  In the context of Smart Cities, indicator definitions have been used to
calculate values that enable the comparison among different cities. The
calculation of an indicator values has challenges as the calculation may need
to combine some aspects of quality while addressing different levels of
abstraction. Knowledge graphs (KGs) have been used successfully to support
flexible representation, which can support improved understanding and data
analysis in similar settings. This paper presents an operational description
for a city KG, an indicator ontology that support indicator discovery and data
visualization and an application capable of performing metadata analysis to
automatically build and display dashboards according to discovered indicators.
We describe our implementation in an urban mobility setting.
