About the Journal

Journal of Data Science and Applications (JDSA) is a peer-reviewed academic journal that focuses on the dissemination of high-quality research and innovative applications in the field of data science and its real-world implementations. The journal aims to bridge the gap between data science theory and practical applications across multidisciplinary fields.

IJDSA provides a platform for researchers, practitioners, and policymakers to publish original research articles, review papers, and applied studies that demonstrate how data science methods can be effectively utilized to solve complex problems in various sectors such as agriculture, business, health, education, environment, and technology.

The journal encourages submissions that highlight applied analytics, machine learning solutions, data-driven decision making, and the integration of data science techniques with domain-specific challenges.

Scope

The scope of the Journal of Data Science and Applications includes, but is not limited to, the following topics:

  • Data Science Theory, Methods, and Frameworks
  • Data Mining and Predictive Modeling
  • Machine Learning and Artificial Intelligence Applications
  • Big Data Engineering and Analytics
  • Statistical and Computational Modeling
  • Data Visualization and Decision Support Systems
  • Text Mining and Natural Language Processing (NLP)
  • Internet of Things (IoT) and Sensor Data Analysis
  • Cloud and Edge Computing for Data Applications
  • Business Intelligence and Data-Driven Innovation
  • Applied Data Science in Agriculture, Health, Education, and Environment
  • Ethical and Responsible Use of Data

IJDSA upholds a double-blind peer-review process to ensure the integrity, originality, and scientific contribution of all published papers. The journal welcomes interdisciplinary research and collaborative studies between academia, government, and industry.