  We propose here a methodology to help to understand the shortcomings of
public transportation in a city via the mining of complex networks representing
the supply and demand of public transport. We show how to build these networks
based upon data on smart card use in buses via the application of algorithms
that estimate an OD and reconstruct the complete itinerary of the passengers.
The overlapping of the two networks sheds light in potential overload and waste
in the offer of resources that can be mitigated with strategies for balancing
supply and demand.
