Impact Factor and Journal Rank of IEEE Transactions on Big Data

About:

IEEE Transactions on Big Data is dedicated to the timely publication of impactful research at the intersection of big data technologies and their practical applications. The journal focuses on advancing the analysis, design, and implementation of big data systems and methodologies. It covers a broad spectrum from fundamental research in big data to engineering solutions for processing and analyzing vast amounts of data across various domains.

Objective: The journal aims to foster research that addresses critical challenges in big data technologies and data science. It seeks to publish innovative contributions that advance the understanding and application of big data methodologies in diverse environments, spanning business, healthcare, science, and beyond.

Interdisciplinary Focus: IEEE Transactions on Big Data welcomes submissions that integrate data science with real-world applications. Topics of interest include big data analytics, data mining, machine learning, data management, and visualization. The journal bridges theoretical advancements with practical applications in fields such as finance, healthcare, transportation, and social media.

Global Impact: With a global readership and contributions from leading researchers worldwide, IEEE Transactions on Big Data influences the development of big data technologies. The journal rigorous peer-review process ensures the publication of high-impact research that shapes the future of data science and big data applications.

Excellence in Scholarship: IEEE Transactions on Big Data upholds rigorous standards of scientific integrity and scholarly excellence. All submissions undergo thorough peer review to uphold methodological rigor, relevance, and originality. Published articles contribute substantively to advancing knowledge and innovation in big data technologies and data science.

Impact and Innovation: By facilitating collaboration among researchers and practitioners, IEEE Transactions on Big Data drives innovation in data science and big data technologies. The journal provides valuable insights and solutions that enhance the efficiency, reliability, and performance of data processing and analysis across diverse applications.

Journal Home:  Journal Homepage

Editor-in-Chief:  Jie Tang

scope: Big Data Analytics:
Techniques and algorithms for analyzing large-scale data.

Data Mining:
Methods for extracting useful information from vast datasets.

Machine Learning for Big Data:
Machine learning algorithms and models tailored for big data applications.

Data Management:
Systems and approaches for storing, managing, and retrieving big data.

Scalability and Performance:
Techniques to ensure scalable and high-performance big data processing.

Data Security and Privacy:
Ensuring the security and privacy of big data in storage and transmission.

Visualization of Big Data:
Methods for effectively visualizing and interpreting large datasets.

Applications of Big Data:
Real-world applications of big data in various domains such as healthcare, finance, social networks, etc.

Big Data Infrastructure:
Development and optimization of infrastructure for big data processing and storage.

Emerging Technologies:
Exploration of new technologies and tools for big data analytics and management.

Print ISSN:  2332-7790

Electronic ISSN:  

Abstracting and Indexing:  Scopus, SCIE

Imapct Factor 2023:  7.2

Subject Area and Category:  Computer Science,Information Systems,Decision Sciences,Information Systems and Management

Publication Frequency:  

H Index:  24

Best Quartile:

Q1:  Information Systems

Q2:  

Q3:  

Q4:  

Cite Score:  11.8

SNIP:  3.094

Journal Rank(SJR):  1.821

Latest Articles:   Latest Articles in IEEE Transactions on Big Data

Guidelines for Authors: IEEE Transactions on Big Data Author Guidelines

Paper Submissions: Paper Submissions in IEEE Transactions on Big Data

Publisher:  IEEE-Institute of Electrical and Electronics Engineers Inc.

Country:  United States