EPJ Data Science

Scope & Guideline

Empowering Researchers with Cutting-edge Data Science

Introduction

Immerse yourself in the scholarly insights of EPJ Data Science with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN-
PublisherSPRINGER
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationEPJ DATA SCI / EPJ Data Sci.
Frequency1 issue/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressONE NEW YORK PLAZA, SUITE 4600 , NEW YORK, NY 10004, UNITED STATES

Aims and Scopes

The journal EPJ Data Science focuses on the intersection of data science with various domains, emphasizing empirical research methodologies and quantitative analysis. It seeks to advance the understanding of complex systems through data-driven approaches, fostering interdisciplinary collaboration and innovation.
  1. Interdisciplinary Data Science Research:
    Highlights the integration of data science methodologies across various fields such as social sciences, economics, urban studies, and public health.
  2. Quantitative Analysis and Empirical Methods:
    Emphasizes rigorous quantitative methods, including statistical modeling, machine learning, and network analysis to derive insights from data.
  3. Focus on Societal Challenges:
    Addresses pressing societal issues through data analysis, including public health, social media dynamics, and economic behavior, contributing to informed policy-making.
  4. Advancements in Computational Techniques:
    Showcases innovative computational techniques and tools, such as large language models and network embeddings, enhancing data analysis capabilities.
  5. Exploration of Human Behavior:
    Investigates human mobility, social interactions, and behavioral patterns using data-driven insights to understand complex social phenomena.
The journal EPJ Data Science is currently witnessing a dynamic evolution of themes, reflecting emerging trends in data science and its applications across various sectors. The following themes have gained traction in recent publications, indicating areas of heightened interest and research activity.
  1. Social Media Analysis and Misinformation:
    A growing emphasis on analyzing social media dynamics, misinformation campaigns, and their societal impacts, particularly in the context of recent geopolitical events.
  2. Human Mobility and Urban Dynamics:
    Increased focus on understanding human mobility patterns and their implications for urban planning and public health, especially in light of the COVID-19 pandemic.
  3. Artificial Intelligence and Ethics:
    Emerging discussions around AI ethics, transparency, and accountability, as researchers explore the implications of AI technologies in various applications.
  4. Network Science:
    A trend towards utilizing network science to understand complex interactions across social, economic, and biological systems, highlighting the interconnectedness of data.
  5. Sustainability and Environmental Impact:
    Growing interest in assessing sustainability through data science, including the analysis of environmental factors and their influence on social behaviors.

Declining or Waning

While EPJ Data Science continues to explore a wide array of topics, certain areas of focus appear to be diminishing in prominence over recent years. This decline may reflect shifts in research priorities or the maturation of methodologies.
  1. Traditional Statistical Methods:
    There is a noticeable reduction in the application of traditional statistical methods in favor of more advanced computational techniques and machine learning approaches.
  2. Isolated Case Studies:
    The journal has shifted towards broader analyses and comprehensive data-driven investigations rather than isolated case studies, which are becoming less frequent.
  3. Descriptive Analytics:
    A decline in purely descriptive analytics is observed as the journal increasingly favors predictive modeling and causal inference methodologies.
  4. Single-Domain Studies:
    Research that focuses exclusively on single domains without interdisciplinary connections appears to be waning, with a stronger emphasis on interdisciplinary approaches.

Similar Journals

Computational and Mathematical Methods

Fostering Collaboration for Groundbreaking Computational Research
Publisher: WILEY-HINDAWIISSN: Frequency: 1 issue/year

Computational and Mathematical Methods is a dynamic peer-reviewed journal published by Wiley-Hindawi, focusing on innovative research in the fields of computational mathematics, mechanics, and theory. Since its transition to an Open Access format in 2022, the journal has enhanced its accessibility to researchers and practitioners globally, providing a platform for the dissemination of high-quality studies that contribute to emerging developments in mathematical modeling and computational techniques. Based in the United Kingdom, this journal is committed to fostering collaboration amongst scholars, evidenced by its rankings within Scopus: Q3 in computational mathematics, computational mechanics, and computational theory and mathematics, reflecting its relevance and influence within these critical fields. With an emphasis on interdisciplinary studies, Computational and Mathematical Methods is an essential resource for researchers, professionals, and students seeking to expand their knowledge and apply cutting-edge methodologies to practical challenges.

SIAM Journal on Mathematics of Data Science

Bridging Theory and Application in Data Science
Publisher: SIAM PUBLICATIONSISSN: Frequency: 4 issues/year

SIAM Journal on Mathematics of Data Science is an esteemed publication within the fields of applied mathematics and data science, published by SIAM PUBLICATIONS. This journal serves as a vital platform for researchers and practitioners, dedicated to disseminating high-quality research that addresses complex mathematical problems arising in the context of data science. The journal aims to bridge the gap between rigorous mathematical theory and practical applications, fostering interdisciplinary collaboration among mathematicians, data scientists, and statisticians. With its commitment to excellence, the SIAM Journal on Mathematics of Data Science contributes significantly to advancing the understanding and development of mathematical methodologies that analyze and interpret large datasets effectively. Researchers and professionals will find it an invaluable resource with its comprehensive articles, insightful reviews, and original research papers, which represent the forefront of innovative mathematical approaches in the evolving landscape of data science. For those interested in contributing to this dynamic field, the journal provides an array of access options tailored to diverse audiences.

Data

Elevating standards in data research and dissemination.
Publisher: MDPIISSN: Frequency: 12 issues/year

Data is an innovative open-access journal published by MDPI, dedicated to advancing research and knowledge in the fields of Computer Science and Information Systems. Since its inception in 2016, Data has positioned itself as a prominent platform for disseminating high-quality research, currently boasting an impact factor reflective of its rigorous peer-review process and academic standards. Situated in Switzerland, the journal encompasses a broad scope of topics, making it an essential resource for researchers, professionals, and students alike. With a notable standing in multiple categories—including Q2 rankings in Information Systems and Information Systems and Management—the journal facilitates access to cutting-edge findings and methodologies that drive innovation in data management and analysis. Scholars are encouraged to utilize this open-access platform to share their findings and contribute to the collective understanding in these rapidly evolving fields.

JOURNAL OF INTELLIGENT INFORMATION SYSTEMS

Advancing the Frontiers of Intelligent Systems
Publisher: SPRINGERISSN: 0925-9902Frequency: 6 issues/year

The Journal of Intelligent Information Systems, published by Springer since 1992, is a premier academic journal that offers a multidisciplinary platform in the fields of Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture, Information Systems, and Software. With an impressive impact reflected in its 2023 Q2 category rankings across multiple domains and a commendable standing in the Scopus Rankings—ranking #84 in Computer Networks and Communications and #101 in Artificial Intelligence—the journal is recognized for its contribution to advancing knowledge and innovation. Although it is not an open-access journal, its accessibility through institutional subscriptions ensures that a wide range of researchers, professionals, and students can engage with high-quality, peer-reviewed research that addresses the latest advancements and trends in intelligent systems. For over three decades, this journal has effectively bridged gaps between academia and industry, making it a vital resource for those aiming to push boundaries in intelligent information systems.

Journal of Applied Mathematics & Informatics

Innovating Solutions through Applied Mathematics and Informatics.
Publisher: KOREAN SOC COMPUTATIONAL & APPLIED MATHEMATICS-KSCAMISSN: 2734-1194Frequency: 3 issues/year

Journal of Applied Mathematics & Informatics is a peer-reviewed academic journal published by the Korean Society of Computational & Applied Mathematics (KSCAM), focusing on the integration and application of mathematical theories and computational techniques across various domains. Established in 2019, this journal serves as a platform for researchers, professionals, and students to share innovative methodologies, practical applications, and theoretical advancements in fields like analysis, applied mathematics, and computational theory. As a Q4 ranked journal according to the 2023 category quartiles in analysis, applied mathematics, computational mathematics, and miscellaneous mathematics, it provides a valuable, albeit niche, contribution to the academic landscape. While the journal currently operates without open access options, it aims to disseminate quality research to foster collaboration and knowledge exchange within the mathematics and computer science communities. Researchers looking to explore emerging trends and methodologies in applied mathematics and informatics will find an essential resource in this journal, which is based in Daejeon, South Korea.

Computational and Mathematical Organization Theory

Revolutionizing organizational analysis through cutting-edge computational methods.
Publisher: SPRINGERISSN: 1381-298XFrequency: 4 issues/year

Computational and Mathematical Organization Theory, published by SPRINGER, is a prominent journal specializing in the intersection of mathematical and computational methodologies within organizational theory. With its ISSN 1381-298X and E-ISSN 1572-9346, this journal has established itself as a critical source of cutting-edge research since its inception in 1995 and continues to thrive with contributions spanning from 2005 to 2024. Noteworthy is its recognition in the 2023 quartile rankings, where it holds a Q2 status across multiple categories, such as Applied Mathematics, Computational Mathematics, and Decision Sciences, reflecting its broad analytical scope and the relevance of its findings to diverse fields. Furthermore, its Scopus rankings position it favorably within the academic community, underscoring its significant impact in Applied Mathematics (Rank #156/635), Computational Mathematics (Rank #59/189), and Modeling and Simulation (Rank #122/324). Although the journal is not open access, it provides crucial insights and methodologies that aid researchers and practitioners in enhancing organizational processes through mathematical and computational lenses. For scholars seeking to advance their understanding and application of these interdisciplinary approaches, Computational and Mathematical Organization Theory serves as an invaluable resource in the ever-evolving landscape of academic inquiry.

Advances in Data Science and Adaptive Analysis

Transforming Complex Data into Actionable Knowledge.
Publisher: WORLD SCIENTIFIC PUBL CO PTE LTDISSN: 2424-922XFrequency: 4 issues/year

Advances in Data Science and Adaptive Analysis is a prestigious journal dedicated to the advancement of knowledge within the rapidly evolving fields of data science and adaptive analysis. Published by WORLD SCIENTIFIC PUBL CO PTE LTD, this journal aims to serve as a platform for researchers, professionals, and students to disseminate innovative findings and methodologies. With a focus on interdisciplinary approaches, it invites contributions that explore the application of adaptive techniques in tackling complex data-driven challenges. Situated in Singapore, the journal stands out for its commitment to high-quality research, making significant impacts in the academic community and beyond. Although the journal currently does not offer open access, it remains a crucial resource for those striving to push the boundaries of data science research and its practical applications.

Applied Network Science

Fostering collaboration across the global network research community.
Publisher: SPRINGERNATUREISSN: Frequency: 1 issue/year

Applied Network Science is a premier open access journal published by SpringerNature that has been a vital resource in the fields of computational mathematics and computer networks since its inception in 2016. With an impressive Q1 ranking in Multidisciplinary fields and Q2 rankings in both Computational Mathematics and Computer Networks and Communications, it distinguishes itself as a significant contributor to interdisciplinary research efforts. The journal fosters innovative methodologies and applications within network science, making it a crucial platform for researchers, professionals, and students alike. With an E-ISSN of 2364-8228 and a commendable standing in global rankings, it supports a broad audience through its commitment to open access, ensuring that groundbreaking research is readily available. Located in Switzerland, Applied Network Science continues to shape the landscape of network research and communication, making substantial impacts across various domains.

Proceedings of the Romanian Academy Series A-Mathematics Physics Technical Sciences Information Science

Highlighting Scholarly Excellence in Eastern European Academia
Publisher: EDITURA ACAD ROMANEISSN: 1454-9069Frequency: 3 issues/year

Proceedings of the Romanian Academy Series A-Mathematics Physics Technical Sciences Information Science, published by EDITURA ACAD ROMANE, is a noteworthy academic journal that serves as a platform for disseminating original research in the intersecting fields of mathematics, physics, engineering, and computer science. With an ISSN of 1454-9069, this journal not only highlights the vibrant academic contributions from Romania but also attracts international submissions, thus fostering global collaboration. Though it currently does not offer an open-access model, the journal remains indexed in significant databases, reflecting its commitment to quality and scholarly rigor. The journal’s impact can be seen through its rankings, including Q4 in Computer Science, Q3 in Engineering, and Q4 across Mathematics and Physics, as well as its Scopus percentile rankings, which indicate meaningful contributions to these domains. With a converged publication span from 2008 to 2024, it aims to catalyze advancements in technical sciences while enriching the academic discourse among researchers, professionals, and students alike. The journal’s headquarters in Bucharest, Romania, positions it as a key player in the Eastern European academic landscape, making it essential reading for those engaged in cutting-edge research.

Complex Systems

Advancing Knowledge in Complex Systems Science
Publisher: COMPLEX SYSTEMS PUBLICATIONS INCISSN: 0891-2513Frequency: 4 issues/year

Complex Systems is a pivotal journal published by Complex Systems Publications Inc, specializing in the interdisciplinary field of complex systems science. With an ISSN of 0891-2513, it focuses on advancing the understanding of complex phenomena across various domains, including computer science and control engineering. Operating from the United States, this journal has established itself as a credible source with a current impact factor reflecting its relevance—ranking in the Q3 category for both Computer Science (miscellaneous) and Control and Systems Engineering as of 2023. Although it does not offer Open Access, Complex Systems aims to facilitate the exchange of cutting-edge research and innovative methodologies, making it indispensable for researchers, professionals, and students eager to explore and contribute to the field. With coverage spanning from 2012 to 2024, it strives to foster a deeper understanding of the principles governing complex systems, thus paving the way for future technological advancements and theoretical developments.