  Cycling is an effective solution for making urban transport more sustainable.
However, bicycle networks are typically developed in a slow, piecewise process
that leaves open a large number of gaps, even in well developed cycling cities
like Copenhagen. Here, we develop the IPDC procedure (Identify, Prioritize,
Decluster, Classify) for finding the most important missing links in urban
bicycle networks, using data from OpenStreetMap. In this procedure we first
identify all possible gaps following a multiplex network approach, prioritize
them according to a flow-based metric, decluster emerging gap clusters, and
manually classify the types of gaps. We apply the IPDC procedure to Copenhagen
and report the 105 top priority gaps. For evaluation, we compare these gaps
with the city's most recent Cycle Path Prioritization Plan and find
considerable overlaps. Our results show how network analysis with minimal data
requirements can serve as a cost-efficient support tool for bicycle network
planning. By taking into account the whole city network for consolidating urban
bicycle infrastructure, our data-driven framework can complement localized,
manual planning processes for more effective, city-wide decision-making.
