Geographic representations of networks, such as transport networks, typically consist of end-point, junctions and simply-connected nodes. Where a simply-connected node is a node which is only connected to two other nodes. Typically OSM networks consist of a large number of simply-connected nodes with a smaller number of end-point or simply-connected nodes.

This approach looks to disaggregate, or break up, of OSM transport-network data into its consitutent edges and reassembly of a simplified network through the removal of duplicate or parallel edges, and combining simply-connected nodes. For example, based on analysis of a OSM British rail-network data shows 497 359 nodes with 506 337 edges 1 012 604 segments 925 172 (91.4%) are simply-connected.

More details about the implementation is given here

To extract and process the data is dependant on the following tools:

• python3
• pandas and numpy python3 packages for simplification
• matplotlib and networkx python3 packages for visualisation

    $ ./run.sh

Executing the run.sh script runs the simplication and visualisation of the testedges.tsv data-set, creating simplified network and visualises this using the networkx module

Running the junction.py script to converts the examples in the testedges.tsv into the simplified testsegments-files.ndjson data as follows:

   $ ./junction.py --tsv testedges.tsv testsegments-file.ndjson

Running the plot-graph.py script as follows creates .svg visualisations of the test and simplified networks in the images directory graph.html

   $ ./plot-graph.py --tsv testedges.tsv
   $ ./plot-graph.py --json testsegments-file.ndjson

Additional graphs used in the graphs.html are then generated as:

    $ ./plot-graph.py --tsv example-edges.tsv
    $ ./plot-graph.py --json example-segments.ndjson

The graph.html (and graph.md) is generated from the graph.yaml file using the output-html.py script from the goldfinch/markdown