  Cycling is a key ingredient for a sustainability shift of Denmark's
transportation system. To increase cycling rates, a better nationwide network
of bicycle infrastructure is required. Planning such a network requires
high-quality infrastructure data, however, the quality of bicycle
infrastructure data is severely understudied. Here, we compare Denmark's two
largest open data sets on dedicated bicycle infrastructure, OpenStreetMap (OSM)
and GeoDanmark, in a countrywide data quality assessment, asking whether data
is good enough for network-based analysis of cycling conditions. We find that
neither of the data sets is of sufficient quality, and that data set conflation
is necessary to obtain a complete dataset. Our analysis of the spatial
variation of data quality suggests that rural areas are more likely to suffer
from problems with data completeness. We demonstrate that the prevalent method
of using infrastructure density as a proxy for data completeness is not
suitable for bicycle infrastructure data, and that matching of corresponding
features thus is necessary to assess data completeness. Based on our data
quality assessment we recommend strategic mapping efforts towards data
completeness, consistent standards to support comparability between different
data sources, and increased focus on data topology to ensure high-quality
bicycle network data.
