Data Science and Engineering
Springer International Publishing
Switzerland
journal
SJR by Edition
Subject Categories
- Artificial IntelligenceQ1
- Computational MechanicsQ1
- Computer Science ApplicationsQ1
- Information SystemsQ1
- SoftwareQ1
Areas: Computer Science · Engineering
Most published research topics
Source: OpenAlex
Publication Statistics
Documents per Year
Detailed Information
ISSN
2364-1541, 2364-1185
SJR Best Quartile
Q1
Region
Western Europe
Citations per Document (2 years)
5.10
References per Document
57.17
Coverage
2016-2026
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.
Metrics from SCImago Journal Rank 2025. View on SCImago