Global Bike Parking Open Data: A Directory of 36+ Free Datasets

Every cyclist knows the feeling: you arrive at your destination and spend five minutes circling the block looking for somewhere to lock up. Bike parking may not be as glamorous as protected bike lanes or bike-share systems, but it’s a fundamental piece of cycling infrastructure — and one that’s increasingly well-documented through open data.

We’ve compiled a directory of 36+ open datasets across 12 countries that publish bicycle parking locations, capacity, and facility types as freely downloadable data. Whether you’re a city planner benchmarking your infrastructure, a developer building a cycling app, or a researcher studying urban mobility, this list is your starting point.

Why Bike Parking Data Matters

Bike parking isn’t just a convenience — it’s a determinant of whether people choose to cycle. A 2019 study published in Transport Reviews found that secure bike parking at destinations is one of the top factors influencing the decision to cycle for transport. Cities that can’t tell you where their bike racks are located almost certainly can’t tell you whether they have enough of them, or whether they’re in the right places.

Open data changes that equation. When parking locations, capacity, and facility types are published as machine-readable datasets, it becomes possible to:

• Identify gaps in bike parking coverage across a city
• Plan new installations based on demand and proximity analysis
• Build wayfinding tools that help cyclists find parking in real time
• Benchmark cities against each other on parking provision
• Track investment in cycling infrastructure over time

The Datasets

Below is every open bike parking dataset we’ve found, organised by region. Each entry includes the data formats available, the licence, and what fields you can expect to find.

Australia

Australia has some of the most granular bike parking data in the world, with datasets available at the state, city, and council level.

The Transport for NSW datasets are particularly valuable because they cover the state’s network of secure bike sheds at train stations — including usage data that shows how demand for secure parking has grown over time.

Brazil

Brazil’s cycling data ecosystem is growing rapidly, driven by municipal open data portals and community-led mapping efforts.

CicloMapa deserves special mention — it’s a community-driven, OSM-based national cycling map that aggregates bike parking (and other cycling infrastructure) across the entire country. It’s a model for how open community mapping can fill gaps that government data portals haven’t yet reached.

Italy

Italian cities are increasingly publishing cycling infrastructure data as part of broader smart city and open data initiatives.

Milan’s dataset is one of the most complete in Italy, with over 3,200 bike parking locations including capacity and type information. Trento stands out for using the CC0 (public domain) licence, making its data fully unrestricted for any use. Vicenza is a welcome addition — its municipal GIS portal offers multiple download formats including direct GeoJSON access.

Europe (Other)

Several European countries publish bike parking data at a national level — a significant advantage for cross-city analysis.

France’s national dataset is remarkable — it aggregates all bicycle parking from OpenStreetMap into a single, government-hosted download with consistent field names and a permissive licence. London’s Cycling Infrastructure Database goes further, including photographs of each parking facility alongside the location data.

Belgium’s Velopark takes a different approach, using JSON-LD (linked data) to describe bike parking facilities with rich metadata that can be integrated into journey planners and mobility platforms.

United States

US bike parking data is published at the city level, with several major cities offering well-maintained, frequently updated datasets.

New York City’s dataset is notable for being in the public domain — no attribution required, no restrictions on use. All five datasets are available through Socrata or ArcGIS platforms with built-in APIs, making them easy to integrate programmatically.

Global: OpenStreetMap

The single most comprehensive source of bike parking data worldwide is OpenStreetMap (OSM). Contributors have mapped hundreds of thousands of bicycle parking facilities across every continent, tagged with capacity, type (stands, lockers, shed, bollard), access restrictions, and more.

You can query OSM bike parking data using the Overpass Turbo query tool. A simple query like this returns all bike parking in a bounding box:

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[out:json];
node["amenity"="bicycle_parking"]({{bbox}});
out body;

OSM data is licensed under the Open Database License (ODbL), which requires attribution and share-alike for derivative databases. For many applications — including cycling apps, research, and urban planning — this is the most practical starting point, especially in cities that don’t publish their own open data.

What Makes a Good Bike Parking Dataset?

Not all datasets are created equal. The most useful ones share a few characteristics:

1. Location precision — Coordinates accurate to the individual rack, not just the street or block
2. Capacity — How many bikes can be parked, not just that parking exists
3. Type classification — Racks, lockers, cages, and sheltered parking serve different needs
4. Freshness — Data that’s updated regularly as new racks are installed or removed
5. Open licence — CC BY, CC0, ODbL, or public domain — licences that allow reuse without friction
6. Machine-readable formats — GeoJSON, CSV, or API access, not just PDFs or web maps

The best datasets in this directory — France’s national aggregation, London’s CID, Milan’s bike parking, and the major US city portals — hit most or all of these criteria.

Gaps and Opportunities

Despite the progress, there are significant gaps in the global picture:

• Africa, South Asia, and Southeast Asia are almost entirely absent from open bike parking data. Cities like Bogota, Jakarta, and Nairobi have growing cycling populations but limited open data infrastructure.
• Capacity data is missing from many datasets — you can find the location of a rack but not how many bikes it holds.
• Real-time availability is virtually non-existent. A few cities track bike-share dock availability in real time, but no open dataset we’ve found reports real-time occupancy of public bike racks.
• Standardisation remains a challenge. Every dataset uses different field names, type classifications, and coordinate formats. There’s no equivalent of GTFS (General Transit Feed Specification) for bike parking.

A shared specification for bike parking data — call it GBPS (General Bike Parking Specification) — would dramatically reduce the friction of working with these datasets and enable cross-city comparisons at scale.

How Party Onbici Uses Open Data

At Party Onbici, we believe that open cycling data is the foundation for better cycling cities. Our platform collects ride data from group cycling events and makes it available to city planners — showing not just where people ride, but where they start and end their journeys.

Bike parking data is a natural complement to ride data. When you combine where people ride with where they can (and can’t) park, you get a much clearer picture of where infrastructure investment will have the greatest impact.

If your city publishes bike parking data and it’s not on this list, or if you know of a dataset we’ve missed, get in touch. We’ll keep this directory updated as new datasets become available.

Want to help build better cycling data for your city? Download Party Onbici and start recording your rides. Every trip you log helps planners understand where cycling infrastructure is needed most — including bike parking.