Unlock diverse, quality mobility data in Brussels for insights, planning, and innovation.
Register now Discover our APIAccess diverse, quality-assured mobility data in Brussels for insights, planning, and innovation. Explore real-time and historical data from various sources like public transport, micro-mobility, railway, traffic, and air-quality feeds. Power your data-driven solutions for optimized urban mobility.
Access to real-time geospatial location feeds of various mobility sources, including public transport vehicles, micro-mobility vehicles, railway trains, traffic, and air-quality feeds.
Processed data is enriched and integrated, allowing users to build applications using high-quality and enhanced data.
Acts as a centralized access point for all mobility-related information in Brussels, eliminating the need to search through multiple sources.
Provides access to large amounts of historical mobility data, enabling research work on batch mobility data management and analytics.
Provides efficient pipelines for data cleansing, enhancement, and fusion, ensuring high-quality and usable data for analysis and decision-making.
Encourages applied research efforts and collaboration with the research community to refine and improve the dataset, maximizing its value for various stakeholders.
The Mobility Twin for Brussels is a unique open data ecosystem that allows you to access and use mobility data from the Brussels-Capital Region. It is a unique opportunity to develop innovative solutions for the mobility of tomorrow.
As an open data platform, the Mobility Twin for Brussels is a collaborative project. You are always welcome to contribute to the platform by adding new data sources, improving the data quality, or enriching the data by creating new data products.
ContributeIf you use the platform or the data provided by the platform in one of your projects, please cite the paper below:
@article{merten_sakr_mobilitytwin_2023,
title = {Brussels Mobility Twin (Data and Resources Paper)},
author = {Gaspard Merten and Mahmoud Sakr},
booktitle = {The 31st ACM International Conference on Advances in Geographic
Information Systems (SIGSPATIAL '23)},
year = {2023},
address = {Hamburg, Germany},
publisher = {ACM},
doi = {10.1145/3589132.3625634}
}