International Transactions on Data Science (ITDS)

About the Journal

International Transactions on Data Science (ITDS) is a peer-reviewed journal dedicated to advancing the field of data science through high-quality research contributions from academia, industry, and government institutions worldwide. ITDS serves as a platform for disseminating cutting-edge research findings, innovative methodologies, and practical applications in all areas of data science.

Scope:

ITDS covers a broad spectrum of topics related to data science, including but not limited to:

1. Data Mining and Knowledge Discovery: Original research in data mining techniques, algorithms, and methodologies for extracting valuable insights and knowledge from large datasets.

2. Machine Learning and Artificial Intelligence: Advances in machine learning algorithms, deep learning models, reinforcement learning techniques, and their applications in various domains.

3. Big Data Analytics: Innovative approaches for processing, analyzing, and visualizing massive volumes of structured and unstructured data to derive actionable insights.

4. Data-driven Decision Making: Studies on using data-driven approaches to inform decision making in business, healthcare, finance, marketing, and other domains.

5. Data Science Applications: Practical applications of data science techniques in real-world scenarios, including predictive analytics, fraud detection, recommendation systems, personalized medicine, and smart cities.

6. Data Privacy and Ethics: Research addressing privacy-preserving data mining, fairness and transparency in machine learning models, ethical considerations in data collection and analysis, and regulatory compliance.

Publication Criteria:

ITDS welcomes original research articles, review papers, survey articles, and case studies that contribute significant insights to the field of data science. Submissions undergo a rigorous peer-review process to ensure the quality, originality, and relevance of published content.

Audience:

The primary audience of ITDS includes researchers, academics, data scientists, practitioners, policymakers, and professionals interested in advancing the theory, methodologies, and applications of data science. The journal serves as a valuable resource for staying updated on the latest developments and trends in the rapidly evolving field of data science.

Editorial Board:

ITDS is supported by an esteemed editorial board comprising leading experts and scholars in the field of data science. The editorial team ensures the integrity and quality of published content while fostering collaboration and knowledge exchange among researchers worldwide.

Submission Guidelines:

Authors interested in submitting their work to ITDS are encouraged to review the journal's submission guidelines available on the official website. Submissions should adhere to the journal's formatting requirements and ethical standards.

Mission:

The mission of ITDS is to promote interdisciplinary research, innovation, and collaboration in data science, thereby advancing knowledge discovery, decision making, and societal impact through the effective use of data-driven approaches. By providing a platform for scholarly exchange and dissemination of research findings, ITDS aims to contribute to the continued growth and advancement of the field of data science on a global scale.