SIST EN 12896-8:2026
(Main)Public transport - Reference data model - Part 8: Management information & statistics
- Abstract
The present document is composed of the following data packages:
— Indicators;
— Reusable components;
— Explicit frames for statistics
— Query.
This document itself is composed of the following parts:
— main document representing the conceptual foundations and corresponding data model (normative);
— Annex A containing the data dictionary and attribute tables, i.e. the list of all the concepts presented in the main document together with their definitions (normative);
— Annex B presenting the model evolution (informative);
— Annex C, providing details of the significant technical changes between this document and EN 12896-8:2019 (informative)
- Status
- Published
- Public Enquiry End Date
- 09-Sep-2026
- Publication Date
- 29-Oct-2026
- Technical Committee
- ITC - Information technology
- Current Stage
- 6060 - National Implementation/Publication (Adopted Project)
- Start Date
- 28-Oct-2026
- Due Date
- 02-Jan-2027
- Completion Date
- 30-Oct-2026
SIST EN 12896-8:2026 is the Slovenian standard for Transmodel Part 8, published by SIST and aligned with prEN 12896-8:2026. It specifies the reference data model for management information and statistics in public transport, including indicators, event logging, statistical methods and query structures used by operators, authorities, system suppliers and analysts.
What does SIST EN 12896-8:2026 specify?
SIST EN 12896-8:2026 specifies the Transmodel data model for management information and statistics in public transport. The document focuses on the data packages for indicators, reusable components, explicit frames for statistics and query.
In practical terms, this part defines how operational data, calculated indicators and statistical queries are structured so that different systems can exchange and analyse them consistently.
The document is organized into a normative main text and three annexes:
| Annex | What it covers |
|---|---|
| Annex A | Data dictionary and attribute tables for the concepts in the main document |
| Annex B | Model evolution and diagrams showing added concepts and relationships with other Transmodel parts |
| Annex C | Significant technical changes compared with EN 12896-8:2019 |
The scope also places this part within the Transmodel series, which is composed of 10 parts, and points readers to the wider Transmodel framework for conventions, methodology and notation.
What are the key requirements of SIST EN 12896-8:2026?
SIST EN 12896-8:2026 is built around a management-information model that turns operational public transport data into indicators and statistics. The most important requirements are in Clauses 4.2 to 4.5 and Annex A, because they define how data is prepared, recorded, analysed and exchanged.
Data preparedness must be stated
Clause 4.2 defines three data preparedness levels: raw, cleansed and processed. The producer and consumer roles change with each level, which matters because the consumer may need to clean data itself or may be able to use already validated data directly.
In practice, this lets organizations declare the reliability and processing state of exchanged data. That declaration affects architecture, software complexity and who is responsible for cleansing and statistical calculation.
Operational events are modelled explicitly
Clause 4.3 covers recording service and vehicle performance events. The covered event areas include journey monitoring, recorded passing times, recorded stops, boarding and alighting, impeded time, status of planned interchanges and disturbances.
This is the part a implementer uses when mapping operational records to the standard. It matters because punctuality, stop activity, passenger exchange and disruption events all need to be captured in a consistent way before they can be analysed.
Statistical methods are part of the model
Clause 4.4 introduces statistical concepts and methods in OpRa. The two named topics are distribution analysis support and distribution of duration type indicators.
That means the standard is not limited to storing raw events. It also provides a structure for statistical processing, especially where delay or other time-based indicators need to be grouped into distributions and compared across journeys or periods.
The conceptual data model defines the main structures
Clause 4.5 sets out the conceptual data model. The main elements are Explicit Frames, the Loggable Object Model, logging time and place, temporal and contextual structures, service dimensions, fleet dimensions, offered capacity, measured number of passengers, expected number of passengers, service intensity, delayed and early vehicle journeys, cancelled vehicle journeys, and the Query Model.
This is the core of the standard. It tells implementers how to model the operational data objects and how to connect them to indicators and queries so that systems can share comparable management information.
Passenger-counting and capacity indicators are split into several models
Clause 4.5 and Annex A show separate model families for capacity and passenger measurement, including offered capacity, expected number of passengers, and measured number of passengers. The measured passenger models are further divided into counting-device, stop-count and validated-access approaches.
That separation matters because different organizations collect passenger data in different ways. The standard lets them use the same conceptual framework even when the measurement method is not the same.
Late and cancelled journeys are modelled as indicators
Clause 4.5 includes dedicated structures for delayed and early vehicle journeys and for cancelled vehicle journeys. Annex A lists the indicator models behind these topics, including counts, entries, occurrences and mean delay.
In practice, this supports operational performance tracking, reporting and service-quality analysis. It gives a common way to represent punctuality and cancellation statistics across systems.
Annex A is the detailed reference for implementation
Annex A is normative and contains the data dictionary and attribute tables for the model. It lists the packages, subpackages and classes that make up the Part 8 model, including the indicator, fleet, passenger, service intensity and query structures.
For implementers, Annex A is the place to check the exact vocabulary of the model before building mappings, interfaces or databases.
What terms does SIST EN 12896-8:2026 define?
SIST EN 12896-8:2026 defines a set of key modelling terms in Clause 3.1 and uses several standard abbreviations in Clause 3.2.
- Aggregation frame - a data structure that groups values for use in a formula that produces an indicator.
- Indicator - calculated or measured data used to describe the status or quality of a service or function.
- Indicator type - the category of an indicator, such as time, length or passenger count.
- Indicator unit - the measurement unit used for a specific indicator, such as metres, seconds or passengers.
- Formula - the method used to calculate indicators from other indicators or raw data.
- Granularity - the smallest input unit used in a calculation process to generate indicator output.
- O/D matrix - a tabular origin/destination structure, such as daily traffic volume between zones.
- OpRa - Operating Raw Data and statistics exchange, the data-exchange context named in the standard.
Who uses SIST EN 12896-8:2026?
SIST EN 12896-8:2026 is used by public transport operators, authorities, system suppliers and analysts. The document is especially relevant where operational data has to be exchanged or analysed across systems.
Typical tasks include performance monitoring, service quality assessment, delay and cancellation analysis, capacity and passenger-demand evaluation, operational control, reporting to authorities, and service planning and optimisation. That makes the standard useful in both day-to-day operations and longer-term planning.
What changed in SIST EN 12896-8:2026 from the previous edition?
SIST EN 12896-8:2026 supersedes EN 12896-8:2019. Annex C summarizes the significant technical changes.
The changes named in Annex C include:
- deletion of the former Introduction clause
- revision of the normative references, terms and definitions, and general information clauses
- integration of operational performance tracking through late-journey incident logging, service-intensity measurements and multi-method passenger-count aggregation
- structural updates that incorporate common data-management frameworks
- extension of capacity-tracking models for offered and planned fleet dimensions
- refinement of contextual-indicator association and statistical-query protocols
- addition of reusable filtering scopes and duration-distribution analytics
- updated Annex A and Annex B
- new Annex C for technical changes
Which standards are used with SIST EN 12896-8:2026?
SIST EN 12896-8:2026 normatively references EN 12896-1. That part supplies the common concepts, conventions, methodology, notation and core principles used across Transmodel.
The bibliography and general information also name related Transmodel parts and companion standards that form the wider ecosystem:
| Standard | What it contributes |
|---|---|
| EN 12896-2 to EN 12896-7, EN 12896-10 | Other parts of Transmodel that, together with Part 8, form Transmodel version 6.2 |
| CEN/TR 12896-9 | Informative documentation to help with implementation projects |
| EN 15531 series | Service interfaces for real-time public transport operations |
| CEN/TS 16614 series (NeTEx) | Network and timetable exchange, including passenger information and accessibility |
| CEN/TS 17118 | Open API for distributed journey planning |
| ISO/IEC 19505-1 | UML infrastructure used for the model notation |
What does the SIST EN 12896-8:2026 document contain?
SIST EN 12896-8:2026 contains a conceptual model, data dictionary tables and UML-based diagrams for management information and statistics. The main text describes the data packages, while Annex A turns the model into a dictionary of concepts and attributes.
Table 1 explains the data preparedness states of raw, cleansed and processed data. Figure 1 shows a sample data flow between systems in a PTO environment.
Annex A includes the package tree and class hierarchy, with model groups for indicators, fleet dimensions, passenger counts, service intensity, queries and reusable components. Annex B uses diagrams marked for added concepts and new relationships, which helps readers see how Part 8 connects with other Transmodel parts.
Relations
- Effective Date
- 01-Dec-2026
- Effective Date
- 07-Oct-2026
- Effective Date
- 07-Oct-2026
- Effective Date
- 07-Oct-2026
- Effective Date
- 07-Oct-2026
- Effective Date
- 07-Oct-2026
- Referred By
SIST-TS CEN/TS 17370:2026 - Public transport - Operating raw data and statistics exchange - Effective Date
- 07-Oct-2026
- Effective Date
- 07-Oct-2026
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Frequently Asked Questions
SIST EN 12896-8:2026 is a standard published by the Slovenian Institute for Standardization (SIST). Its full title is "Public transport - Reference data model - Part 8: Management information & statistics". This standard covers: The present document is composed of the following data packages: — Indicators; — Reusable components; — Explicit frames for statistics — Query. This document itself is composed of the following parts: — main document representing the conceptual foundations and corresponding data model (normative); — Annex A containing the data dictionary and attribute tables, i.e. the list of all the concepts presented in the main document together with their definitions (normative); — Annex B presenting the model evolution (informative); — Annex C, providing details of the significant technical changes between this document and EN 12896-8:2019 (informative)
The present document is composed of the following data packages: — Indicators; — Reusable components; — Explicit frames for statistics — Query. This document itself is composed of the following parts: — main document representing the conceptual foundations and corresponding data model (normative); — Annex A containing the data dictionary and attribute tables, i.e. the list of all the concepts presented in the main document together with their definitions (normative); — Annex B presenting the model evolution (informative); — Annex C, providing details of the significant technical changes between this document and EN 12896-8:2019 (informative)
SIST EN 12896-8:2026 is classified under the following ICS (International Classification for Standards) categories: 35.240.60 - IT applications in transport. The ICS classification helps identify the subject area and facilitates finding related standards.
SIST EN 12896-8:2026 has the following relationships with other standards: It is inter standard links to SIST EN 12896-8:2019, SIST-TS CEN/TS 16614-4:2026, SIST-TS CEN/TS 17402:2020, SIST-TS CEN/TS 16614-4:2020, SIST-TS CEN/TS 16614-1:2020, SIST-TP CEN/TR 18359:2026, SIST-TS CEN/TS 17370:2026, SIST-TS CEN/TS 16614-6:2024. Understanding these relationships helps ensure you are using the most current and applicable version of the standard.
SIST EN 12896-8:2026 is associated with the following European legislation: EU Directives/Regulations: 2010/40/EU. When a standard is cited in the Official Journal of the European Union, products manufactured in conformity with it benefit from a presumption of conformity with the essential requirements of the corresponding EU directive or regulation.
SIST EN 12896-8:2026 is available in PDF format for immediate download after purchase. The document can be added to your cart and obtained through the secure checkout process. Digital delivery ensures instant access to the complete standard document.
Standards Content (Sample)
SLOVENSKI STANDARD
01-december-2026
Nadomešča:
SIST EN 12896-8:2019
Javni prevoz - Referenčni podatkovni model - 8. del: Informacije o upravljanju in
statistika
Public transport - Reference data model - Part 8: Management information & statistics
Öffentlicher Verkehr - Referenzdatenmodell - Teil 8: Managementinformationen und
Statistiken
Transports publics - Modèle de données de référence - Partie 8 : tableaux de bord et
statistiques
Ta slovenski standard je istoveten z: EN 12896-8:2026
ICS:
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.
EN 12896-8
EUROPEAN STANDARD
NORME EUROPÉENNE
September 2026
EUROPÄISCHE NORM
ICS 35.240.60 Supersedes EN 12896-8:2019
English Version
Public transport - Reference data model - Part 8:
Management information & statistics
Transports publics - Modèle de données de référence - Öffentlicher Verkehr - Referenzdatenmodell - Teil 8:
Partie 8 : tableaux de bord et statistiques Managementinformationen und Statistiken
This European Standard was approved by CEN on 28 September 2026.
CEN members are bound to comply with the CEN/CENELEC Internal Regulations which stipulate the conditions for giving this
European Standard the status of a national standard without any alteration. Up-to-date lists and bibliographical references
concerning such national standards may be obtained on application to the CEN-CENELEC Management Centre or to any CEN
member.
This European Standard exists in three official versions (English, French, German). A version in any other language made by
translation under the responsibility of a CEN member into its own language and notified to the CEN-CENELEC Management
Centre has the same status as the official versions.
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, Türkiye and
United Kingdom.
EUROPEAN COMMITTEE FOR STANDARDIZATION
COMITÉ EUROPÉEN DE NORMALISATION
EUROPÄISCHES KOMITEE FÜR NORMUNG
CEN-CENELEC Management Centre: Rue de la Science 23, B-1040 Brussels
© 2026 CEN All rights of exploitation in any form and by any means reserved Ref. No. EN 12896-8:2026 E
worldwide for CEN national Members.
Contents Page
European foreword . 7
1 Scope . 9
2 Normative references . 9
3 Terms, definitions and abbreviations . 9
3.1 Terms and definitions . 9
3.2 Abbreviations . 10
3.3 General information . 11
4 Management Information and Statistics Domain . 11
4.1 Introduction . 11
4.2 Data Preparedness Levels. 11
4.2.1 Preparedness level raw . 13
4.2.2 Preparedness level cleansed . 13
4.2.3 Preparedness level processed. 14
4.3 Recording Service and Vehicle Performance Events . 14
4.3.1 Introduction . 14
4.3.2 Journey monitoring . 15
4.3.3 Recorded Passing Times . 16
4.3.4 Recorded Stops . 16
4.3.5 Boarding and Alighting . 16
4.3.6 Impeded Time . 17
4.3.7 Status of Planned Interchanges . 17
4.3.8 Disturbances . 18
4.4 Statistical Concepts and Methods in OpRa . 18
4.4.1 Introduction . 18
4.4.2 Distribution analysis support . 19
4.4.3 Distribution of duration type indicators . 20
4.5 Conceptual data model . 21
4.5.1 Introduction . 21
4.5.2 Explicit Frames . 23
4.5.3 Loggable Object Model . 27
4.5.4 Logging Time and Place . 29
4.5.5 Temporal and contextual structures . 30
4.5.6 Indicators . 34
4.5.7 Service dimensions . 37
4.5.8 Fleet dimensions . 39
4.5.9 Offered capacity . 41
4.5.10 Measured number of passengers . 44
4.5.11 Expected number of passengers . 50
4.5.12 Service intensity . 52
4.5.13 Delayed and early vehicle journeys . 53
4.5.14 Cancelled vehicle journeys . 57
4.5.15 Query Model . 60
Annex A (normative) Data dictionary . 65
A.1 Introduction . 65
A.2 Data dictionary — Management information and statistics . 69
A.2.1 Part 8 - Management Information & Statistics (MI) . 69
A.2.2 Part 8 - Management Information & Statistics (MI)::EF Explicit Frame MODELs . 69
A.2.3 Part 8 - Management Information & Statistics (MI)::EF Explicit Frame MODELs::AF
Actual Frame MODEL . 69
A.2.3.1 ACTUAL FRAME . 69
A.2.4 Part 8 - Management Information & Statistics (MI)::EF Explicit Frame MODELs::CI
Contextual Indicator Frame MODEL . 70
A.2.4.1 CONTEXTUAL INDICATOR . 70
A.2.4.2 CONTEXTUAL INDICATOR FRAME . 70
A.2.4.3 CONTEXT KEYLIST . 70
A.2.4.4 GENERIC CONTEXTUAL INDICATOR . 71
A.2.5 Part 8 - Management Information & Statistics (MI)::EF Explicit Frame MODELs::PF
Planned Frame MODEL . 71
A.2.5.1 PLANNED FRAME . 71
A.2.6 Part 8 - Management Information & Statistics (MI)::EF Explicit Frame MODELs::RF
Indicator Frame MODEL . 71
A.2.6.1 INDICATOR FRAME . 71
A.2.6.2 PreparednessLevel. 72
A.2.7 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs . 72
A.2.7.1 INDICATOR . 72
A.2.7.2 INDICATOR LOG ENTRY . 72
A.2.8 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::CJ Cancelled
Dated Vehicle Journeys MODELs . 73
A.2.8.1 CANCELLED DATED VEHICLE JOURNEY COUNT . 73
A.2.8.2 CANCELLED DATED VEHICLE JOURNEY ENTRY . 73
A.2.8.3 CANCELLED JOURNEY OCCURRENCE . 74
A.2.9 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::EX Expected
Number of Passengers MODELs . 74
A.2.9.1 EXPECTED PASSENGER COUNT . 74
A.2.9.2 EXTERNAL PASSENGER COUNT . 74
A.2.10 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::FD Fleet
Dimensions Indicators MODELs . 75
A.2.10.1 ACTUAL FLEET DIMENSIONS . 75
A.2.10.2 FLEET DIMENSIONS . 75
A.2.10.3 PLANNED FLEET DIMENSIONS . 75
A.2.11 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::LJ Late
Dated Vehicle Journeys MODELs . 76
A.2.11.1 LATE DATED VEHICLE JOURNEY COUNT . 76
A.2.11.2 LATE DATED VEHICLE JOURNEY ENTRY . 76
A.2.11.3 LATE JOURNEY INTERVAL . 77
A.2.11.4 LATE JOURNEY OCCURENCE CAUSE . 77
A.2.11.5 LATE JOURNEY OCCURRENCES . 77
A.2.11.6 MEAN DELAY . 78
A.2.12 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::OC Offered
Capacity MODELs. 78
A.2.12.1 ACTUAL CAPACITY . 78
A.2.12.2 OFFERED CAPACITY . 78
A.2.12.3 CAPACITY SPECIFICATION ENUMERATION . 78
A.2.12.4 PLANNED CAPACITY . 79
A.2.12.5 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::OC
Offered Capacity MODELs::UC Use Cases . 79
A.2.12.5.1 VEHICLE SEAT COUNT . 79
A.2.13 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::PX
Measured Number of Passengers MODELs . 79
A.2.13.1 AGGREGATED BOARDING AND ALIGHTING ENTRY . 79
A.2.13.2 AGGREGATED ONBOARD DEVICE BASED PASSENGER COUNT . 80
A.2.13.3 AGGREGATED TICKETING BASED PASSENGER COUNT . 80
A.2.13.4 BOARDING AND ALIGHTING BASED PASSENGER COUNT . 81
A.2.13.5 ONBOARD DEVICE BASED PASSENGER COUNT . 81
A.2.13.6 TICKETING BASED PASSENGER COUNT . 81
A.2.14 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::SD Service
Dimensions Indicator MODELs . 82
A.2.14.1 ACTUAL SERVICE DIMENSIONS . 82
A.2.14.2 PLANNED SERVICE DIMENSIONS . 82
A.2.14.3 SERVICE DIMENSIONS . 83
A.2.14.4 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::SD
Service Dimensions Indicator MODELs::UC Use Cases . 84
A.2.15 Part 8 - Management Information & Statistics (MI)::ID Indicator MODELs::SI Service
Intensity Indicators MODELs . 84
A.2.15.1 ACTUAL SERVICE INTENSITY . 84
A.2.15.2 AVERAGE COMMERCIAL SPEED . 84
A.2.15.3 CAPACITY OVER DISTANCE . 84
A.2.15.4 EXPECTED SERVICE INTENSITY . 85
A.2.15.5 LOAD OVER JOURNEY DISTANCE . 85
A.2.15.6 MEAN CAPACITY OVER JOURNEY DISTANCE . 85
A.2.15.7 MEAN CAPACITY OVER NETWORK DISTANCE. 86
A.2.15.8 MEAN CAPACITY OVER ROUTE DISTANCE . 86
A.2.15.9 PLANNED SERVICE INTENSITY. 86
A.2.15.10 SERVICE INTENSITY . 87
A.2.15.11 TRANSPORT PERFORMANCE . 87
A.2.15.12 TRANSPORT PERFORMANCE PER VEHICLE . 87
A.2.16 Part 8 - Management Information & Statistics (MI)::RC Reusable Components MODELs
................................................................................................................................................................... 88
A.2.17 Part 8 - Management Information & Statistics (MI)::RC Reusable Components
MODELs::DM Data Managed Object MODEL . 88
A.2.17.1 DATA MANAGED OBJECT . 88
A.2.17.2 KEY LIST. 88
A.2.17.3 KEY VALUE . 88
A.2.18 Part 8 - Management Information & Statistics (MI)::RC Reusable Components
MODELs::FS Filtering Supoort MODELs . 89
A.2.18.1 CALENDAR AWARE PT SCOPE . 89
A.2.18.2 FLEET SCOPE . 89
A.2.19 Part 8 - Management Information & Statistics (MI)::RC Reusable Components
MODELs::GA Generic Aggregations MODELs . 89
A.2.19.1 DURATION DISTRIBUTION . 89
A.2.19.2 DURATION INTERVAL . 90
A.2.19.3 OCCURRENCE . 90
A.2.20 Part 8 - Management Information & Statistics (MI)::RC Reusable Components
MODELs::RT Recorded Trip MODEL . 91
A.2.20.1 RECORDED LEG . 91
A.2.20.2 RECORDED TRIP . 91
A.2.21 Part 8 - Management Information & Statistics (MI)::RC Reusable Components
MODELs::LT Logging Time and Place MODEL . 91
A.2.21.1 LOCATED EVENT . 91
A.2.22 Part 8 - Management Information & Statistics (MI)::RC Reusable Components
MODELs::RV Recorded Vehicle MODELs . 92
A.2.22.1 RECORDED STOP . 92
A.2.22.2 BOARDING AND ALIGHTING . 92
A.2.22.3 INTERCHANGE STATUS . 93
A.2.23 Part 8 - Management Information & Statistics (MI)::QM Query MODEL . 93
A.2.23.1 OPRA FUNCTIONAL REQUEST . 93
A.2.23.2 OPRA FUNCTIONAL DELIVERY . 93
A.2.23.3 GROUPING INSTRUCTION . 94
A.2.23.4 PARTICIPANT SYSTEM . 94
A.2.23.5 AGGREGATE FUNCTION . 94
A.2.23.6 AGGREGATION INSTRUCTIONS . 95
Annex B (informative) Data Model Evolutions . 96
B.1 Introduction . 96
B.2 Diagrams with additional concepts and relationships with other Parts . 96
Table B.1 — List of diagrams with additional concepts and relationships to other Parts . 96
B.3 Diagrams with additional relationships . 100
Annex C (informative) Significant technical changes between this document and the
previous edition . 102
Bibliography . 103
European foreword
This document (EN 12896-8:2026) has been prepared by Technical Committee CEN/TC 278 “Intelligent
transport systems”, the secretariat of which is held by NEN.
This European Standard shall be given the status of a national standard, either by publication of an
identical text or by endorsement, at the latest by March 2027, and conflicting national standards shall be
withdrawn at the latest by March 2027.
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 supersedes EN 12896-8:2019.
Annex C provides details of the significant technical changes between this document and EN
12896-8:2019.
This document is part of the European standard series EN 12896, known as “Transmodel”. This is a series
of documents that comprises the following parts:
— EN 12896-1, Public transport - Reference data model - Part 1: Common concepts
— EN 12896-2, Public transport - Reference data model - Part 2: Public transport network
— EN 12896-3, Public transport - Reference data model - Part 3: Timing information and vehicle
scheduling
— EN 12896-4, Public transport - Reference data model - Part 4: Operations monitoring and control
— EN 12896-5, Public transport - Reference data model - Part 5: Fare management
— EN 12896-6, Public transport - Reference data model - Part 6: Passenger information
— EN 12896-7, Public transport - Reference data model - Part 7: Driver management
— EN 12896-8, Public transport - Reference data model - Part 8: Management information and
statistics
— EN 12896-10, Public transport - Reference data model - Part 10: Alternative Modes
Together these documents create Transmodel version 6.2 and thus replace Transmodel V6.0.
In addition to the nine normative parts of this series, a Technical Report (Public Transport – Reference
Data Model – Informative Documentation) was published in 2016 under the reference CEN/TR 12896-9.
It provides additional information to help those implementing projects involving the use of Transmodel.
It is intended that this Technical Report will be extended and republished as soon as all the normative
parts are revised.
For information on the conventions, methodology, and notations for conceptual modelling and the core
principles of Transmodel, refer to EN 12896-1.
Any feedback and questions on this document should be directed to the users’ national standards body.
A complete listing of these bodies can be found on the CEN website.
According to the CEN-CENELEC Internal Regulations, the national standards organisations of the
following countries are bound to implement this European Standard: 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, Türkiye and the United
Kingdom.
1 Scope
The present document is composed of the following data packages:
— Indicators;
— Reusable components;
— Explicit frames for statistics
— Query.
This document itself is composed of the following parts:
— main document representing the conceptual foundations and corresponding data model
(normative);
— Annex A containing the data dictionary and attribute tables, i.e. the list of all the concepts
presented in the main document together with their definitions (normative);
— Annex B presenting the model evolution (informative);
— Annex C, providing details of the significant technical changes between this document and EN
12896-8:2019 (informative)
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 12896-1, Public transport - Reference data model - Part 1: Common concepts
3 Terms, definitions and abbreviations
3.1 Terms and definitions
For the purposes of this document, the terms and definitions given in EN 12896-1 and the following apply.
3.1.1
aggregation frame
data structure within which the data values are grouped and used for a formula to provide an indicator
3.1.2
indicator
set of data (calculated or measured) which may be either qualitative or quantitative that is used to
provide information on the status (may be a measure, a functional state, etc.) or the quality of a service
or a function
3.1.3
indicator type
category of a given indicator, e.g. time, length, passenger count, price, vehicle, etc.
3.1.4
indicator unit
measurement unit (e.g. metres, seconds, passengers, etc.) in which a specific indicator is measured
3.1.5
formula
method to calculate indicators that are based on other indicators or on a set of raw data
3.1.6
granularity
input for calculation processes representing the smallest unit(s) to generate output indicator(s)
3.1.7
O/D matrix
tabular structure describing data by origin/destination parameters (e.g. daily traffic volume between
zones)
3.1.8
indicator parameter type
category of a given indicator parameter, e.g. time, length, passenger count, price, vehicle, etc.
3.1.9
indicator parameter unit
measurement unit (e.g. meters, seconds, passengers, etc.) in which a specific indicator parameter is
measured
3.2 Abbreviations
API Application Programming Interface
AVM Automatic Vehicle Monitoring
AVMS Automatic Vehicle Monitoring System
GIS Geographical Information System
GPS Global Positioning System
HTTP Hypertext Transfer Protocol
IFOPT Identification of Fixed Objects in Public Transport
ISO International Standards Organization
IT Information Technology
NeTEx Network and Timetable Exchange
PT Public Transport
PTO Public Transport Operator
OJP Open API for Distributed Journey Planning
OpRa Operating Raw Data and statistics exchange
SIRI Service Interface for Real-time Information
TM Transmodel
UML Unified Modelling Language
URI Uniform Resource Identifier
URL Universal Resource Locator
VDV Verband Deutscher Verkehrsunternehmen (Germany)
WGS World Geodetic Standard
3.3 General information
The following standards are based on the Transmodel conceptual data model for public transport domain
to provide a harmonized, interoperable, and consistent approach for public transport data, service
interfaces, and journey planning across Europe:
— EN 15531 (series) [10] to [16] – Service interfaces for real-time public transport operations.
— CEN/TS 16614 (series) (NeTEx) [17] to [22] – Network and timetable data exchange, including
passenger information and accessibility.
— CEN/TS 17118 [23] – Open API for distributed journey planning.
4 Management Information and Statistics Domain
4.1 Introduction
Management information deals with functions analysing production data to evaluate the service quality
or to take corrective measures in planning and managing operations. In public transport, for instance, the
study of operational data (e.g. observed passing times, passenger load, delays and cancellations) 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 three main types of data:
— data resulting from the planning stages, i.e. theoretical data on the production orders (e.g.
timetables, target passing times, driver rosters, etc.);
— data describing the daily actual production (e.g. observed passing times, actual number of
passengers, number of late or cancelled journeys, etc.);
— data aggregations and calculated statistics (late journey duration intervals, number and
percentage of late and cancelled journey occurrences)
Advances in technology for data capture, exchange, storage and analysis make it possible to make these
data available in operational and management information systems for use by a broad range of
stakeholders, such as PT operators, authorities, system suppliers, and analysts. Consistent data
structures make it easier to define interoperable queries and data exchanges for specific tasks such as
performance monitoring, service quality assessment, delay and cancellation analysis, capacity and
passenger-demand evaluation, operational control, reporting to authorities, and service planning and
optimisation.
4.2 Data Preparedness Levels
Many use cases in OpRa use data sources that can have various levels of reliability. Informing the
consumer of a dataset about the reliability of the raw data and other indicators being exchanged an
important block of metadata. For example, if an onboard data aggregator device, acting as a producer,
states that the data has been fully processed and cleaned, the consumer side is not required to develop
and maintain data cleansing functionality.
To be able to calculate the metrics transferred, using OpRa will require, depending on the data about a
metric being transferred, access to the raw unprocessed data for both planned and unplanned service
operations as well as processed clean data.
For example, in the scenario where data is being exchanged between a PTO unit and a PTO server there
are three stages of preparedness of the data:
— Raw;
— Cleansed;
— Processed.
To illustrate the differences between the preparedness states, the following table (Table 1) sums the roles
of a producer and a consumer system, and lists some consequences which would trigger some
architecture planning considerations in an OpRa-using environment.
Table 1 — Data preparedness Concepts
Preparedness: Preparedness: Preparedness:
Raw Cleansed Processed
Producer / Producer states that the Producer states that Producer states that
Consumer roles data contains the whole erroneous data was validating the data
measurement, but it removed from the had been finished
may contain erroneous measurement. and shall not be
data. It is up to the Consumer may modified.
Consumer to get rid of further investigate
Consumer can use
measurement errors if errors if required,
the data without
needed but that’s not
further examination
mandatory
of quality
Consequences Consumer needs to Producer can hide measurement equipment’s
develop data cleansing characteristics (error probabilities)
methods
Producer has larger responsibilities
Consumer may not be depending on regulatory environment
aware of measurement
Quality of the Producer system might affect
characteristics (error
overall performance, since it filters out data
probabilities) of
Consumer software can be simpler, focusing
Producer’s equipment
more on higher-level tasks
Consumer is responsible
Consumer is responsible for calculating
for calculating statistics
statistics
A sample data flow diagram (Figure 1) shows how the level of preparedness may change as data moves
between IT systems and organisations:
Figure 1 — Data preparedness stages for a PTO – PTA environment
4.2.1 Preparedness level raw
In the scenario where data is being exchanged between a PTO unit and PTO server data for the use case
Number of cancelled journeys, the following data may be needed:
— Planned service;
— Requires actual service: control actions (PARTIAL / JOURNEY CANCELLATION);
— DATED VEHICLE JOURNEY reference;
— Cancellation type (PARTIAL / full);
— Control action metadata.
This data may contain partial or unchecked data which originates from a given person on duty at a given
place.
No checking or processing of data has occurred. This data can be referred to as raw.
4.2.2 Preparedness level cleansed
Where data goes through some cross-checking before transferring, for example it may go through some
integration process combining from multiple sources (e.g. workstations).
Where there is an obvious error, or the data value is outside of expected and or allowed values this data
element may have been removed.
This data is the same as the raw data values except false data has been removed. This data can be referred
to as cleansed.
4.2.3 Preparedness level processed
Once data has been received in the PTA data warehouse by aggregating data from multiple PTOs it may
undergo processing. This processing may have corrected a value where there is an obvious error or the
data value is outside of expected and or allowed values.
This data is the same as the raw data except where false data has been corrected. This data can be referred
to as processed.
4.3 Recording Service and Vehicle Performance Events
4.3.1 Introduction
The record of events related to the performance of vehicle journeys, in particular service journeys, on
each day of their operation is an important source of information for management information. The main
information to record is the following:
— actual passing times at points along the route;
— the number of passengers boarding and alighting and the time taken to do so;
— the occurrence of impeded time;
— interchange realisation;
— the occurrence of disturbances.
The diagram below shows such recorded information that exist in Transmodel. Several use cases use the
data from the diagram.
The Recorded Object MODEL (figure 2) for vehicle monitoring demonstrates how Transmodel supports
the capture, storage, and association of operational data related to VEHICLE MONITORING. Key
functionality of the model:
— Vehicle monitoring events: the model can record monitored vehicle journeys, including their
operational context (e.g., operating day, service journey, and vehicle journey references). Each
monitored journey can be broken down into monitored legs and monitored trips, which are
linked to trip patterns and stops.
— Temporal and spatial data: the model can handle observed passing times, recorded stops, and
interchange statuses, ensuring accurate timestamps and location references (e.g., places, zones).
— Logging and traceability: all monitored activities can be logged through vehicle monitoring log
entries and trip monitoring log entries, providing traceability for auditing and performance
analysis.
— Granularity and composition: the model allows hierarchical decomposition of journeys into legs
and trips, supporting detailed monitoring at different levels of granularity.
— Integration with service data: recorded objects should reference planned data such as service
journeys, vehicle journeys, and stop points, enabling comparison between planned and actual
operations.
— Flexibility for operational adjustments: the model should accommodate real-time updates, such
as boarding and alighting events, and interchange adjustments, to reflect actual passenger and
vehicle behaviour.
However, according to user needs many other operating raw data may be recorded.
Figure 2 — Recorded Objects MODEL
4.3.2 Journey monitoring
The data for the subsequent evaluation of service journeys is collected during operations through
recording MONITORED VEHICLE JOURNEYs (as described in EN 12896-4). Such journeys are observed
actual journeys, as recognized by a monitoring system, operated on the OPERATING DAY on which the
data are collected. The term “monitoring” should be understood in a wide sense that embraces both
automated and manual survey means.
However, it is of a great importance for management information to be able to relate, as far as possible,
any such monitored journeys to the plan assigned to them, to compare the actual production performance
against the original plan. Therefore, a MONITORED VEHICLE JOURNEY will relate, in most cases, to a
DATED VEHICLE JOURNEY. The latter represents the latest valid plan assigned to the considered vehicle.
Most DATED VEHICLE JOURNEYs will be NORMAL DATED VEHICLE JOURNEYs, which means that they
are copied from a schedule designed for a DAY TYPE to be applied on the OPERATING DAY. Others are
extra DATED VEHICLE JOURNEYs, created by a CONTROL ACTION to meet a specific set of circumstances.
Any DATED VEHICLE JOURNEY may have been amended by CONTROL ACTIONs (e.g. by shortening of the
ROUTE, an added departure lag, etc.).
4.3.3 Recorded Passing Times
The passing time of a vehicle is recorded as an OBSERVED PASSING TIME. It refers to a given MONITORED
VEHICLE JOURNEY and is recorded at a particular POINT. An OBSERVED PASSING TIME is a
specialization of DATED PASSING TIME.
The POINT in question may be a SCHEDULED STOP POINT, a TIMING POINT or any other type of POINT
defined for a measurement purpose. For instance, to evaluate the influence of the traffic on a bus line,
passing times may be recorded at the entry point then at the exit point of a complex road junction.
OBSERVED PASSING TIMEs may be recorded at TIMING POINTs to check whether standard run times are
appropriate, or at a SCHEDULED STOP POINTs to check the service punctuality as a quality indicator.
If the vehicle stops at a POINT, an OBSERVED PASSING TIME may record an arrival time or a departure
time, or both; alternatively, it may record simply a passing time. If the vehicle stops, the waiting time (i.e.
the period during which the vehicle is not moving) may also be recorded.
4.3.4 Recorded Stops
It is of interest to record when a vehicle stops at a SCHEDULED STOP POINT and opens the doors to allow
passengers to board or alight. This information is useful on networks where vehicles only stop when a
passenger (onboard or waiting at the stop point) requests it to do so. The duration of the period during
which the doors are open is also of interest, as it can be used to refine the schedules or to consolidate
demand data. This duration of the period that the doors are open is often different from that of the time
the vehicle is halted at the stop.
The entity RECORDED STOP is used to describe the above information. It is referencing an OBSERVED
PASSING TIME, extending the information captured. RECORDED STOPs may only be created for a
SCHEDULED STOP POINT. Note that, when the vehicle has several doors, the Do
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