I'm writing a paper for an undergraduate economic history class and I'm interested in North American railways in the 1800's. I've found historical GIS data for the period here. The railroad data are KML files.
My idea is to analyze the railways using network/graph theory. Each station would be a node/vertex, and the edges would be the rail lines between each station. I could then use measures like closeness centrality to analyze the network structure.
To do so I would need to convert the KML files to basically a spreadsheet (i.e .csv) format giving the distance between each connected station, with row x column y giving the length of the rail line between station x and station x (an adjacency matrix).
Is it feasible to perform such a conversion?
My undergraduate degree is in economics and mathematics but I have experience with Python from data analysis and computer science courses. I don't have any direct GIS experience.