  Multimodal transportation systems can be represented as time-resolved
multilayer networks where different transportation modes connecting the same
set of nodes are associated to distinct network layers. Their quantitative
description became possible recently due to openly accessible datasets
describing the geolocalised transportation dynamics of large urban areas.
Advancements call for novel analytics, which combines earlier established
methods and exploits the inherent complexity of the data. Here, our aim is to
provide a novel user-based methodological framework to represent public
transportation systems considering the total travel time, its variability
across the schedule, and taking into account the number of transfers necessary.
Using this framework we analyse public transportation systems in several French
municipal areas. We incorporate travel routes and times over multiple
transportation modes to identify efficient transportation connections and
non-trivial connectivity patterns. The proposed method enables us to quantify
the network's overall efficiency as compared to the specific demand and to the
car alternative.
