ACTIVITY 3.1: Identify information sources and cooperate with data owners


By Tom Wood / Updated: 28 Nov 2019


Before deciding on future policies, it is essential to know what problems you are currently facing. In urban transport and mobilityinfo-icon, this knowledge is often very fragmented and incomplete. Like pieces of a puzzle, datainfo-icon and information need to be put together in order to describe the current situation. To conduct a good analysis, you first need to identify which data is needed (to analyse all SUMP aspects and, in particular, the political priorities of your process), what information is available, and what is still lacking. Beginner cities with no or only a small amount of data available should not be discouraged and rather see it as an opportunity to improve data collection as part of the SUMP process. A challenge most cities face is that their data is not harmonised in terms of timescales or spatial coverage, and that data is often distributed between different data owners, holders or storage systems. As a result, access can become a problem due to a lack of information on existing databases and because of reluctance to share the information - in particular when commercial operators, are involved who might also demand high payments for their data or cite commercial confidentiality. A thorough data auditinfo-icon, excellent communication with data owners and mutual data sharing with them can help to overcome this. Experience has shown that early involvement of internal and external data owners and clear agreements can contribute to a higher willingness to cooperate.



  • Identify data needs in terms of political priorities and probable objectives.

  • Get a good overview of the available data, including quality and accessibilityinfo-icon.

  • Identify data gaps and additional information needed for your mobility analysis.

  • Cooperate with external and internal organisations to complete your dataset, ideally establishing long-term agreements to ensure good data supply also in the future.

  • Ensure that gaps in data are filled where possible.

  • By combining data available in different parts of your organisation, in other organisations, and (if needed) by collecting new data, achieve a set of information on urban mobility and related areas that enables a status analysis.



  • Perform a data audit. Get an overview of data needs and sources, identify all available data relevant for your Sustainable Urban Mobility Planinfo-icon, and assess its quality and accessibility.

  • Retrieve available data, synthesise its content and identify data gaps for your main mobility issues. Select suitable data that describes the status of transport and mobility in your city, focused on the general aims of sustainable urban mobility (see first Milestone) and the political priorities that led to the decision to develop a SUMP. For example, if a political priority is to improve road safety, then data on fatalities is required. Your data should provide information on the status and trends of:

    • all transport modes used in your city, including freight and the level of integrationinfo-icon of modes (multimodalityinfo-icon);

    • all main sustainable mobility aspects relevant to your city (e.g. air pollution, traffic noise, road safety, liveability of public spaces, equitable accessibility to services, employment and education).

  • Go beyond a simple description of the status and aim to understand the underlying reasons. For example,

  • why do most people still drive to the centre and park there despite good availability of Park & Ride? Strive for data explaining the motivations for mobility behaviour that you want to influence, for example by including qualitative behaviour-related questions in mobility surveys. This information will help to choose effective measures later on.

  • Consult stakeholders and the general public on the problems and issues that they feel should be addressed by the SUMP. This makes them aware of the planning process, ensures that their voices are heard and makes the public feel ownershipinfo-icon of the SUMP. Their collective impression can also be a valuable source of information that helps to fill data gaps.

  • Strive to arrange data sharing with external owners of data that you need for your analysis. Respect confidentiality (following European and national legislation), anonymise personal information and handle data carefully to avoid cooperation problems (consider setting up a security strategyinfo-icon for your data management). Explain clearly why the data is required, showing the benefits to be generated by its use, and describe how the data will be used and held by your organisation. Agree together on the process to collect and share the data so that all partners can rely on a single, common set of information (e.g. secure data sharing platform).

  • To fill important remaining gaps in your data, you should check the availability of default values, such as those provided e.g. by the national level, or collect additional data that is not accessible from internal or external data owners. Data can be collected by a variety of means. For example, trends in the number of pedestrians can be determined by carrying out manual counts annually at key points in the city, such as by installing counting machines or conducting a household survey. The choice of methodinfo-icon depends on the resources available, the size of the city and the level of reliability required. The following general types of data could be distinguished:

    • Quantitative data from automatic measurements (e.g. counting machines, infrared and other sensors, cameras, satellites) or GPS data (e.g. vehicle tracking, mobile phone locations collected via apps or by mobile providers),

    • Quantitative and qualitative data from surveys (household, on-street, in-vehicle) or from on-street observations (e.g. manual traffic counts, site visits, inventory of curb space assignments),

    • Qualitative data from interviews or focus groups,

    • Qualitative data from journals, blogs, social media,

    • Modelling data to fill data gaps.


For data collection, it is important to generate precise, specific and complete data sets, but also to set priorities and clear targets for the purpose of the data. The Topic Guide Urban Road Safety and Active Travel in Sustainable Urban Mobility Planning offers a list of priorities for data collection related to road safety:

  • Identification of the main types of accidents as a basis to define the right targetinfo-icon groups to approach and measures to be developed;

  • Identification of dangerous spots in the multi-modal network;

  • Setting realistic but ambitious targets for safety policyinfo-icon;

  • Awareness building: correct accident figures can help to build awareness;

It also defines a minimum set of data needed to analyse the road safety situation in a city. Most importantly, the analysis should consider:

  • Total number of casualties and fatalities per year in the city over a period of at least 3 years;

  • Total number of accidents without injuries, grouped according to the different transport modes, over a period of at least three years; and

  • Location and type of accidents on the (multimodal) network of the city


Activities beyond essential requirements

  • Use open data as much as possible. This will make the process more transparent, allowing citizens and stakeholders to access and use the data, which in turn can benefit your planning activities (e.g. university students who analyse a mobility issue in- depth or who programme a mobility app for your city). Make sure that the open data that is used is of high quality.

  • Establish a central municipal data centre that manages the data of all departments. This facilitates internal data exchange and integrated planning, making it easier to consider the data and policy aspects of other departments.


Timing and coordination

  • Can be started once the core team is set up and the geographic scope is defined (see Activity 1.2 and 2.1), at the latest after agreeing on the timeline and work plan.

  • Directly feeds into the mobility analysis of Activity 3.2.

  • The identification of data sources and needs is linked to the definition of objectives (Activity 5.2), strategic indicators (Activity 6.1), and the monitoringinfo-icon process (Activity 11.1).



✔ Data needs to be specified, with a view of political priorities and probable objectives.
✔ Available data identified and quality checked.
✔ Data gaps defined and additional data sources identified.
✔ Secure data management established.
✔ Data sharing with external owners of relevant data agreed.
✔ Additional data collected, if needed.


Tools for measuring the quality of public spaces

There is a range of tools available that help you to measureinfo-icon how people use public spaces and to understand how they can be improved for the public life that takes place in them. As one of the forerunners in this area, Gehl Institute offers a selection of such tools on their website, such as:

  • Twelve Quality Criteria is a toolinfo-icon for researching how public spaces are experienced by their users. More specifically, it is used to evaluate whether different features of a public space are protective, comfortable, and enjoyable for people.

  • People Moving Count measures how many people move through a space and by what means. This information gives you a sense of how busy a space is at different times of the day and how accessible it is by different modes of transport.

  • The Stationary Activity Mapping tool helps you map what people are doing in a space at a given time, such as sitting on a bench, playing sports, or performing live music. The result is a “snapshot” of activity in your survey area. By evaluating what is already happening in a place, you can begin to identify potential enhancements to public life.

  • Increasingly, apps are used for public space analysis, which makes it easier for cities to collect data in the field and to later organise and share the data on a public database.

For more information, see:


Listen & learn! - Online map-based surveys for data collection [ref:47]

Planning for people requires the (early) integration of citizens in the process - for example through data collection with Public Participationinfo-icon GIS (Geographic Information System). Online map-based surveys, which link an online survey with an interactive map, combine public involvement and data collection for smart planning that is based on people’s needs, perceptions and ideas. PPGIS enables the collection of data from a large and diverse group of people, while it improves public involvement, helps to create ownership for the process, and also takes up the citizeninfo-icon perspective. For planners, the collected data can be a source of information, and PPGIS can also be used to give citizens decision-making power in the process. For example, through defining the areas of intervention with mapping those with need of improvement (e.g. perceptions of public transport service, mapping unsafe areas, insufficient cycling routes etc.). In this way, the city of Helsinki developed its Master Plan together with citizens and the city of Stockholm collected ideas for the design of a new neighborhood. Rather than replacing traditional methods, online map-based surveys can complement them to reach a wider public and increase the quality of the collected data. Especially for metropolitan areasinfo-icon, Public Participation GIS can be a door opener to reach a wide audience in the whole region.

Which kind of data can you collect with online map-based surveys?

Collecting data directly from and with citizens can give you a completely new insight into people’s living environments that can be utilized along the planning process. By asking participants to locate various places on a map (e.g. their daily activity places or areas they prefer/avoid), assess the quality of infrastructure, or map their ideas for the future development of the city, Sustainable Urban Mobility Planning can gain a closer perspective from the citizens and understand where actions need to be taken. By collecting spatial data, geographical patterns can be linked with socio-demographic aspects, attitudes and environmental quality. Data from map-based online surveys can, for example, be used to understand more about:

  • Mobility behaviour (e.g. through mapping of visited places, routes, trip purposes, visit frequencies, mode choices);

  • Places of interest and activity spaces;

  • (Dis-)Satisfaction and perceptions of e.g. neighborhood, urban space, accessibility, public safety, green space, mobility services, infrastructure, etc.;

  • Identification of areas in need of improvement (e.g. insufficient public transport service);

  • Mobility-related health outcomes and well-being; and

  • Demographic data.

Which online tools are available?


Measuring accessibility - the Flemish ‘Mobiscore’ approach

Urban mobility planning should focus not only on mobility in the narrower sense (i.e. the ease of moving around in the city), but also on the final aim of mobility, which is the accessibility of places and activities. Accessibility describes the actual potential to participate in out-of-home activities. One of the barriers you need to overcome in order to address accessibility more explicitly in a SUMP is the difficulty to measure it.

The Flemish tool and its use in Flanders

In May 2019, the Environmentinfo-icon, Nature and Energy Department (LNE) of the Flemish administration launched a web-based tool, ‘Mobiscore’, that assigns an ‘accessibility score’ to a particular house or land lot. The score informs potential buyers or renters of a house about how well the various facilities – such as a railway station, bus stop, school, etc. – can be reached in a sustainable manner; such as by foot or by bike. With the development of this tool, the Ministry department wants to raise awareness among citizens about the mobility impact that arises from the choice of residence. The decision to buy or rent is an influential moment that can be seized to drive change in mobility behaviour, for example, modal choices. People who want to move to a new house can easily compare the accessibility of different locations on the Mobiscore website ( – only in Dutch). The tool could also evolve into a useful analytical instrument for urban mobility planning. As it assigns an accessibility score for each hectare (100x100m), a map of the different scores in a functional urban area would reveal areas with high and low accessibility. This can, for example, help in deciding where to upgrade public transport or biking connections most urgently. Furthermore, it can certainly better link urban development policy with mobility planning by showing where to develop housing, schools, etc., in order to promote sustainable transport modes.

How the Flemish approach can inspire your SUMP

It is unlikely that a ready-made tool to measure accessibility to common daily destinations is available in your city. However, during Activity 3.1 (Identify information sources and cooperate with data owners), you should check with the Spatial or Urban planning department or research institutes in your area to see if GIS-based data on the location of shops, schools, etc., is available. Based on these densities, an accessibility score for different areas in the city can be developed. In addition, density of public transport stops or the identification of areas within walking distance of these stops (e.g. 400 meters for bus stops and 800 meters for train stops) can be analysed. In the second SUMP phase on strategy development, accessibility indicatorinfo-icon mapping can inform discussions with public transport providers, citizens and other stakeholders. This is particularly useful when cooperating with urban development departments in order to develop a so-called TOD strategy (Transit Oriented Development), i.e. urban development oriented towards public transport nodes while also discouraging developments in car-dependent areas with low public transport accessibility. On the neighbourhood level, accessibility mapping can encourage the development of active mobility routes and helps planning for mixed-use developments, including schools, shops and services.

For more detailed information on the methodology used for the ‘mobility score’ indicator developed in Flanders, see:

Author: Dirk Lauwers, Center for Mobility and Spatial Planning, Ghent University

Figure 18: Geographical distribution of the Mobiscore across Flanders (scoring for 1 hectare cells; red (4) being the least accessible and blue (9) the most accessible; Transport & Mobility Leuven, 2019. Mobiscore,


More analysis tools

More info: 


Partnership for data collection between municipality and public transport authority

In the past years, Gdynia has established a valuable partnership with different actors to collect data for mobility planning. Detailed interviews with citizens on mobility preferences and behaviours (carried out by the public transport authority), GPS data collected in different campaigns and projects, traffic observations, as well as interviews on the street with pedestrians, drivers, and shop owners provide data. It is used
i.a. for heat maps, animations of cycling flows, and freight statistics useful to transport and city planners. Developing a trustworthy relationship with your partners and making them part of the whole process helps you to both receive data and maintain the partnership for the future.

Source: City of Gdynia, collected by UBC



Online citizen participation to assess the mobility situation

Complementing traditional methods of data collection, the City of Bremen utilised crowdsourcing-based methods to analyse the problems and opportunities of mobility developments in the city. A proactive participation strategy and innovative online participation modules allowed citizens to be a key data source. Citizens addressed questions - ‘where are things running badly?’ and ‘where are they running smoothly?’ – through an online platform, which enabled users to further mark specific locations on a map and color-code entries according to transport mode. The portal received more than 100,000 page views, 4,000 contributions, 9,000 comments, and 100,000 ‘like’ or ‘dislike’ comments.

Author: Michael Glotz-Richter, City of Bremen, collected by ICLEI