I'm currently looking into real-world networks which can be well approximated by interval graphs. It seems natural to suspect that networks that have constraints forcing them to be approximately physically linear could be well approximated by interval graphs.
For example, the highway system of the south island of New Zealand forms a network where geographical constraints force the network to have a natural linearity.
However, if I were to use this network, it looks like I would need to key in each of the highway intersections by hand.
In another attempt, I tried using the C. elegans neural network, thinking the physical linearity of the worm would force the network to be linear. Unfortunately, this research was thwarted by long head-to-tail neurons with large numbers of synapses (see my cogsci.SE question).
Question: Where can I access a real-world network which has an approximately linear structure (possibly due to some physical constraints)?
The network should be in a format that should be computer-readable.