Published on: 27 July 2016
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Published on: 27 July 2016
Published on: 26 July 2016
Published on: 7 July 2016
Published on: 18 June 2016
Published on: 14 June 2016
Published on: 5 August 2015
Published on: 18 June 2012
Published on: 22 April 2015
Published on: 25 June 2012
Published on: 25 October 2014
EPJ is a rapidly growing series of internationally reputed, peer-reviewed journals that are indexed in all major citation databases. The editorial boards of the EPJ are composed of leading specialists in their respective fields and have made it their mission to uphold the highest standards of scientific quality in the journals. EPJ started in the late 1990s as a merger and co-publication of Zeitschrift für Physik (Springer), Journal de Physique (EDP Sciences) and Il Nuovo Cimento (Società Italiana di Fisica) covering all aspects of the pure and applied physical sciences. Its spectrum has since expanded to encompass many interdisciplinary topics, including complexity and data sciences.
Advances in data-driven computational social sciences
Collection published: 22 February 2016
Making Big Data work: Smart, Sustainable, and Safe Cities
Collection published: 28 January 2015
See all article collections here.
The 21st century is currently witnessing the establishment of data-driven science as a complementary approach to the traditional hypothesis-driven method. This (r)evolution accompanying the paradigm shift from reductionism to complex systems sciences has already largely transformed the natural sciences and is about to bring the same changes to the techno-socio-economic sciences, viewed broadly.
EPJ Data Science offers a publication platform to address this evolution by bringing together all academic disciplines concerned with the same challenges:
This is accomplished through experiments and simulations, by data mining or by enriching data in a novel way. The focus of this journal is on conceptually new scientific methods for analyzing and synthesizing massive data sets, and on fresh ideas to link these insights to theory building and corresponding computer simulations. As such, articles mainly applying classical statistics tools to data sets or with a focus on programming and related software issues are outside the scope of this journal.
EPJ Data Science covers a broad range of research areas and applications and particularly encourages contributions from techno-socio-economic systems, where it comprises those research lines that now regard the digital “tracks” of human beings as first-order objects for scientific investigation. Topics include, but are not limited to, human behavior, social interaction (including animal societies), economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting up to and including policy advice.