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EPJ Data Science

Publishing model:
Open access

Overview

EPJ Data Science is an open access journal focusing on new scientific methods for analyzing and synthesizing massive data sets to achieve new insights into societal phenomena

  • Covers extraction, analysis, and interpretation of data regarding complex systems.
  • Investigates new empirical laws concerning the function of complex systems.
  • Primarily targets techno-socio-economic systems, analyzing digital traces of human behavior as primary objects for investigation.
  • Provides a platform for discussing data-driven science in a wide range of research areas and applications.

Editors-in-Chief
  • David Garcia PhD
  • Yelena Mejova PhD

Societies and partnerships

Journal metrics

Journal Impact Factor
2.5 (2024)
5-year Journal Impact Factor
3.3 (2024)
Submission to first decision (median)
10 days
Downloads
943k (2025)

Call for papers

Latest articles

Journal updates

Journal information

Electronic ISSN
2193-1127
Co-Publisher information
EDP Sciences, Società Italiana di Fisica
Abstracted and indexed in
  1. ANVUR
  2. Baidu
  3. CLOCKSS
  4. CNKI
  5. CNPIEC
  6. Chinese Academy of Medical Science (CAMS)
  7. Current Contents/Engineering, Computing and Technology
  8. DBLP
  9. DOAJ
  10. Dimensions
  11. EBSCO
  12. EI Compendex
  13. Gale
  14. GoOA - The Chinese Academy of Sciences (CAS)
  15. Google Scholar
  16. INSPEC
  17. Japanese Science and Technology Agency (JST)
  18. Naver
  19. Norwegian Register for Scientific Journals and Series
  20. OCLC WorldCat Discovery Service
  21. Ovid Discovery
  22. Portico
  23. ProQuest
  24. SCImago
  25. SCOPUS
  26. Science Citation Index Expanded (SCIE)
  27. Social Science Citation Index
  28. TD Net Discovery Service
  29. WTI AG
  30. Wanfang
  31. eLibrary.ru
© Springer-Verlag GmbH Germany, part of Springer Nature

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