  The knowledge of city exploration trails of people is in short supply because
of the complexity in defining meaningful trails representative of individual
behaviours and in the access to actionable data. Existing datasets have only
recorded isolated check-ins of activities featured by opaque venue types. In
this paper, we fill the gaps in defining what is a semantic trail of city
exploration and how it can be generated by integrating different data sources.
Furthermore, we publicly release two datasets holding millions of semantic
trails each and we discuss their most salient characteristics. We finally
present an application using these datasets to build a recommender system meant
to guide tourists while exploring a city.
