Impact Factor and Journal Rank of Big Data Research

About:

Objective:
Big Data Research, published by Elsevier, aims to publish high-quality, peer-reviewed research articles and reviews that advance the understanding and application of big data analytics. The journal serves as a platform for researchers and practitioners to explore innovative methodologies, technologies, and applications in big data science.

Publication Focus:
Methodologies: Novel algorithms, techniques, and frameworks for processing, analyzing, and interpreting large-scale datasets. Applications: Case studies and real-world applications demonstrating the impact of big data analytics across various domains, including healthcare, finance, e-commerce, social media, and smart cities. Tools and Infrastructure: Development and evaluation of tools, platforms, and infrastructures to support big data processing and management. Ethical and Legal Issues: Discussions on privacy, security, ethical considerations, and regulatory frameworks related to big data research and applications.

Research Areas:
Data Mining and Machine Learning: Advanced methods for knowledge discovery, pattern recognition, and predictive modeling from big data. Data Integration and Visualization: Techniques for integrating heterogeneous data sources and visualizing complex datasets to facilitate decision-making. Big Data Infrastructure: Scalable architectures, cloud computing, and distributed systems for efficient storage and processing of big data. Big Data Analytics: Techniques for real-time analytics, stream processing, and data-driven decision support systems.

Contributions:
Big Data Research welcomes original research articles, surveys, reviews, and technical notes that contribute significant insights into the theory, methodology, and applications of big data analytics. It aims to foster interdisciplinary collaborations and promote the dissemination of cutting-edge research in this rapidly evolving field.

Conclusion:
Big Data Research, as published by Elsevier, plays a crucial role in advancing knowledge and innovation in big data analytics. By bridging the gap between theory and practice, the journal contributes to the development of transformative technologies and solutions that harness the power of big data for societal and industrial applications.

Journal Home:  Journal Homepage

Editor-in-Chief:  Philippe Bonnet

scope: Big data analytics

Data mining and knowledge discovery

Machine learning for big data

Data-intensive computing and processing

Big data visualization

Distributed and parallel databases for big data

Cloud computing for big data

Big data applications in various domains (e.g., healthcare, finance, social media)

Privacy, security, and ethics in big data

Scalability and performance issues in big data systems

Print ISSN:  22145796

Electronic ISSN:  

Abstracting and Indexing:  SCOPUS, SCience Citation Imndexd EXpanded

Imapct Factor 2023:  3.3

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

Publication Frequency:  

H Index:  38

Best Quartile:

Q1:  Information Systems

Q2:  

Q3:  

Q4:  

Cite Score:  8.4

SNIP:  1.511

Journal Rank(SJR):  0.869

Latest Articles:   Latest Articles in Big Data Research

Guidelines for Authors: Big Data Research Author Guidelines

Paper Submissions: Paper Submissions in Big Data Research

Publisher:  Elsevier Inc.

Country:  United States