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Making Big Data work: Smart, Sustainable, and Safe Cities

The exponential growth in streams of data sensing real world situations and human behaviors - including call detail records (CDRs), social media data (Twitter, Facebook, etc.), traffic data, spending data, government data, satellite data, and others - provides opportunities for carrying out new research and to deal with fundamental problems such as urban planning, healthy living, epidemic prediction, crime prediction, emergency response planning, social dynamics understanding, etc. This thematic series focuses on analyzing the “digital breadcrumbs” people leave behind as they go about their daily lives to dynamically model aggregate human behavior and to learn how a society emerges from these “micro” interactions and how it evolves over time.

Edited by: Fabrizio Antonelli, Bruno Lepri, Alex 'Sandy' Pentland, Fabio Pianesi


  1. Content type: Editorial

    The goal of the present thematic series is to showcase some of the most relevant contributions submitted to the ‘Telecom Italia Big Data Challenge 2014’ and to provide a discussion venue about recent advances ...

    Authors: Bruno Lepri, Fabrizio Antonelli, Fabio Pianesi and Alex Pentland

    Citation: EPJ Data Science 2015 4:16

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  2. Content type: Regular article

    The high population density in cities confers many advantages, including improved social interaction and information exchange. However, it is often argued that urban living comes at the expense of reducing hap...

    Authors: Aamena Alshamsi, Edmond Awad, Maryam Almehrezi, Vahan Babushkin, Pai-Ju Chang, Zakariyah Shoroye, Attila-Péter Tóth and Iyad Rahwan

    Citation: EPJ Data Science 2015 4:7

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  3. Content type: Regular article

    Spatial variations in the distribution and composition of populations inform urban development, health-risk analyses, disaster relief, and more. Despite the broad relevance and importance of such data, acquiri...

    Authors: Rex W Douglass, David A Meyer, Megha Ram, David Rideout and Dongjin Song

    Citation: EPJ Data Science 2015 4:4

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  4. Content type: Regular article

    We analyse a large mobile phone activity dataset provided by Telecom Italia for the Telecom Big Data Challenge contest. The dataset reports the international country codes of every call/SMS made and received by m...

    Authors: Paolo Bajardi, Matteo Delfino, André Panisson, Giovanni Petri and Michele Tizzoni

    Citation: EPJ Data Science 2015 4:3

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  5. Content type: Regular article

    Human mobility in a city represents a fascinating complex system that combines social interactions, daily constraints and random explorations. New collections of data that capture human mobility not only help ...

    Authors: Manlio De Domenico, Antonio Lima, Marta C González and Alex Arenas

    Citation: EPJ Data Science 2015 4:1

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