Cite Score and Journal Rank of International Journal of Data Science and Analytics

About:

The International Journal of Data Science and Analytics is a peer-reviewed publication dedicated to the study and application of data science and analytics. It provides a platform for researchers, practitioners, and professionals to publish original research articles, comprehensive reviews, and case studies on the latest advancements and methodologies in data science and analytics.

Objective:

The primary objective of the journal is to advance the field of data science and analytics by promoting innovative research and practical applications. It aims to facilitate the exchange of knowledge and ideas among experts working in areas such as data mining, machine learning, big data analytics, and data-driven decision-making.

Topics Covered:

The International Journal of Data Science and Analytics covers a wide range of topics including: Data mining and knowledge discovery Machine learning and artificial intelligence Big data technologies and architectures Predictive analytics and statistical modeling Data visualization and interpretation Data privacy, security, and ethical issues

Impact:

The journal significantly impacts both academia and industry by fostering the development and application of advanced data science and analytics techniques. Its publications contribute to the advancement of methodologies and tools that enhance the ability to analyze and leverage large datasets, driving innovation and informed decision-making across various domains.

Significance:

The International Journal of Data Science and Analytics is significant in advancing the field of data science by promoting interdisciplinary research and practical applications. By publishing high-quality, peer-reviewed articles, the journal supports the development and adoption of cutting-edge data science solutions, enhancing the ability to extract actionable insights and value from complex data.

Journal Home:  Journal Homepage

Editor-in-Chief:  João Gama

scope: The International Journal of Data Science and Analytics focuses on the development, application, and evaluation of data science and analytics methodologies. Here are the key areas typically covered in this journal:

1. Data Science Methodologies
Fundamental principles and techniques in data science
Data preprocessing, cleaning, and transformation
Data integration and data warehousing

2. Statistical Analysis and Data Mining
Statistical techniques for data analysis
Data mining methods and algorithms
Predictive modeling and pattern recognition

3. Machine Learning and Artificial Intelligence
Machine learning algorithms and frameworks
Deep learning and neural networks
Applications of AI in data science

4. Big Data Analytics
Technologies and frameworks for big data processing
Scalable data storage and retrieval
Analysis of large-scale data sets and data streams

5. Data Visualization
Techniques for visualizing complex data
Interactive and dynamic visualization tools
Use of dashboards and reporting systems

6. Data Ethics and Privacy
Ethical considerations in data collection and usage
Privacy-preserving techniques and data anonymization
Legal and regulatory aspects of data handling

7. Domain-Specific Applications
Application of data science in various domains such as healthcare, finance, marketing, and engineering
Case studies demonstrating data-driven decision-making
Integration of data science techniques in industry-specific challenges

8. Computational Methods
Algorithms and computational techniques for data analysis
High-performance computing and parallel processing
Optimization methods in data science

9. Data Science Tools and Platforms
Software and tools for data analysis and visualization
Development and evaluation of data science platforms
Integration of open-source and commercial tools

10. Emerging Trends and Innovations
Advances in data science technologies and methods
Emerging trends in data analytics and data-driven insights
Future directions and research opportunities in data science

Print ISSN:  2364415X,

Electronic ISSN:  23644168

Abstracting and Indexing:  SCOPUS

Imapct Factor 2023:  3.4

Subject Area and Category:   Computer Science, Computational Theory and Mathematics, Computer Science Applications, Information Systems, Mathematics, Applied Mathematics, Modeling and Simulation

Publication Frequency:  

H Index:  31

Best Quartile:

Q1:  

Q2:  Applied Mathematics

Q3:  

Q4:  

Cite Score:  6.4

SNIP:  1.312

Journal Rank(SJR):  0.739

Latest Articles:   Latest Articles in International Journal of Data Science and Analytics

Guidelines for Authors: International Journal of Data Science and Analytics Author Guidelines

Paper Submissions: Paper Submissions in International Journal of Data Science and Analytics

Publisher:  Springer Nature Switzerland AG

Country:  Switzerland