中文刊名：《数据科学与工程》

英文刊名：Data Science & Engineering

国际刊号：ISSN 3105-7497（印刷版） / ISSN 3105-7500（网络版）

出版模式：金色开放获取（Gold OA），适用CC BY 4.0协议（全文永久免费）

出版机构：QUEST PRESS LIMITED

出版频率：双月刊

投稿语言：中文（需附英文标题、摘要、关键词、作者单位及姓名）

核心定位
《数据科学与工程》是一本聚焦数据驱动创新与工程实践的国际化学术期刊。本刊致力于推动数据科学理论方法与工程应用的深度融合，重点关注大数据技术、智能算法与系统工程的前沿发展。我们特别鼓励跨学科的研究范式，融合计算机科学、统计学与领域专业知识，为数据科学与工程领域的创新突破提供学术支撑。

约稿范围
本刊欢迎以下研究方向的投稿：

大数据架构与分布式系统

机器学习与深度学习算法

数据挖掘与知识发现

数据可视化与可视分析

数据库技术与数据仓库

数据安全与隐私保护

自然语言处理与文本挖掘

推荐系统与智能决策

数据治理与数据质量

数据科学与工程教育

目标与愿景
本刊旨在成为数据科学与工程领域的权威学术交流平台，推动理论创新与技术实践的协同发展。我们致力于促进学术界与工业界的深度合作，为研究者、工程师和教育工作者提供高质量的成果分享与学术对话平台，助力数据驱动的研究范式转型。

全球数据索引计划
本刊正在申请纳入以下国际知名学术数据库：

SCIE (Science Citation Index Expanded)

Ei Compendex

Scopus

DBLP Computer Science Bibliography

DOAJ (Directory of Open Access Journals)

Google Scholar

百度学术

万方数据

维普资讯

CNKI 中国知网

Data Science & Engineering Call for Papers

Journal Information

Journal Title (English): Data Science & Engineering

Journal Title (Chinese): 《数据科学与工程》

ISSN: 3105-7497 (print) / 3105-7500 (online)

Publishing Model: Gold Open Access (under CC BY 4.0 license)

Publisher: QUEST PRESS LIMITED

Publication Frequency: Bimonthly

Language of Submission: Chinese (must include English title, abstract, keywords, and author affiliations/names)

Core Focus
Data Science & Engineering is an international academic journal focusing on data-driven innovation and engineering practices. The journal is committed to advancing the deep integration of data science theories and methodologies with engineering applications, with particular emphasis on cutting-edge developments in big data technologies, intelligent algorithms, and systems engineering. We particularly encourage interdisciplinary research paradigms that integrate computer science, statistics, and domain expertise to provide academic support for innovative breakthroughs in data science and engineering.

Scope
We welcome submissions in the following areas:

Big Data Architecture and Distributed Systems

Machine Learning and Deep Learning Algorithms

Data Mining and Knowledge Discovery

Data Visualization and Visual Analytics

Database Technology and Data Warehousing

Data Security and Privacy Protection

Natural Language Processing and Text Mining

Recommendation Systems and Intelligent Decision Making

Data Governance and Data Quality

Data Science and Engineering Education

Aims and Vision
Our goal is to establish Data Science & Engineering as an authoritative academic exchange platform in the field of data science and engineering, promoting the coordinated development of theoretical innovation and technological practice. We are committed to fostering deep collaboration between academia and industry, providing a high-quality platform for researchers, engineers, and educators to share achievements and engage in academic dialogue, thereby facilitating the transformation towards data-driven research paradigms.

Global Indexing Plan
The journal is pursuing inclusion in the following international academic databases:

SCIE (Science Citation Index Expanded)

Ei Compendex

Scopus

DBLP Computer Science Bibliography

DOAJ (Directory of Open Access Journals)

Google Scholar

Baidu Scholar

Wanfang Data

VIP (Weipu) Information

CNKI (China National Knowledge Infrastructure)