  Intensive development of urban systems creates a number of challenges for
urban planners and policy makers in order to maintain sustainable growth.
Running efficient urban policies requires meaningful urban metrics, which could
quantify important urban characteristics including various aspects of an actual
human behavior. Since a city size is known to have a major, yet often
nonlinear, impact on the human activity, it also becomes important to develop
scale-free metrics that capture qualitative city properties, beyond the effects
of scale. Recent availability of extensive datasets created by human activity
involving digital technologies creates new opportunities in this area. In this
paper we propose a novel approach of city scoring and classification based on
quantitative scale-free metrics related to economic activity of city residents,
as well as domestic and foreign visitors. It is demonstrated on the example of
Spain, but the proposed methodology is of a general character. We employ a new
source of large-scale ubiquitous data, which consists of anonymized countrywide
records of bank card transactions collected by one of the largest Spanish
banks. Different aspects of the classification reveal important properties of
Spanish cities, which significantly complement the pattern that might be
discovered with the official socioeconomic statistics.
