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Computer Science - Information Systems and Applications | EPJ Data Science - a SpringerOpen journal (Societies)

EPJ Data Science

EPJ Data Science

Editors-in-Chief: F. Schweitzer; A. Vespignani

ISSN: 2193-1127 (electronic version)

Journal no. 13688

Copublished by the Italian Physical Society, EDP Sciences and Springer 

Italian Physical Society

Società Italiana di Fisica
The Italian Physical Society (SIF - Società Italiana di Fisica), founded in 1897 is a non-profit association with the aim to promote, favour and protect the progress of Physics in Italy and worldwide. SIF represents the Italian scientific community, in the research, the educational and professional fields, either private or public, relative to all areas of Physics and its applications (Medicine, Biology, Informatics, Economics and Finance, Meteorology and Climate, Environment, Archeometry, Cultural Heritage and others).

EDP Sciences

Logo EDPscience
EDP Sciences (Édition Diffusion Presse Sciences), a subsidiary of several learned societies, works closely with the scientific world. It specializes in the communication and dissemination of scientific information to specialist audiences alike (general public, decision makers, teachers…). EDP Sciences produces and publishes international journals, books and internet sites with a predominantly scientific or technical content.

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  • Aims and Scope

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    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:

      • how to extract meaningful data from systems with ever increasing complexity
      • how to analyse them in a way that allows new insights
      • how to generate data that is needed but not yet available
      • how to find new empirical laws, or more fundamental theories, concerning how any natural or artificial (complex) systems work

    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.

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