New EPJ Data Science thematic series on human mobility

1684177876 New EPJ Data Science thematic series on human mobility | kundaliniresearch

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

Bringing human mobility communities together

Human mobility is a research area that offers unique opportunities to apply new models and theories dealing with big data science and collective dynamics and to gain a better understanding of how people behave as individuals and as a society. The number of scientific publications on human mobility has been growing steadily over the last decade, with contributions from researchers from various disciplines speaking different languages ​​and looking at the problem from different perspectives.

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

How massive data has boosted the field over the past decade

The latest advances in human mobility have been triggered by the widespread use of mobile phones and GPS-enabled personal devices. The availability of accurate data such as the daily trajectories of millions of individuals has allowed researchers to test old theories and hypotheses regarding human mobility and to develop new models to accurately describe mobility behaviours.

Two major application domains have benefited from recent advances in human mobility: transportation and epidemic modeling. On the one hand, new methodologies have been developed to better estimate travel 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 more reliable estimates of epidemic pathways to be obtained. Other interesting applications include the use of mobility data to infer social variables such as well-being, unemployment, segregation.

The future of human mobility: shared economies?

New technologies are developing that could radically change the way we move in the coming decades. The spread of autonomous vehicles and shared economy concepts are likely to be game changers for private and public transport, with radical consequences for society, the economy and the environment.

How exactly will these transformations take place and how will mobility habits change in response to these new technologies? How will we solve the problems of massive pollution, congestion and urban sprawl in an automobile-centric society? Can we understand collective human behavior and design appropriate incentives for sustainable transport, in cities of any size?

While we don’t yet know the answers to these questions, we know what we need to find them: insightful data and intelligent models. This is a very exciting time to be researching human mobility and the future will be even more challenging.

Submit your work!

We want to promote new perspectives on the study of human mobility, as well as innovative approaches to urban planning, traffic forecasting, human mobility modeling and other related issues. For this reason, interdisciplinary opinions are particularly appreciated, such as studies that combine techniques from different fields related to the analysis of human mobility. While not mandatory, we encourage all 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 magazine website.


Guest editors

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

Philip Hoevel I am a physicist and a mathematician by training. Based at the Technische Universität Berlin, my group specializes in theoretical and computational studies of complex systems and networks in physics, biology and the social sciences. A particular focus is placed on the effects of time delay and non-linear dynamics that evolve on network structures and on applications to the spread of emerging infectious diseases and neurosciences.

Michael Szell I am an interdisciplinary researcher with a background in mathematics, computer science and physics; work on the quantification of human behavior, particularly in social networks and in urban mobility and sustainability. I’m particularly interested in the impact of new forms of transportation such as IT-enabled ride-sharing. I held positions at MIT’s Senseable City Lab and at the moovel lab, where I developed massively interactive data exploration platforms accompanying my research: hubcab (www.hubcab.org), What road!? (to be thrown at http://whatthestreet.moovellab.com)

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

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