Datasets:

hulnegy
/

DisPatch70

license: other
license_name: mixed-open-data
license_link: https://github.com/MaxHalford/bike-sharing-history
pretty_name: DisPatch70
tags:
  - bike-sharing
  - urban-computing
  - spatio-temporal
  - time-series

DisPatch70

Aligned bike-share station status and trip records for 90+ cities, built for research on urban dispatch / rebalancing simulation. Status snapshots and trips share one directory layout, one file naming scheme, and explicit join keys.

Layout

gbfs/     <city>/<provider>/<YYYY>/<Mon>.parquet   station status, one row per station x ~15-min snapshot
tripdata/ <city>/<provider>/<YYYY>/<Mon>.parquet   trip records, one row per ride
station_dim/crosswalk.parquet                      station identity table
station_dim/snapshots/<city>/<provider>.parquet    sampled raw GBFS station_information over time

gbfs/.../2025/Mar.parquet and tripdata/.../2025/Mar.parquet cover the same city, provider and calendar month (UTC; trips are partitioned by started_at UTC to match the status feed's commit_at).

Coverage

gbfs/: 93 city/provider pairs in 24 countries, 2023-08 (older cities) or 2024-04 (cities added later) through 2026-07, ~15-minute resolution, 349M rows. Source: the public Parquet export of MaxHalford/bike-sharing-history (git-scraped GBFS feeds), re-encoded with alignment keys added.
tripdata/: the 12 cities whose operators publish trip records overlapping the status window: New York, Washington DC, Chicago, San Francisco Bay Area, Philadelphia, Montréal, Vancouver, Oslo, Bergen, Mexico City, Guadalajara, Buenos Aires (2023-01 → 2026-07/08 where published). Toronto publishes data but blocks non-North-American downloads; it will be added when fetched. All other systems (JCDecaux, Nextbike, Bird, Beryl, Tembici, Donkey Republic, and most municipal systems outside North America) do not publish trip-level records at all.

Alignment keys

key	gbfs/	tripdata/	note
station name	`station`	`start_gbfs_name` / `end_gbfs_name`	exact string match
GBFS station id	`station_id`	`start_station_id` / `end_station_id`	from `station_dim/crosswalk.parquet`; null for JCDecaux feeds (they publish no ids)
time	`commit_at` (UTC)	`started_at` / `ended_at` (UTC)	local wall time in `started_local`/`ended_local` + `tz`

start_match/end_match records how each trip endpoint was resolved: id (operator id ↔ crosswalk), name, coord (nearest station ≤ 60 m), or none. Trips with none and a null start_station_raw are dockless e-bike rides that genuinely have no station (~29% of DC and ~22% of Chicago rides); among station-referencing rides, resolution is ≥ 99.7% in every city.

gbfs/ schema

city, provider, station (name), longitude, latitude, commit_at (UTC), skipped_updates (consecutive unchanged frames before this row), bikes (available bikes), stands (available docks), station_id, capacity_ref (capacity from the crosswalk, last sampled value)

tripdata/ schema

Unified columns: city, provider, ride_id, started_at, ended_at (UTC), started_local, ended_local, tz, duration_s, start_station_raw / end_station_raw (operator's id, verbatim), start_station_name / end_station_name (as published), start_lat/lon, end_lat/lon, start_station_id / end_station_id, start_gbfs_name / end_gbfs_name, start_match / end_match, rideable_type, member_type, source_file, plus every unmapped source column verbatim as src_<original name> (string). Nothing from the original files is dropped.

Per-city id resolution: Lyft cities (NYC/DC/Chicago/SF) match start_station_raw to GBFS short_name; Oslo/Bergen/Philadelphia/Buenos Aires by digits of station_id (YOS:Station:1009 ↔ 1009, bcycle_indego_3213 ↔ 3213, 277BAEcobici ↔ 277); Guadalajara by station_id; Mexico City by digits of short_name; Montréal by name; Vancouver by the leading 0001-style code.

events/ and event_briefings/

events/           <city>/<source>/<YYYY>.parquet   one row per public event (1,020,642 rows)
event_briefings/  <city>/<source>/<YYYY>.parquet   one LLM-written briefing per event row

events/ unifies public-event records overlapping the status window (2023-01 → 2026-08): city permit/calendar datasets (NYC permitted events incl. street closures, Chicago park permits, SF street closures, Montréal public events, Buenos Aires mass-event permits), ESPN scoreboards for ten leagues matched to venues in the twelve cities, and national public holidays. Columns: city, source, source_id, category (sports / concert / festival / parade / street_closure / civic / holiday / other), title, description, venue_name, lat, lon, start_utc, end_utc, start_local, end_local, tz, expected_attendance, status plus every source column verbatim as src_<name>. Time precision differs by source (games to the minute, permits as start/end spans, holidays all-day). Coverage is uneven by design: five cities have municipal permit data, all twelve have sports and holidays.

event_briefings/ turns each event row into a 1–3 sentence operational briefing for a dispatcher (where, when, how large, what it means for bike traffic), generated offline with Qwen3-14B from the prompt in the code repository (prompts/event_briefing.md). Columns: city, source, source_id, start_local, description, model, prompt_version; join back to events/ on (city, source, source_id, start_local). Descriptions use only the fields of the record; records the model failed to describe are absent rather than filled.

station_dim/

crosswalk.parquet: one row per (city, provider, station): station_id, first_seen, last_seen, n_snapshots, name_last, names_seen (JSON list of every name observed), short_name, legacy_id, external_id, lat, lon, capacity, region_id, station_type. Built by sampling the source repo's git history on the 1st and 15th of each month (52 snapshots, 3,003 blobs).

Caveats

The source git history is nearly empty 2024-02 → 2024-12 and 2025-07 (the archive author squashed it); station identities in those windows come from neighbouring snapshots.
JCDecaux feeds publish no station ids; join those 22 cities by name, or by the numeric prefix many names carry ("1001 - TERREAUX").
Vancouver trip times are rounded to the hour by the operator (privacy). 2024-02 was published as XLSX and converted to CSV before parsing.
Trips whose local timestamp is ambiguous/nonexistent at DST transitions have started_at = NaT and were dropped (≲ 0.1%; counts in the processing logs).
Buenos Aires 2023 has a stray index column preserved as src_ field; formats drift across years in several cities — source_file tells you which raw file each row came from.
gbfs/ timestamps are commit times of the scraper (~every 15 min), not last_reported.

Provenance & licenses

Status: MaxHalford/bike-sharing-history (git scraping of public GBFS/JCDecaux feeds; cite the repo). Trips: the operators' open-data programs (Lyft system-data terms for NYC/DC/Chicago/SF; city open-data licenses for the rest). This dataset redistributes and re-encodes those public files; original values are preserved verbatim in *_raw, *_name and src_* columns.