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Pawar0/ride-silver

RIDE Silver RIDE Silver is the cleaned relational release of the RIDE dataset. It contains Belgian passenger railway operations from 2023 to 2025, organized as event, journey, infrastructure, operational-point, and weather tables. This release is intended as a reusable intermediate data layer. It can be used to inspect the underlying railway data, build alternative train-delay prediction tasks, construct model-specific datasets, or reproduce the RIDE Gold benchmark releases.… See the full description on the dataset page: https://huggingface.co/datasets/Pawar0/ride-silver.

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Dataset Card

RIDE Silver

![arXiv](https://arxiv.org/abs/2606.05070) ![Code](https://github.com/orailix/ride)

RIDE Silver is the cleaned relational release of the RIDE dataset. It contains Belgian passenger railway operations from 2023 to 2025, organized as event, journey, infrastructure, operational-point, and weather tables.

This release is intended as a reusable intermediate data layer. It can be used to inspect the underlying railway data, build alternative train-delay prediction tasks, construct model-specific datasets, or reproduce the RIDE Gold benchmark releases.

Files

Path	Description
`events/events_YYYYMM.parquet`	Monthly train event records with train ID, service date, operation node, event type, planned and observed timestamps, line IDs, and delay in seconds.
`journeys/journeys_YYYYMM.parquet`	Monthly journey summaries with train-level metadata, start/end nodes, planned/observed start and end timestamps, event counts, delay summaries, and inferred paths.
`static/op_nodes.parquet`	Operational points with identifiers, names, types, latitude, and longitude.
`static/line_sections.parquet`	Railway line sections with geometry, line ID, endpoint operation nodes, number of tracks, and matched operation nodes.
`static/node_links.parquet`	Directed links between consecutive operation nodes with distances.
`static/weather.parquet`	Hourly weather variables aligned to operation nodes.
`metadata.yaml`	Build metadata.
`ride_silver_croissant.json`	Croissant metadata with schema, Responsible AI, and provenance information.

Coverage

—Time period: January 2023 to December 2025
—Operational points: 1,355
—Line sections: 1,212
—Node links: 1,797
—Events: 94.5M
—Journeys: 3.6M

Loading Example

python

import pandas as pd

events = pd.read_parquet("events/events_202501.parquet")
journeys = pd.read_parquet("journeys/journeys_202501.parquet")
op_nodes = pd.read_parquet("static/op_nodes.parquet")
node_links = pd.read_parquet("static/node_links.parquet")
weather = pd.read_parquet("static/weather.parquet")

Construction

RIDE Silver was generated with the RIDE data-processing pipeline from public railway and weather sources. See the code repository linked above for the construction code and manifests.

Notes

RIDE Silver contains operational railway records and weather observations. It does not intentionally contain passenger identities, employee identities, ticketing records, device identifiers, or direct personal information.

Responsible AI, provenance, and limitation metadata are provided in ride_silver_croissant.json.

Sources

RIDE Silver is derived from public railway and weather sources:

—Infrabel Open Data: https://infrabel.opendatasoft.com/pages/home/
—Open-Meteo: https://open-meteo.com/

When using RIDE Silver, please attribute RIDE, Infrabel Open Data, and Open-Meteo.

License

RIDE Silver is released under CC BY 4.0.

Citation

bibtex

@misc{elliker2026rideopendatasetbenchmark,
      title={RIDE: An Open Dataset and Benchmark for Train Delay Prediction},
      author={Clément Elliker and Mathis Le Bail and Clément Mantoux and Jesse Read and Sonia Vanier},
      year={2026},
      eprint={2606.05070},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2606.05070},
}