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london_transport — London Transport Network

Description

Multiplex network of the train stations of London, assembled by M. De Domenico and collaborators. The data were collected in 2013 from the official website of Transport for London (TfL) and manually cross-checked. Nodes are stations of the London Underground, London Overground and Docklands Light Railway (DLR), and edges connect consecutive stations along a line. The network has three layers: (1) the Underground, where the networks of all eleven Tube lines are aggregated into a single layer, (2) the Overground, and (3) the DLR. Edges are undirected.

The network has the following properties:

  • name, nodeLabel: the station name (lowercase, without spaces, as in "bakerstreet").
  • nodeLat, nodeLong: the latitude and longitude of the station, in degrees.
  • layer: the layer of the edge, with 1 = Tube, 2 = Overground, 3 = DLR (see the graph property layer_key).
  • weight: the number of distinct lines connecting the two stations in that layer (e.g. two adjacent stations served by both the Circle and the District line have weight 2 in the Tube layer).
Tags
Transportation Public Transport Multilayer Weighted
Citation
  • Manlio De Domenico, Albert Solé-Ribalta, Sergio Gómez, and Alex Arenas, "Navigability of interconnected networks under random failures." PNAS 111, 8351-8356 (2014) 10.1073/pnas.1318469111 Sci-Hub
Upstream URL OK
https://manliodedomenico.com/data.php
Upstream license
Open Data Commons Open Database License (ODbL), https://opendatacommons.org/licenses/odbl/
Networks
Tip: hover over a column header for a description.
Column legend
$\left<k\right>$
Mean degree
$\sigma_k$
Standard deviation of the degrees
$\lambda_h$
Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$
Random walk mixing time
$r$
Degree assortativity
$c$
Global clustering coefficient
$\oslash$
(Pseudo-) diameter
$S$
Relative size of the largest component
NPs
Node properties
EPs
Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
london_transport 369 441 2.39 1.07 2.42 289.34 0.17 0.05 39 1.00 Undirected Unipartite name nodeLabel nodeLat nodeLong weight layer 15 KiB 20 KiB 19 KiB 17 KiB
Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.