New EPJ Data Science thematic series on human mobility

EPJ Data Science welcomes submissions to a new thematic series on Individual and Collective Human Mobility: Description, Modelling, Prediction. The team of guest editors behind the series talk about their vision and motivation to gather experts from different fields in the effort to better understand human behaviour. The deadline for submissions is 31 December 2017.


Guest post by Filippo Simini, Philipp Hövel, Michael Szell, Luca Pappalardo, Gourab Ghoshal

Bringing together the communities of human mobility

Human mobility is a research area that offers unique opportunities to apply novel models and theories that deal with big data science and collective dynamics, and to get a better understanding of how people behave as individuals and as a society. The number of scientific publications on human mobility has been growing constantly for the last decade, with contributions of researchers from various disciplines that speak different languages and look at the problem from different perspectives.

We think that this plurality of approaches is a value, because having multiple ways to describe something can only enrich our understanding and provide further insights. However, the diverse backgrounds of researchers working on human mobility can also hinder the spreading of ideas developed in different disciplines. We want this thematic series to be a venue to collect the latest advancements in the field and to facilitate the communication between the different communities working on human mobility.

How massive data has boosted the field in the last decade

The latest advancements in human mobility were triggered by the widespread diffusion of mobile phones and personal devices equipped with GPS. The availability of accurate data such as daily trajectories of millions of individuals has enabled researchers to test old theories and hypotheses regarding human mobility and to develop new models to accurately describe mobility behaviors.

Two main domains of application have benefited from the recent progress in human mobility: transportation and epidemic modelling. On the one hand, new methodologies have been developed to better estimate trip demand, improve traffic forecasting and make shared mobility more efficient.

On the other hand, realistic mobility behaviors have been included in large scale computational models of the spread of infectious diseases, allowing obtain more reliable estimates of the epidemic pathways. Other interesting applications include the use of mobility data to infer social variables such as wellbeing, unemployment, segregation.

The future of human mobility: sharing economies?

New technologies are being developed that could dramatically change the way we move within the next few decades. The diffusion of autonomous vehicles and concepts of shared economy will likely be game changers for private and public transportation, with sweeping consequences for society, the economy, and the environment.

How exactly will these transformations happen and how will mobility habits change in response to these new technologies? How will we solve the issues of massive pollution, congestion, and urban sprawl in a car-centric society? Can we understand collective human behavior and design proper incentives towards sustainable transportation, in cities of any scale?

Even if we don’t know the answers to these questions yet, we do know what we need to find them: detailed data and clever models. This is a very exciting time to do research in human mobility and the future will be even more challenging.

Submit your work!

We want to foster new perspectives on the study of human mobility, as well as innovative approaches to urban planning, traffic forecasting, human mobility modelling and other related issues. For this reason interdisciplinary views are particularly welcome, such as studies merging techniques from several fields related to human mobility analysis. Though it is not mandatory, we encourage all the authors to use open data or to share both the data and code they use for their experiments.

You can find more information about this thematic series and the submission process on the journal website.


The guest editors

Filippo Simini  I am a physicist with a background in statistical mechanics, stochastic processes, and complex networks. My work focuses on the analysis of empirical data to discover and characterize the distinctive statistical patterns of a system (e.g. scale invariance, presence of structures and motifs) and on the development of mathematical models to describe the system’s dynamics and emergent properties. I am particularly interested in interdisciplinary problems and applications, including collective and individual human mobility, transportation, ecological networks and population dynamics.

Philipp Hövel I am a physicist and mathematician by training. Based at Technische Universität Berlin, my group specializes in theoretical and computational studies of complex systems and networks in physics, biology, and social sciences. A particular focus is set on effects of time delay and nonlinear dynamics that evolve on network structures and applications to the spread of emergent infectious diseases and neuroscience.

Michael Szell I am an interdisciplinary researcher with a background in mathematics, computer science, and physics; working on quantification of human behavior, in particular in social networks and in urban mobility and sustainability. I am especially interested in the impact of novel forms of transportation such as IT-enabled ride-sharing. I held positions at MIT’s Senseable City Lab and at moovel lab, where I developed interactive, massive data exploration platforms accompanying my research: hubcab (, What the Street!? (to be launched at

Luca Pappalardo I am a data scientist with background in computer science, network science and data mining. Based at University of Pisa, my research focuses on the analysis of Big Data describing several aspects of human behavior, such as human mobility, social relationships, market purchases, and sports performance. A particular focus on my research now is the developing of spatio-temporal models of human mobility for realistic what-if analysis, simulation and prediction in urban scenarios.

Gourab Ghoshal I am a physicist based at the University of Rochester. My interests are interdisciplinary in nature ranging from non-equilibrium statistical physics, game theory, econophysics, dynamical systems and the origins of life. A particular focus of my group right now is to build phenomenological models of socio-economic entities with an emphasis on understanding the dynamics and evolution of urban systems.

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