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）
CODEN 码： SKYGAY
（国际标准连续出版物标识符·全球唯一标识符，由美国化学文摘社 CAS 分配）
出版模式： 金色开放获取（Gold OA），遵循知识共享署名 4.0 国际协议（CC BY 4.0），全文永久免费获取
出版机构： QUEST PRESS LIMITED
出版频率： 双月刊
出版语言： 中文、英文
投稿语言： 中文（需提供英文标题、摘要、关键词、作者单位及姓名）
发行支持： 国图集团（CIBTC）
进口备案刊号： G015Z119
本刊已获全球多家权威学术数据库收录，致力于推动高质量研究的全球传播，与全球学者携手，共建开放、协作、前瞻的国际学术共同体。

一、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。

二、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

三、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。

四、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：

• 国际核心数据库： SCIE (Science Citation Index Expanded), Ei Compendex, Scopus, DBLP Computer Science Bibliography, DOAJ, Google Scholar

• 中文核心数据库： 百度学术、万方数据、维普资讯、中国知网 (CNKI)

Journal Profile: Data Science & Engineering

Chinese Title: 《数据科学与工程》
English Title: Data Science & Engineering
ISSN:
ISSN 3105-7497 (Print)
ISSN 3105-7500 (Online)
CODEN: SKYGAY (Assigned by Chemical Abstracts Service, CAS)
Publication Model: Gold Open Access under the Creative Commons Attribution 4.0 International License (CC BY 4.0). All content is permanently and freely accessible.
Publisher: QUEST PRESS LIMITED
Publication Frequency: Bimonthly
Publication Language: Chinese, English
Submission Language: Chinese (English title, abstract, keywords, author affiliations, and names must be provided)
Distribution Support: China International Book Trading Corporation (CIBTC)
Import Registration Number: G015Z119

1. Core Positioning

Data Science & Engineering is an international academic journal focusing on data-driven innovation and engineering practice. The journal is committed to promoting the deep integration of data science theoretical methods and engineering applications, with particular emphasis on cutting-edge developments in big data technology, intelligent algorithms, and systems engineering. We especially encourage interdisciplinary research paradigms that integrate computer science, statistics, and domain-specific expertise to provide academic support for innovative breakthroughs in the field of data science and engineering.

2. Scope of Submission

The journal welcomes submissions in the following research 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

3. Aims and Vision

The journal aims to become an authoritative academic exchange platform in the field of data science and engineering, promoting the synergistic 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 supporting the transition to a data-driven research paradigm.

4. Global Indexing Plan

The journal is actively applying for inclusion in the following internationally renowned academic databases:

• International Core Databases: SCIE (Science Citation Index Expanded), Ei Compendex, Scopus, DBLP Computer Science Bibliography, DOAJ (Directory of Open Access Journals), Google Scholar

• Chinese Core Databases: Baidu Scholar, WanFang Data, VIP Information, CNKI (China National Knowledge Infrastructure)