Data Science & Engineering《数据科学与工程》 (ISSN: 3105-7497)

Description

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)
CODEN: SKYGAY
(International Standard Serial Identifier · Globally Unique Identifier)Assigning Agency: Chemical Abstracts Service (CAS), USA
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)
Global Indexing：
DOI，Crossref，Index Copernicus.Poland，EuroPub Publishing Company.Britain，Academia.edu.America，ResearchBib.Japan，Vanderbilt University Medical Center.America，LivRe（livre.cnen.gov.br）.Brazil，Research Center for Chinese Science Evaluation.RCCSE，YangtzeRiverRepos.China，Eurasian Science Journal Index(ESJI).Kazakhstan，Sci Online，Baidu Baike.China，CNKI.China，Wanfang Data.China，VIP.China，Zhongyou Reading.China，Longyuan Journals Network.China，uperStar Database.China，Macao Virtual Library.China，ASCI，GoogleScholar，Baidu Scholar.China，Open Access Library(OALib).America，Kind Congress