The planning and evaluation of cycling infrastructure increasingly depend on demand-oriented data sources, including digital datasets such as GPS trajectories. While these new forms of data offer substantial analytical potential, their non-probabilistic nature raises concerns regarding data quality and representativeness, particularly when applied to modelling cycling behavior or assessing policy interventions. Existing validation efforts highlight that each data source-whether household travel surveys (HTS), permanent counts, or GPS tracking-contains inherent limitations, underscoring the need for systematic evaluation. In light of the growing reliance on GPS-based data from the nationwide CITY CYCLING (CC) campaign in Germany and the corresponding questions from practitioners about its representativeness, we seek to assess the validity of digital datasets within applied planning contexts.