Quality Online Repository
This website page is a central repository for all elaborations by the NAPCORE Quality Activity. It includes background information and various deliverables as downloadable files. The Repository is populated incrementally, i.e. documents may be uploaded or updated over time. Please check this website page regularly for updates
Last Update: June 29, 2025
Data quality as a success factor for ITS
The efficiency and acceptance of Intelligent Transport Systems (ITS) services depend to a large extent on meeting the quality expectations of individual users, such as travellers. These services in turn rely on accurate and up-to-date data and information, often sourced from various data providers. Therefore, there is a clear correlation between the quality of an ITS service and the quality of the underlying data.
In the ITS data value chain, data quality depends on various actors, from traffic managers and information providers to end users. From the users’ perspective, perceived quality depends not only on the data content but also on data visibility, description, legal and technical data access, and conformity with declared structures. Moreover, data quality is context-dependent, often going beyond ITS and mobility use cases.
In theory, data suppliers should monitor data quality, report quality levels and continuously improve data provision. In practice, however, ITS end-user service providers reusing such data often face challenges in assessing and aligning data quality, due to undocumented and non-harmonised quality levels. Various actions are therefore needed to support and harmonise data quality assessment and documentation by the different ITS data actors. NAPCORE provides some basic elaborations on this.
The Quality Activity at NAPCORE
One of the main tasks of NAPCORE is to provide a robust framework for the quality assessment of (meta)data in European NAPs.
A dedicated Quality Activity at NAPCORE establishes quality-related agreements and definitions for different NAP data and service domains. In particular, definitions are made about quality criteria and quality requirements, covering aspects such as geographic coverage, timeliness, latency, position accuracy, and error level.
A major output of this task is a set of Quality Frameworks for different data domains and use cases.
A Quality Framework is a set of definitions and an application guidance for actors dealing with NAP (meta)data quality. Key elements include:
- quality criteria, sometimes also called quality indicators, metrics or parameters,
- quality levels which describe (minimum) requirements to be met for each quality criterion, and
- recommendations how to assess these criteria and levels.
Quality Frameworks for NAP (meta)data
The individual Quality Frameworks are available below:
Generic report “A set of Quality Frameworks for the assessment of NAP (meta)data quality”
This report compiles the background and approaches to establishing these Quality Frameworks. It describes basic concepts and previous approaches to defining data quality, provides a road-map to the quality elaborations in NAPCORE, and summarizes the individual Quality Frameworks by NAPCORE.
A Quality Framework for Floating Car Data (FCD)
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Floating car data (FCD), also known as probe vehicle data, is widely regarded as an advanced method for supporting ITS services. FCD is a dynamic and real-time data collection method that involves gathering information from GPS-equipped vehicles as they move through a road transport network. In this respect, FCD serves as a life feed providing a continuous picture of and insights into various facets of the operational state and status of a road transport network, including traffic flow, travel patterns, level of congestion, and vehicle-induced emissions.
The FCD Quality Framework evaluates the suitability of FCD through four key dimensions: correctness, completeness, timeliness, and hybrid dimensions. Each dimension encompasses specific quality criteria and metrics tailored to assess different aspects of data quality.
A main input was an analysis of current State of the Art, including use cases with FCD relevance. From here, a set of FCD quality criteria and metrics was proposed. Another important part of the methodology was a case study with real-life FCD in Thessaloniki.
The report compiles the methodology, criteria, and metrics, offering a practical tool for assessing and improving FCD quality across diverse applications.
A Quality Framework for UVAR Data
Urban Vehicle Access Regulations (UVARs) have become quite prominent as a means of traffic management in many European cities and regions. UVARs mostly target road safety and environmental goals and regulate or restrict the usage of public road network elements based on certain criteria. These criteria include vehicle types, traveller types and land-use types. The regulations and restrictions are typically valid for certain areas and (optionally) for certain time periods.
To support the harmonised digitisation and electronic communication of UVARs across Europe, the QUALITY FRAMEWORK for UVAR Data providing guidance on applicable quality criteria and metrics, as well as on how to conduct quality assessments.
The report compiles findings from the literature research and the methodology to capture the applicable quality criteria and metrics. It further provides a detailed description of applicable Quality Criteria and Metrics, as well as practical recommendations to conduct quality assessments in real-life settings. Lastly, it contains a case study with a concrete example of how to apply the framework.
A Cross-Domain Quality (CDQ) methodology for assessing data and services Quality
The CDQ methodology includes various assessment methods for the standardised reporting of different aspects of data/service quality during several phases of the subscription process (planning, staging, production and ad-hoc) and for different assessment types. These assessment methods form a horizontal layer above other domain-related Quality Frameworks.
The first developed method is called “Evaluation of the formal quality of data/service documentation”. This method evaluates metadata of a specific data set/service against defined criteria, enabling data users to check the suitability of a data set/service during the planning phase of data subscription process. This method is operational, with tools and detailed documentation available for individual assessments.
A Quality Framework for On-Street Parking Data
Even if parking is a substantial element of the transport system, parking-related data became prominent in the ITS domain only in the recent years, mainly due to the intensified digitalisation of parking management, and the explicit consideration of parking in several delegated regulations under the European ITS Directive. However, quality aspects for related data have been only defined in the truck parking context by the EU EIP project (see below). In contrast, no quality definitions are found for the urban parking scenario.
To fill this gap, NAPCORE partner BASt elaborated a Quality Framework for Parking Data. In particular, this Framework is dealing with on-street parking data in urban settings. It is providing definitions for static and dynamic data about on-street parking infrastructure, parking regimes and parking availabilities. It is revisiting, concretising, and expanding previous quality definitions, and putting them in a practical context of data provision in the on-street parking domain.
Because there are many data-sourcing opportunities to describe an on-street parking situation, a quality approach must consider a heterogenous data landscape. A suitable method was found in ground-truth and cross-reference testing, as realised by BASt in the city of Hamburg, Germany. The findings and analyses from this data analysis, as well as feedback and expertise from parking management staff in Hamburg, were used to define and validate quality definitions for on-street parking data. The results are published in a scientific report.
A Quality Framework for Multimodal Travel Information Services (MMTIS) data
MMTIS data is quite complex as it encompasses all mobility modes and their interactions, while involving all mobility stakeholders. Likewise, quality definitions for the MMTIS are quite complex, considering different mode-related and local/ national conditions and specificities.
A first approach by the EU EIP project in 2019 formulated initial concepts, defining basic criteria applicable to all countries, also enabling NAP implementations.
To ensure acceptance and maturity of this previous work, NAPCORE has renewed the MMTIS Quality Framework, addressing a broader range of MMTIS stakeholders, and reusing expertise from parallel EU projects in the MMTIS domain, such as DATA4PT.
The methodology for this quality Framework started with a review of the former EU EIP Framework, which was then reframed and concretised to capture relevant quality aspects. Further, current MMTIS quality methods and approaches in the EU were reviewed via three online workshops.
All these inputs have been considered for an update of the MMTIS Quality Framework. The report compiles the methodological approach, an updated set of MMTIS quality criteria and metrics, and recommendations for a practical assessment of such criteria and metrics.
A Quality Framework for Alternative Fuels Data
The provision of high-quality Alternative Fuels (AF) data is critical to supporting the growing number of initiatives designed to advance sustainable transport across Europe. A current trigger in this context is the Alternative Fuels Infrastructure Regulation (AFIR) by the European Commission, which mandates data about AF infrastructures to be published on National Access Points (NAPs) from April 2025.
However, the lack of clear data quality definitions and standards has so far hindered stakeholders from effectively providing AF data through the National Access Points (NAPs). NAPCORE has been tasked with developing a dedicated Quality Framework for AF data, which is essential for ensuring data reliability and fostering wider adoption of the AFIR.
The public report outlines the development of that framework, detailing the methodology and structure behind it.
A Quality Framework for Road Network Topology
The topology of a road network refers to the arrangement or structure of the network, including how roads are connected and the relationships between different segments or nodes within the network. This Framework aims to establish a common understanding of quality aspects, when dealing with topology information.
The methodology starts with an analysis on how road databases are usually modelled, on relevant use cases relying on network topology, and on relevant data providers. The quality dimensions are then derived from an analysis of so-called topological checks, which are usually conducted by road databases. One of such checks is the “‘Road Segments must Be Properly Snapped‘, for example.
In this process, it became clear that the road network data topology topic is complex in nature and in scope. It was also found that the topology is a result of a processed map, meaning that the quality aspect moves to the relevant data sets that define the digital maps.
In the end, a complete finalised framework of defined and agreed quality definitions could not be provided that can be implemented right away. Instead, some follow-up actions were defined. This includes a further analysis of the relationship between the relevant map data and the resulting topology data needs. It also includes a future work on quality definitions for the data that the underly the topological process, such as data on roadwork nodes, for example. Future NAPCORE quality activities will cover the identified follow-up actions.
Quality Framework Application Guideline
Another deliverable by NAPCORE supplements the presented Quality Frameworks with practical support. While the Quality Frameworks define quality criteria and methods in a theoretical manner, the Application Guideline focuses on how to practically apply these frameworks. It provides guidance, examples, and methods to support practitioners in carrying out quality assessments, and it consolidates insights from pilot assessments, previous research, and stakeholder inputs.
The report presents a hands-on guideline for organisations responsible for data quality on NAPs and other data platforms. It covers the following aspects:
- Roles of key actors (NAP operators, data providers, data consumers, National Bodies, and neutral organisations) in data quality assurance
- Fundamental principles for conducting quality assessments
- A set of practical methods for quality assessment, illustrated with real-world examples and aligned with different quality criteria and stages in the data lifecycle
Previous Quality Frameworks by EU EIP
The “European ITS Platform” (EU EIP) was a EU project between 2016 and 2021. It enabled the cooperation of road authorities, road operators, ministries and partners from the private sector in the field of Intelligent Transport Systems (ITS) for roads. The main goal was to foster, accelerate and optimise current and future ITS deployments.
One of the tasks was to achieve a common understanding of data quality in ITS, especially for Europe-wide deployments of ITS services and data provision. In particular, common quality criteria and requirements, as well as quality assessment methods for evaluating ITS data and services were elaborated.
Among others, Quality Frameworks were provided for the following ITS domains:
- Safety-Related and Real-Time Traffic Information Services
- Multimodal Travel Information Services
- Intelligent Truck Parking Services
- C-ITS
An online repository provides all quality-related outputs by EU EIP:
https://www.its-platform.eu/achievement/quality-of-european-its-services-and-their-data/
NAPCORE takes advantage of this legacy, by reusing and concretising many of the EU EIP concepts.
Widening the perspective: parallel actions beyond NAPCORE
There are various initiatives by ITS sectors and stakeholder groups to establish and streamline quality concepts.
One of these is the TISA’s proposal for a “RTTI 5-Star Rating Standard”. It defines quality requirements for data provisioning by road authorities in three key areas (speed limits, roadworks, road closures) so that they are processed in the services delivered by service providers to end users. The aim of the standard is, among others, to clarify minimum quality levels that provide added value for service providers for inclusion of data in their services. This standard incorporates previous definitions for data quality by EU EIP, and expands those based on perspectives gathered at various stakeholder workshops. NAPCORE is working with the authors of the 5-Star Rating Standard, with the goal to align quality perspectives across the wider ITS and NAP domain.
https://tisa.org/successful-rtti-5-star-rating-evaluation-methodology-workshop/
https://tisa.org/successful-tisa-rtti-quality-workshop-in-amsterdam/
The US Federal Highway Administration has commissioned a framework called “Traffic Data Quality Measurement”. It contains methods and guidelines for measuring data quality for different applications in road traffic management. It defines fundamental measures of traffic data quality, proposes calculation procedures for these measures and suggests acceptable levels of quality for different applications. Again, the NAPCORE team is in contact with the authors of this framework to exchange international perspectives and work towards common solutions.
The C-Roads Platform is a joint initiative of European Member States and road operators for testing and implementing C-ITS services in light of cross-border harmonisation and interoperability. A collaboration agreement between NAPCORE and C-ROADS has been set up, recognizing that the delivery of reliable ITS and C-ITS services depends on multiple levels of data, information, technical, and service quality encompassing all steps of the ITS value chain.
A first cooperation activity investigated in further detail the connection between NAPCORE and C-ROADS platforms on the topic of data quality. This resulted in collaboration note providing a preliminary mapping between NAPCORE Quality Frameworks and C-Roads services/use cases. This analysis will enable further discussions on lower-level aspects, such as additional quality criteria/requirements or even implications of data quality aspects on C-ITS service provision (and service quality thereof).
Future investigations are envisioned through workshops involving C-Roads and NAPCORE partners, experts, and representatives.
- Cooperation note: “Cooperation C-Roads Platform and NAPCORE_Data quality topic”
Feedback and more information
Feel free to contact the activity leader if you have any feedback or need further information on the NAPCORE Quality Activity:
- Peter Lubrich
- Federal Highway Research Institute (BASt), Germany
- lubrich@bast.de
- napcore@bast.de
