dimacs10_roads — OpenStreetMap road networks of Europe and Asia (DIMACS10, 2010)

Description

Road networks of Europe, Asia and six European countries, extracted from OpenStreetMap (OSM) by M. Kobitzsch (Karlsruhe Institute of Technology) for the 10th DIMACS Implementation Challenge on graph partitioning and graph clustering (2011–2012). The OSM data were downloaded from Geofabrik on March 23–24, 2010; all routable streets were extracted (the OSM ways tagged motorway, trunk, primary, secondary and tertiary, with their links, and residential, unclassified, road, living_street and service), and the largest strongly connected component of the resulting directed road graph was kept, without self-loops and parallel edges. The networks are the undirected and unweighted versions of these components (a one-way street becomes an undirected edge).

A node is a point of a road (an OSM node: an intersection, or a point along the course of a road), and an edge is a road segment between two consecutive points. Since the points along the course of roads are kept, most nodes have degree two. There is one network for each region: europe, asia, belgium, germany, great_britain, italy, luxembourg and netherlands; the countries are separate extracts, which overlap with the europe network.

The networks have the following properties:

(Node) latitude and longitude: the geographical position of the node (the coordinate files of the challenge give them in units of $10^{-5}$ degrees, with the latitudes shifted by one degree, which is corrected here; e.g. the end of the road at the North Cape, at 71.169° N, appears at 72.169°).

Tags

Transportation Roads Spatial Unweighted

Added

2026-10-27

Citation

D. A. Bader, H. Meyerhenke, P. Sanders, D. Wagner (eds.), "Graph Partitioning and Graph Clustering. 10th DIMACS Implementation Challenge Workshop." Contemporary Mathematics 588, American Mathematical Society (2013) 10.1090/conm/588 Sci-Hub

Upstream URL OK

https://sites.cc.gatech.edu/dimacs10/archive/streets.shtml
https://www.openstreetmap.org

Networks

Tip: click on a column header to sort the list, or hover over it 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	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$\oslash$	$S$	Kind	Mode	NPs	gt	GraphML	GML	csv
europe	50,912,018	54,054,660	2.12	0.48	3.63	10917479.12	0.18	30,102	1.00	Undirected	Unipartite	latitude longitude	382.4 MiB	542.3 MiB	498.6 MiB	711.7 MiB
asia	11,950,757	12,711,603	2.13	0.48	2.89	10379862.39	0.34	48,125	1.00	Undirected	Unipartite	latitude longitude	84.5 MiB	124.8 MiB	119.1 MiB	163.5 MiB
belgium	1,441,295	1,549,970	2.15	0.49	2.58	4520523.52	0.10	1,987	1.00	Undirected	Unipartite	latitude longitude	10.0 MiB	15.6 MiB	14.6 MiB	19.9 MiB
germany	11,548,845	12,369,181	2.14	0.53	3.24	10656658.30	0.07	6,322	1.00	Undirected	Unipartite	latitude longitude	86.0 MiB	126.7 MiB	119.4 MiB	162.6 MiB
great_britain	7,733,822	8,156,517	2.11	0.54	2.95	12300738.57	0.03	9,339	1.00	Undirected	Unipartite	latitude longitude	55.8 MiB	82.6 MiB	78.0 MiB	106.1 MiB
italy	6,686,493	7,013,978	2.10	0.41	2.78	8558104.97	0.25	13,108	1.00	Undirected	Unipartite	latitude longitude	44.8 MiB	67.5 MiB	64.8 MiB	89.3 MiB
luxembourg	114,599	119,666	2.09	0.41	2.21	1616851.04	0.10	1,337	1.00	Undirected	Unipartite	latitude longitude	2.3 MiB	3.1 MiB	3.1 MiB	3.2 MiB
netherlands	2,216,688	2,441,238	2.20	0.58	2.51	5255376.19	0.10	2,553	1.00	Undirected	Unipartite	latitude longitude	15.0 MiB	24.7 MiB	23.3 MiB	28.6 MiB