Data Science and Engineering
Impact Factor Trend (2023–2026)
Clarivate IF trend for Data Science and Engineering
SCImago Journal Rank citation prestige weighting
36 papers with at least that number of citations each
Aims & Scope
The journal of Data Science and Engineering (DSE) responds to the remarkable change in the focus of information technology development from CPU-intensive computation to data-intensive computation, where the effective application of data, especially big data, becomes vital. The emerging discipline data science and engineering, an interdisciplinary field integrating theories and methods from computer science, statistics, information science, and other fields, focuses on the foundations and engineering of efficient and effective techniques and systems for data collection and management, for data integration and correlation, for information and knowledge extraction from massive data sets, and for data use in different application domains. Focusing on the theoretical background and advanced engineering approaches, DSE aims to offer a prime forum for researchers, professionals, and industrial practitioners to share their knowledge in this rapidly growing area. It provides in-depth coverage of the latest advances in the closely related fields of data science and data engineering. More specifically, DSE covers four areas: (i) the data itself, i.e., the nature and quality of the data, especially big data; (ii) the principles of information extraction from data, especially big data; (iii) the theory behind data-intensive computing; and (iv) the techniques and systems used to analyze and manage big data. DSE welcomes papers that explore the above subjects. Specific topics include, but are not limited to: (a) the nature and quality of data, (b) the computational complexity of data-intensive computing,(c) new methods for the design and analysis of the algorithms for solving problems with big data input,(d) collection and integration of data collected from internet and sensing devises or sensor networks, (e) representation, modeling, and visualization of big data,(f) storage, transmission, and management of big data,(g) methods and algorithms of data intensive computing, such asmining big data,online analysis processing of big data,big data-based machine learning, big data based decision-making, statistical computation of big data, graph-theoretic computation of big data, linear algebraic computation of big data, and big data-based optimization. (h) hardware systems and software systems for data-intensive computing, (i) data security, privacy, and trust, and(j) novel applications of big data.
Special Issues
Calls for PapersNo active Calls for Papers found for this journal.
WoS Categories & Quartiles
Detailed JCR / JCI category rankings and quartile breakdown from Clarivate
COMPUTER SCIENCE, INFORMATION SYSTEMS
COMPUTER SCIENCE, THEORY & METHODS
COMPUTER SCIENCE, INFORMATION SYSTEMS
COMPUTER SCIENCE, THEORY & METHODS
Annual Historical Statistics & Publications
Track annual publication volume, total citations, and Impact Factor evolution
SCImago & Scopus Journal Intelligence
Global SCImago ranking, SJR prestige index, Scopus coverage, and societal policy impact
Weighted prestige citation metric per document indexed in the Scopus database.
Average citations received per document published in the 2-year window.
Diamond Open Access: Authors publish completely free of charge with zero author-facing fees.
Scopus 3-Year Publication & Citation Window
Aggregated from Scopus database across the 3-year SJR evaluation window.
Societal Impact & Inclusivity (SCImago)
Citations in government and international policy documents
Percentage of female authors published in the journal
Real-world societal policy reach and author gender diversity tracked by SCImago.
Scopus Subject Categories
Journal Metrics & Citation Visualizations
Total Cites vs Self-Cites
Evaluation of scholarly independence and citation reach
Citations per Document
Citation metric windows across 2, 3, and 4 years
Chinese Academy of Sciences (CAS) Classification
Major / minor zone classification and CAS Early Warning List history
Academic Intelligence Overview & Context
ImpaQ AnalysisData Science and Engineering (acronym: dsej, ISSN: 2364-1185) is a peer-reviewed international scholarly journal in the field of Engineering, published by Springer Nature in Germany. The periodical holds a Journal Impact Factor (JIF) of 4.10, ranking in quartile Q2 of Web of Science (ESCI), a Scopus SJR indicator of 1.212 (Q1), an H-index of 36.
The journal enforces rigorous peer evaluation with a publication frequency of 4 issues per year, an annual output of approximately 30 scientific articles. In terms of accessibility and author fees, it operates under the Gold OA model with Diamond Open Access (100% free of author APC charges). It serves as a benchmark publication platform for academics, researchers, and doctoral candidates seeking global research visibility.
Publishing & Editorial Information
Detailed publisher, peer-review turnaround, and publication cycle specifications
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