to be coherent with already existent PT norms.
Moreover, involved actors and stakeholders have been identified like: Public Transport Authority
(PTA), Public Transport Agencies, Public Transport Operator (PTO), system integrators and

Transport authorities, transport operators, infrastructure managers or transport on demand service providers
shall provide the static travel and traffic data and historic traffic data listed in point 1 of the Annex of the different
transport modes, by using: (a) for the road transport, the standards defined in Article 4 of Delegated Regulation
(EU) 2015/962; (b) for other transport modes, the use of one of the following standards and technical specifications:
NeTEx CEN/TS 16614 and subsequent versions, technical documents defined in Regulation (EU) No 454/2011 and
subsequent versions, technical documents elaborated by IATA or any machine-readable format fully compatible
and interoperable with those standards and technical specifications; (c) for the spatial network the requirements
defined in Article 7 of Directive 2007/2/EC.
16) For what concerns the exchange of static scheduled data (such as public transport, long distance coach and
maritime including ferry), the relevant data in the national access point should use the CEN data exchange standard
NeTEx CEN/TS 16614 based on the underlying conceptual data reference model Transmodel EN 12896:2006 and
subsequent upgraded version.
passengers, analysing public transportation Planning and Operation process, that have been divided into
five main stages to group all the activates that characterize the Public Transport Service:
• strategic planning: definition of network elements (lines, stops), main service parameters (vehicles
sizes, operation intervals, service intervals for important time demand types), and guaranteed
interchanges are planned;
• tactical planning: operators plan their resource usage (vehicles, rolling stock, personnel), with
detailed timetables for each resource unit;
• before travel: all planned networks and timetables are published. Passengers and other types of
clients can plan their use of the offered transportation services via printed and electronic media, and
make their reservations as needed;
• in-travel: the transportation service is conducted. Real-time information exchange is available while
this takes place and can be recorded;
• study and control: in this stage, operators and authorities review the history of actual operations,
which could lead to improvements through operational changes, or an optimization of strategic and
tactical planning.
The PTA and PTO are interested in all the defined stages, meanwhile from the passenger point of view;
only the last three stages are relevant (all the preparation work being hidden).

Figure 3 — Public Transport Service phases
During the assessment the most relevant research projects results have been considered and a deep
analysis of the roles and usage of Public Transport Standards have been completed to guarantee a
coherent approach of OpRa.
The first four stages are under the scope of NeTEx (Network Timetable Exchange) and SIRI (Service
Interface for Real Time Information) and the last stage is the additional scope to be covered by OpRa. All
these standards are compliant with the European Public Transport Reference Data Model (Transmodel).
NeTEx supports data exchange for the Strategic Planning and Tactical Planning stages, with data more
than 24 h before validity date. In the Before Travel stage, NeTEx can be used to publish all planned data
to client systems. Meanwhile SIRI supports “in-travel / in-operation” data exchange.
The OpRa scope is mainly concentrated to support data exchange for the Study and Control stage and it
mainly focus on actual and measured information, i.e. information that cannot be changed anymore in the
future. The OpRa covered concepts are based on following Transmodel domains:
— operations monitoring and control (Part 4);
— management information and statistics (Part 8).
1.3 Use cases definition and classification phase
To identify the set of raw data, a clear definition of use cases that, based on the assessment phase results,
describes the indicators definition and usage to satisfy the Public Transport Study and Control phase is
needed.
In this complex and articulate scenario, the work bring to a definition of several use cases this led to the
needs to aggregate them and classify accordingly.
1.4 Indicators definition phase
For each defined use case an indicator has been formally defined, including its formulae. It has been
advised that some indicators could have particular importance in for the Quantitative Analysis and in this
perspective they could be considered Key Process indicators (KPI), for the purpose of this OpRa work,
indicators and KPI are used as synonyms.
1.5 Raw data identification phase
After use cases and indicators have been defined, the work enter in the phase of raw data identification
for the calculation of the indicators included all use cases. Due to the high level of complexity of the
results, a traceability matrix has been identified.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content
constitutes requirements 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.
EN 12896-8:2018 , Public Transport — Reference Data Model — Part 8: Management Information and
Statistics
3 Terms and definitions
For the purposes of this document, the terms and definitions given in prEN 12896-8 and the following
apply.
ISO and IEC maintain terminological databases for use in standardization at the following addresses:
• IEC Electropedia: available at http://www.electropedia.org/
• ISO Online browsing platform: available at http://www.iso.org/obp
3.1
attribute
property of an entity
3.2
conceptual data model
description of a real-world domain in terms of entities, relationships, and attributes, in an
implementation independent manner and providing a structure on which the rest of the development of
an application system can be based

Under preparation. Stage at the time of publication: prEN 12896-8:2018.
3.3
conceptual level
conceptual data model in the context of data modelling
3.4
database
collection of data; often used in the sense of the physical implementation of a data model
3.5
data model
real-world domain in terms of data and relationships
3.6
entity
object (data) that has its own existence (as opposed to an attribute)
3.7
function
a sub-activity of a functional area
3.8
functional area
arbitrarily defined set of activities used to define the objectives and limits of the data model
3.9
interoperability
ability of (sub) systems to interact with other (sub) systems according to a set of predefined rules
(interface)
3.10
logical data model
data design that takes into account the type of database to be used but does not consider the means of
utilization of space or access
3.11
logical denormalized model
relational data model that is not fully normalized, i.e. does not completely follow the normalization rules
and thus could be redundant
3.12
logical level
logical data model in the context of data modelling
3.13
management information
all activities allowing the company management to collect the information necessary to meet problem-
solving needs
Note 1 to entry: Data of operational systems are filtered and aggregated for the purpose of management
information, and are made available to the user interactively, or in form of pre-defined reports and summaries. Such
functions are in principle related to all functional areas of a company, with particular reference to the management
of statistical results.
3.14
operations monitoring and control
all activities related to the transportation process, i.e. real-time functions related to the driving and
transportation of passengers according to given instructions, including the monitoring of the driving
process and its control in case of deviations, as well as all activities that support the driving process
(traffic light priority, track switching, bay selection, advance/delay advice, etc.)
Note 1 to entry: Such functions are often assisted by computer-aided tools, known as Automated Vehicle
Monitoring (AVM).
3.15
passenger information
all activities related to informing the users either on the planned or on the actual transportation services
3.16
real-time control
see operations monitoring and control
3.17
relational data model
type of logical data model giving the information as series of tables (relations) and attributes
Note 1 to entry: The relational data model has the following characteristics: 1) all attribute values are atomic, 2) all
“tuples” (rows/occurrences) are distinct, 3) no part of the primary key may be null, 4) foreign key values have to
correspond to an existing primary key in another relation or be null.
3.18
scheduling
see tactical planning
3.19
strategic planning
all activities related to definition of network elements (lines, stops), main service parameters (vehicles
sizes, operation intervals, service intervals for important time demand types), and guaranteed
interchanges planned
3.20
tactical planning
all activities related to the tactical planning of transportation, splitting into vehicle scheduling, driver
scheduling, and rostering
3.21
UML
Unified Modelling Language
3.25
domain specific terms and definitions
terms specific to the management information and statistics domain and which are also data entity names
Note 1 to entry: These terms are defined in Annex A and are mostly not repeated here.
3.25.1
indicator
relates to a set of data (planned or measured) and could be either qualitative or quantitative
3.25.2
granularity
determines the smallest unit for an indicator
3.25.3
formula
describes the method to calculate indicators that are based on other indicators or on a set of raw data
4 Symbols and abbreviations
API application programming interface
AVL automated vehicle location
AVLS AVL system
AVMS automated vehicle management system
CEN Comité Européen de Normalization
DRT demand responsive transport
FTS flexible transport service
IFOPT identification of fixed objects in public transport
ISO International Standards Organization
KPI key process indicator
NeTEx Network and Timetable Exchange
OpRa Operating Raw Data and statistic exchange
PT public transport
PTA public transport authority
PTO public transport operator
QoS quality of service
SIRI service interface for real-time information
TR Technical Report
UML Unified Modelling Language
UC use case
WGS World Geodetic Standard
WSDL Web Services Description Language
XMI XML Metadata Interchange
XML Extensible Mark-up Language
XSD XML schema document
5 National scenarios for Public Transport raw data and statistics exchange
5.1 General
A deep and detailed study of PT world has been conducted, focusing on current or desired usage of raw
data and statistics on information exchange processes among stakeholders (mainly authorities, operators
and system providers) in several EU countries. Particular attention has been posted on the identification
of all possible measured data and measured data aggregation and statistics exchanges.
All the aspects have been described in terms of Public Transport National scenarios, including high-level
description of the role of indicators in PT Governance. Thanks to this contribution, national requirements
have been collected and analysed, focusing on data input for PT network study including ERA, UITP and
UIC.
5.2 France
5.2.1 General
Several scenarios implying the use of raw data are considered in France:
— reporting from rail companies to authorities in French regions (this scenario is the one having
provided most of the French use case as input to OpRa);
— reporting of bus operators to local authorities (from city to region);
— internal use at operator level in order to improve the quality and the economy of the service;
— security analysis.
5.2.2 Rail reporting
Strong needs were reported from ARF (Association des Régions de France) and were used as input for
OpRa. French regions are in charge of organizing the rail transport within the regions (mainly TER), with
the SNCF as operator for now, but also having in mind the incoming market opening. There are some
strong contractual reporting requirements (rail operator reporting to the regional authority) in order for
the region to check how the ordered service compares to the actual one. Furthermore, regions are facing
unstable data formats and unclear definition when collecting operational data, and this needs to be solved
for the current situation, and even more in the context of an opened market.
The main identified expectations are:
— clear definitions of exchanged concepts;
— a generic list of concepts in which they could pick up what they need for operational reporting and
indicator building: the selected concept could then unambiguously be inserted in call for tender. The
generic list needs of course to be available for authorities and operators;
— a well-defined and stable data format to exchange information related to the above concepts;
— rules that can be inserted in call for tenders and that can be verified (verify and test the conformance
of data sets to the expected concepts and exchange protocol).
Examples of needs:
— identify the number of late trains per station, clearly differentiating cancelled trains and late trains;
— collect information about disruptions, differentiating incidents due to the infrastructure, due to
external events (weather, passenger), due to the operator, to strikes, etc.
— comparison of data sets (reporting) produce at different dates;
— being able to easily import the operational reporting in tool (allowing visualization, comparison and
statistics);
— to have the same type of information for several region, allowing comparison across regions;
— to have a clear view of the scheduled service including: vehicle type, number of vehicles, distances,
number of passenger per train (expected, maximum), etc., and later on the corresponding observed
values so they can be compared to each other;
— getting the information about substitution offer and when they are used;
— differentiate distance run by train (kilometres) and distance run by coaches;
— to be able to collect to have ticketing information (sold tickets and travel cards, km and trips per
travel cards, etc.);
— to be able to focus on subparts of Vehicle Journeys (for trains crossing several regions);
— etc.
5.2.3 Local public transport reporting
Operational reporting is highly important for rail, but is equally important at local level (cities, urban
area, etc.). This will mainly involve relation between authorities and bus operators, but also tram and
metro operators. Therefore, even if there are some obvious commonalities with the reporting expected
from rail operator, this local context has a set of particularities.
This local market is already fully opened and requires to clearly set the expectations in call for tenders,
and then control through the provision of operational data that the service is consistent with the
requirement (with possible financial adjustments).
Among the particularities of this local market, it may be mentioned a higher focus on distance (service
with passengers and dead-run without passengers, with a clear distinction b
...