Mobility, Data Mining and Privacy: A Vision of Convergence

The comprehension of phenomena related to movement – not only of people and vehicles but also of animals and other moving objects – has always been a key issue in many areas of scientific investigation or social analysis. The human geographer, for instance, studies the flows of migrant populations with reference to geography – places that are sources and destinations of migrations – and time. The historian, another example, studies military campaigns and related movements of armies and populations. (A famous instance is the depiction of Napoleon’s March on Moscow, published by C.J. Minard in 1861, discussed in Chap. 1 of this book (see Fig. 1.1); this figure represents with eloquence the fate of Napoleon’s army in the Russian campaign of 1812–1813, by showing the movement of the army together with its dramatically diminishing size during its advance and subsequent retreat.) The ethologist studies animal behaviour by the analysis of movement patterns, based on field observations or, sometimes, on data from tracking devices. Today, in the extremely complex social systems of the gigantic metropolitan areas of the twenty-first century, the observation of the movement patterns and behavioural models of people is needed for the traffic engineers and city managers to reason about mobility and its sustainability and to support decision makers with trustable knowledge. The very same knowledge about people movement and behaviour is precious for the urban planner, e.g. to localise new services, to organise logistics systems and for the timely detection of changes that occur in the movement behaviour. At a finer-grained spatial scale, movement in contexts such as a shopping area or a natural park is an interesting subject of investigation, either for commercial purposes, as in geo-marketing, or for improving the quality of service. In all the above cases, albeit so different from each other, two key problems recur: