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EPJ Data Science

About:

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.

Journal Home:  Journal Homepage
Editor-in-Chief:  Markus Strohmaier,
scope:

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.

Print ISSN:

Print ISSN:  21931127

Electronic ISSN:  

Abstracting and Indexing:  Scopus SCience Citation Index Expanded
Imapct Factor 2020:  3.184
Subject Area and Category:   Computer Science Computer Science Applications Mathematics Computational Mathematics Modeling and Simulation
Publication Frequency:  
H Index:  34
Best Quartile:

Q1:  Modeling and Simulation

Q2:  

Q3:  

Q4:  

Journal Home:  Journal Homepage
Cite Score:  7.0
SNIP:  2.143
Journal Rank(SJR):  0.915
Guidelines for Authors:

EPJ Data Science Author Guidelines

Publisher & Country:

Publisher:  Springer Science and Business Media

Country:  United States