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.

翻译：高质量自行车基础设施数据是基于证据进行自行车网络规划的前提，而此类规划有助于推动人类出行方式的绿色转型。然而，这一前提往往难以实现：政府机构或OpenStreetMap等众包项目的数据常存在未知性、异质性或低质量问题。现有道路网络数据质量评估工具通常未能考虑网络拓扑结构、空间异质性及自行车专有数据特征。为填补这些空白，我们推出BikeDNA——一款面向自行车基础设施数据的可复现质量评估开源工具，重点关注网络结构与连通性。BikeDNA支持单一数据集的独立分析，或OpenStreetMap与参考数据集间的比较分析（含要素匹配）。数据质量指标既针对整个研究区域进行全局评估，也在网格单元层面进行局部分析，从而揭示数据质量的空间差异。工具可生成交互式地图及HTML/PDF报告，便于结果的可视化呈现与交流。BikeDNAC支持从城市规划、OpenStreetMap数据改进到可持续出行网络研究等多场景下的自行车基础设施数据质量评估。