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ZENODO
Dataset . 2018
Data sources: Datacite
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ZENODO
Dataset . 2018
Data sources: Datacite
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ZENODO
Dataset . 2018
Data sources: ZENODO
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ZENODO
Dataset . 2018
Data sources: Datacite
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ZENODO
Dataset . 2018
Data sources: ZENODO
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A Collection Of Public Transport Network Data Sets For 25 Cities

Authors: Rainer Kujala; Christoffer Weckström; Richard Darst;

A Collection Of Public Transport Network Data Sets For 25 Cities

Abstract

This dataset describes the public transport networks of 25 cities across the world in multiple easy-to-use data formats. These data formats include network edge lists, temporal network event lists, SQLite databases, GeoJSON files, and General Transit Feed Specification (GTFS) compatible ZIP-files. The source data for creating these networks has been published by public transport agencies according to the GTFS data format. To produce the network data extracts for each city, the original data have been curated for errors, filtered spatially and temporally and augmented with walking distances between public transport stops using data from OpenStreetMap. Cities included in this dataset version: Adelaide, Belfast, Berlin, Bordeaux, Brisbane, Canberra, Detroit, Dublin, Grenoble, Helsinki, Kuopio, Lisbon, Luxembourg, Melbourne, Nantes, Palermo, Paris, Prague, Rennes, Rome, Sydney, Toulouse, Turku, Venice, and Winnipeg. Contrary to the version 1.0 of this data set, this version (1.2) does not include the cities of Antofagasta and Athens, for which non-commercial usage of the data is not allowed. Contrary to previous versions of the data set (1.0 and 1.2), in this version (1.2) the temporal filtering of the data has been slightly adapted, so that the daily and weekly data extracts cover all trips departing between from 03 AM on Monday to 03 AM on Tuesday (daily extract) or 03 AM of the Monday next week (weekly extract). Additionally, a temporal network extract covering a full week of operations has been added for each city. Documentation of the data can be found in the Data Descriptor article published in Scientific Data: http://doi.org/10.1038/sdata.2018.89 When using this dataset, please cite also the above-mentioned paper.

The licensing terms are documented separately for each city.

Related Organizations
Keywords

public transport, transportation, GTFS, temporal network, transit, city, GeoJSON, network, General Transit Feed Specification, OpenStreetMap, GIS

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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