TY - JOUR T1 - Human migration: the big data perspective JF - International Journal of Data Science and Analytics Y1 - 2020 A1 - Alina Sirbu A1 - Andrienko, Gennady A1 - Andrienko, Natalia A1 - Boldrini, Chiara A1 - Conti, Marco A1 - Fosca Giannotti A1 - Riccardo Guidotti A1 - Bertoli, Simone A1 - Jisu Kim A1 - Muntean, Cristina Ioana A1 - Luca Pappalardo A1 - Passarella, Andrea A1 - Dino Pedreschi A1 - Pollacci, Laura A1 - Francesca Pratesi A1 - Sharma, Rajesh AB - How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing traditional and novel data sources and models at each phase. We concentrate on three phases of migration, at each phase describing the state of the art and recent developments and ideas. The first phase includes the journey, and we study migration flows and stocks, providing examples where big data can have an impact. The second phase discusses the stay, i.e. migrant integration in the destination country. We explore various data sets and models that can be used to quantify and understand migrant integration, with the final aim of providing the basis for the construction of a novel multi-level integration index. The last phase is related to the effects of migration on the source countries and the return of migrants. SN - 2364-4168 UR - https://link.springer.com/article/10.1007%2Fs41060-020-00213-5 JO - International Journal of Data Science and Analytics ER - TY - JOUR T1 - (So) Big Data and the transformation of the city JF - International Journal of Data Science and Analytics Y1 - 2020 A1 - Andrienko, Gennady A1 - Andrienko, Natalia A1 - Boldrini, Chiara A1 - Caldarelli, Guido A1 - Paolo Cintia A1 - Cresci, Stefano A1 - Facchini, Angelo A1 - Fosca Giannotti A1 - Gionis, Aristides A1 - Riccardo Guidotti A1 - others AB - The exponential increase in the availability of large-scale mobility data has fueled the vision of smart cities that will transform our lives. The truth is that we have just scratched the surface of the research challenges that should be tackled in order to make this vision a reality. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders in building knowledge discovery pipelines over such data sources. At the same time, this widespread data availability also raises privacy issues that must be considered by both industrial and academic stakeholders. In this paper, we provide a wide perspective on the role that big data have in reshaping cities. The paper covers the main aspects of urban data analytics, focusing on privacy issues, algorithms, applications and services, and georeferenced data from social media. In discussing these aspects, we leverage, as concrete examples and case studies of urban data science tools, the results obtained in the “City of Citizens” thematic area of the Horizon 2020 SoBigData initiative, which includes a virtual research environment with mobility datasets and urban analytics methods developed by several institutions around Europe. We conclude the paper outlining the main research challenges that urban data science has yet to address in order to help make the smart city vision a reality. UR - https://link.springer.com/article/10.1007/s41060-020-00207-3 ER -