01603nas a2200193   4500008004100000245007700041210006900118260001300187520097300200100002301173700001901196700002101215700001701236700002401253700002001277700002101297700002401318856006701342       2018                        eng d00aDiscovering Mobility Functional Areas: A Mobility Data Analysis Approach0 aDiscovering Mobility Functional Areas A Mobility Data Analysis A  bSpringer3 aHow do we measure the borders of urban areas and therefore decide which are the functional units of the territory? Nowadays, we typically do that just looking at census data, while in this work we aim to identify functional areas for mobility in a completely data-driven way. Our solution makes use of human mobility data (vehicle trajectories) and consists in an agglomerative process which gradually groups together those municipalities that maximize internal vehicular traffic while minimizing external one. The approach is tested against a dataset of trips involving individuals of an Italian Region, obtaining a new territorial division which allows us to identify mobility attractors. Leveraging such partitioning and external knowledge, we show that our method outperforms the state-of-the-art algorithms. Indeed, the outcome of our approach is of great value to public administrations for creating synergies within the aggregations of the territories obtained.1 aGabrielli, Lorenzo1 aFadda, Daniele1 aRossetti, Giulio1 aNanni, Mirco1 aPiccinini, Leonardo1 aPedreschi, Dino1 aGiannotti, Fosca1 aLattarulo, Patrizia  uhttps://link.springer.com/chapter/10.1007/978-3-319-73198-8_2701766nas a2200169   4500008004100000020001800041245007400059210006900133260005500202520117100257100002201428700001901450700002201469700001701491700002401508856006401532       2016                        eng d  a978889635488900aBig Data and Public Administration: a case study for Tuscany Airports0 aBig Data and Public Administration a case study for Tuscany Airp  aUgento, Lecce (Italy)bMatematicamente.itc06/20163 aIn the last decade, the fast development of Information and Communication Technologies led to the wide diffusion of sensors able to track various aspects of human activity, as well as the storage and computational capabilities needed to record and analyze them. The so-called Big Data promise to improve the effectiveness of businesses, the quality of urban life, as well as many other fields, including the functioning of public administrations. Yet, translating the wealth of potential information hidden in Big Data to consumable intelligence seems to be still a difficult task, with a limited basis of success stories. This paper reports a project activity centered on a public administration  - IRPET, the Regional Institute for Economic Planning of Tuscany (Italy). The paper deals, among other topics, with human mobility and public transportation at a regional scale, summarizing the open questions posed by the Public Administration (PA), the envisioned role that Big Data might have in answering them, the actual challenges that emerged in trying to implement them, and finally the results we obtained, the limitations that emerged and the lessons learned.1 aFurletti, Barbara1 aFadda, Daniele1 aPiccini, Leonardo1 aNanni, Mirco1 aLattarulo, Patrizia  uhttp://sebd2016.unisalento.it/grid/SEBD2016-proceedings.pdf