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

EPJ Data Science

EPJ Data Science

Editor-in-Chief: Markus Strohmaier

ISSN: 2193-1127 (electronic version)

Journal no. 13688

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EPJ Data Science is a peer-reviewed open access journal published under the SpringerOpen brand and spans a range of research areas with a focus on data-driven science

  • A platform for discussing the application of data-driven approaches across many disciplines with emphasis on techno-socio-economic systems 
  • Covers extraction, analysis, enrichment and interpretation of data regarding complex natural and artificial systems
  • Investigates new empirical laws, or more fundamental theories, concerning the function of complex systems
  • Free app available on iTunes and Google Play Store

EPJ Data Science is a platform for discussing the challenges of applying data-driven science to a range of research areas, with a focus on techno-socio-economic systems including human and animal social behavior and interaction, economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, and more.

Related subjects » Complexity - Computational Intelligence and Complexity - Information Systems and Applications

Impact Factor: 2.982 (2017) * 

Journal Citation Reports®

Abstracted/Indexed in 

Science Citation Index Expanded (SciSearch), Journal Citation Reports/Science Edition, Social Science Citation Index, Journal Citation Reports/Social Sciences Edition, SCOPUS, INSPEC, Google Scholar, Current Contents/Engineering, Computing and Technology, DBLP, DOAJ, EBSCO Applied Science & Technology Source, EBSCO Discovery Service, EBSCO STM Source, EBSCO TOC Premier, EI Compendex, OCLC WorldCat Discovery Service, ProQuest Advanced Technologies & Aerospace Database, ProQuest Agricultural & Environmental Science Database, ProQuest Biological Science Database, ProQuest Earth, Atmospheric & Aquatic Science Database, ProQuest Materials Science & Engineering Database, ProQuest Natural Science Collection, ProQuest SciTech Premium Collection, ProQuest Technology Collection, ProQuest-ExLibris Primo, ProQuest-ExLibris Summon

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  • Journal Citation Reports®
    2017 Impact Factor
  • 2.982
  • Aims and Scope

    Aims and Scope


    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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