Data Sets for Ghent

Improving urban mobility together

Data Sets for Ghent

The data that we collect for TMaaS is either fetched from sources with an online API or via sensors (polling). This page shows an overview of all data sources that are integrated so far in the TMaaS dashboard for Ghent.

Public Transport

Information on public transport can help citizens plan their journey in advance and can help enhance service and ultimately facilitate greater use.

De Lijn

TMaaS fetches the data for De Lijn buses and trams within Ghent, for all stops in the city. De Lijn shares much information relevant to users of a certain bus of tram line, as open data and guarantees the data quality.

Data Collected:

  • Bus passthrough traffic throughout Ghent
  • Tram passthrough traffic throughout Ghent
  • Location bus stops
  • Timetables
  • Bus delays/cancellations
  • Tram delays/cancellation
  • Travel time

De Lijn API

NMBS trains

We get the data for NMBS trains within Ghent, for the key stations in the city.

The NMBS shares information on the train schedules & real-time delays as open data. We get it from their API to calculate how many trains are currently in Ghent, what the delays are and detect if any trains have been cancelled. We get the info from the iRail API, who gets it from the NMBS and shares it through a more comprehensible API. NMBS also guarantees the data quality.


Travel Times

A travel time is the needed time it takes to travel from the start-location to the end-location. This information is typically derived from two types of data sources, detection loops and Floating Car Data (FCD).FCD are real-time positions from vehicles collected from different sources as smartphone apps (Waze, Flitsmeister) or on board units. This information is important for traffic management as it gives an insight into the traffic situation in their region. A combination of these two data sources gives a real-time and accurate overview on the traffic situation in the city.


Vehicle detection happens via insulated, electrically conducted loops, installed in the pavement and detects and counts vehicles passing on this fixed point, for example on highways or before traffic lights. They give accurate traffic intensity and travel times, but only on these fixed points. It is not possible to follow a vehicle. The cost price for the installation of loop detectors is quite high, which means that the price for the data can also rise.

Traffic Events

These are events which results in (partially) closure of the road or in a reduced traffic flow. We have divided these events in four categories:

  1. Incidents
  2. Road works
  3. Objects on the road
  4. Accidents.

Weather Information

Information on current and near future weather are very important for travellers, especially for bikers and pedestrian/visitors of the city. Also drivers can be alarmed in case of potentially dangerous situation such as reduced visibility by heavy rain, fog,… of slippery roads by ice. There are many sources available, some are open data and some are paying services.

Parking cars and bicycles

We have divided parking information in three sub clusters namely: on-street, off-street and bicycle parking information.

On-street parking information
On-street parking information is mostly collected by parking sensors or based on ticketing. With the use of parking sensors we can have a detailed occupancy on individually parking spots while off-street and on-street based on ticketing gives information on a collection of parking spots.
Parking sensors are devices that are attached to each separate parking space and measure if and when a vehicle is located there. This way you can also keep an overview of the number of parking spaces that are free and how long a vehicle is parked (interesting for payments). For the city of Ghent we will analyze parking information based on the ticketing from 4411 and try to have an indication on the on-street parking occupancy in Ghent.

Bicycle parking data
The city of Ghent has a number of underground bicycle parking stations where the occupancy of the bicycle racks is monitored and this information will be added to the the TMaaS dashboard for Ghent.

Off-street parking information
As there are many private parking owners, many sources are available for information on underground/above ground parking. This is a difficulty many traffic management systems encounter. Because for one city or region many providers need to be contacted for purchasing the fragmented data. However more and more initiatives on collecting the data and providing the clustered parking information are arising as open data.

Map Data

This data type concerns the data available to create a base map for the TMaaS platform. A base map provides users with context for a map and will be used as an underground for other geospatial information (travel times, parking spots, air quality,…).

For cyclists

This data type consists of data which are interesting for the cyclists in a city. This can include bicycle counters or or safe bike routes. The city of Ghent has a couple of bicycle detection loops which will be implemented in the TMaaS dashboard for Ghent. This information consists of static and dynamic data.

For pedestrians

At this moment we are looking into data sources to measure crowdedness on the streets, especially during events. Cellular information could provide this information. Other data that could be relevant are the quality of the sidewalks.

Car & Bicycle sharing

Static (location) and dynamic (availability) information on car rental where people rent cars for short periods of time, often by the hour. In the city of Ghent, there are various car-sharing services. Information is available on their website but mostly not available by API.

Static (location) and dynamic (availability) information on bike rental where people rent bicycles for short periods of time, often by the hour. In Ghent, Blue Bike and Trapido provide static and dynamic information for third parties by API.

Points of Interest

Points of interest (POI) are specific point locations that a city or citizens may find useful or interesting. These points can be anything for example: toilets, bank, shops, bars, co-working offices etc.

Crowdsourced data

With the use of social media or community-based apps (Touring Mobilis app, Waze, Flitsmeister,…) traffic control centres can receive fast reliable information of incidents in their city. Not only will they receive information from the people in their region but they also can use this community to check or validate events/incidents. These events/incidents can consist of travel times, routes, accidents, road works, jams, obstacles, dangerous weather conditions etc. Also these channels can be used to spread warnings of important information.