Towards user-centric data management: individual mobility analytics for collective services

Abstract

We are under the big data microscope, and our digital traces are an inestimable source of awareness to deeply understand mobility phenomena as well as economic trends, social relationships and so on. Setting the focus of the big data microscope to capture human systematic behavior is surely a promising direction. The proposed vision is a methodological framework aimed to deal with intelligent personal data store that are able to automatically perform individual data mining, and that can provide proactive suggestions and support decisions, allow to share individual profiles in order to reach a level of knowledge comparable to those belonged to a collective system, and suggest interactions between individual and collective data mining in order to overtake the level of complex society knowledge extracted by the state-of-art methods. The study of individuals profiles, and the comparison and interactions with collective patterns, is dramatically helpful both for the novel detailed information retrieved through the methodological framework and for the possibility to deal at the same time with privacy issues.