Module 3: Collection of data for active modes
This module dives into the world of walking and cycling data—how to collect it, interpret it, and use it to drive change in urban mobility planning.
It introduces practical approaches for gathering reliable data on active modes, from using smart technologies and collaborating with service providers to applying simple on-the-ground methods. Participants will learn how to combine different data sources, involve citizens in the process to enrich insights, use data and communicate findings effectively to decision-makers, stakeholders, and the public.
The module highlights why data is essential—not only for understanding current mobility patterns, but also for shaping Sustainable Urban Mobility Plans (SUMPs), evaluating pilots, and building community trust. Real-life examples from European cities will show how data collection methods are being tested and integrated into broader monitoring and evaluation frameworks.
Module 3
What will you learn?
✔Understand why data on walking and cycling is critical for Sustainable Urban Mobility Plans (SUMPs) and pilot projects.
✔Learn practical methods for collecting active mobility data, including on-the-ground techniques, smart technologies, and collaboration with service providers.
✔Explore how to combine different data sources to create a more complete picture of mobility patterns.
✔Discover approaches to involve citizens in data collection, improving accuracy and fostering community engagement.
✔Gain insights into how to communicate transport data effectively to different audiences—decision-makers, stakeholders, and the public—ensuring transparency and impact.
✔See real-life examples from European cities that illustrate innovative data collection practices and their integration into broader monitoring and evaluation frameworks.
➜ By the end of the module, participants will be equipped to apply practical methods for collecting and analysing walking and cycling data, involve citizens effectively in the process, and communicate results to different audiences with confidence. Through interactive workshops, participants will discuss their own challenges and experiences, exchange ideas, and identify solutions that fit their local context.
Agenda
Webinar: 04.03.2026, 09:00–10.30 CET
- 09:00–09:10 | Welcome & Framing Ira Sibelius, Union of the Baltic Cities Sustainable Cities Commission / City of Turku, Finland, and Maarja Käger, Institute of Baltic Studies, Estonia
- 09:10–09:45 | Importance of collecting data about active modes. TBC
- 09:45–10:00 | Collecting and representing data: Focus on collecting data: challenges, outcomes, and lessons learned. Kertu Vuks, City of Tartu, Estonia
- 10.00–10.15 | Piloting a mobile app based campaign as a platform for data collection Maria Uusitalo, Gävle municipality, Sweden
- 10:15-10:25 | Examples from the SUMPs for BSR project pilots: engaging citizens in the collection of data. Maarja Käger, Institute of Baltic Studies, Estonia
- 10:25-10:30 | Wrap up and next steps
Workshop: 18.03.2026, 09:00–11.30 CET
- 09:00–09:10 | Welcome & Framing Ira Sibelius, Union of the Baltic Cities Sustainable Cities Commission / City of Turku, Finland, and Maarja Käger, Institute of Baltic Studies, Estonia
- 09:10–09:25 | Why and how to collect data? TBC
- 09:25–10:05 | Group work I: how to collect data?
- 10:05–10:15 | Lessons learned from data-driven transformation of mobility solutions near Pääskyvuori school Anna-Kaisa Montonen, City of Turku, Finland
- 10:15-10:25 | Lessons learned from school campaign – camera AI as a data source Justyna Suchanek, City of Gdynia, Poland
- 10:25-10:35 | Break
- 10:35-11:05 | Sharing & Reflections
- 11:05–11:20 | Group work II: how to collect data?
- 11:20–11:30 | Wrap-Up & Next Steps.
Background & additional materials
Supporting and encouraging cycling in sustainable urban mobility planning developed by the European Cyclists’ Federation (Küster, F. 2019)
This guideline highlights the importance of data collection in planning, implementing, and evaluating cycling policies within Sustainable Urban Mobility Planning (SUMP). It outlines key data types, such as usage patterns, infrastructure conditions, and safety metrics, and provides practical methods for data collection, including traditional surveys and modern GPS tracking tools. By leveraging reliable data, cities can optimise cycling infrastructure, measure policy impact, and promote active mobility effectively.
Supporting and encouraging walking in sustainable urban mobility planning developed by WALK21 Foundation (Walker, J., Thornton, B. & Quinores, L. 2019)
This guideline emphasizes the importance of integrating walking into Sustainable Urban Mobility Planning (SUMP) through effective data collection and analysis.
It highlights walking as a fundamental mode of mobility that contributes to sustainability, public health, equity, and urban liveability.
The document provides practical insights into collecting data on walking, including modal share, infrastructure quality, and pedestrian needs, to inform evidence-based decision-making.
It also outlines successful case studies from European cities, showcasing how data-driven approaches have improved walkability and supported active mobility.
This resource serves as a valuable tool for understanding the role of data in planning for walking and creating healthier, more sustainable urban environments.
International Walking Data Standard developed by WALK21 Foundation (Sauter, D., Tight, M., Pharoah, T., Martinson, R. & Wedderburn, M. 2016)
This standard provides guidance that ensures all travel surveys provide a complete and accurate mobility data collection which allows for comparisons between cities and countries. It was launched at the Walk21 conference in Vienna in October 2015.
Access the guidance
Year-Round Active Mobility Monitoring Guidance user manual developed by the Interreg BSR project BATS (2024)
The YRAM Monitoring Guidance is designed to assist public authorities in effectively monitoring active mobility and evaluating the impact of various interventions. This guidance focuses on identifying the necessary data required to estimate key performance indicators (KPIs) and methodologies for assessing these KPIs.
Exercises
Coming soon…