  High-quality data on existing bicycle infrastructure are a requirement for
evidence-based bicycle network planning, which supports a green transition of
human mobility. However, this requirement is rarely met: Data from governmental
agencies or crowdsourced projects like OpenStreetMap often suffer from unknown,
heterogeneous, or low quality. Currently available tools for road network data
quality assessment often fail to account for network topology, spatial
heterogeneity, and bicycle-specific data characteristics. To fill these gaps,
we introduce BikeDNA, an open-source tool for reproducible quality assessment
tailored to bicycle infrastructure data with a focus on network structure and
connectivity. BikeDNA performs either a standalone analysis of one data set or
a comparative analysis between OpenStreetMap and a reference data set,
including feature matching. Data quality metrics are considered both globally
for the entire study area and locally on grid cell level, thus exposing spatial
variation in data quality. Interactive maps and HTML/PDF reports are generated
to facilitate the visual exploration and communication of results. BikeDNA
supports quality assessments of bicycle infrastructure data for a wide range of
applications -- from urban planning to OpenStreetMap data improvement or
network research for sustainable mobility.
