The Journal of Data Science and Modeling (JDSM) publishes papers that make theoretical and methodological advances relating to computational aspects of data science such as computational statistics, Bayesian computation, computational mathematics, artificial intelligence (AI), Business intelligence (BI), and data mining. Papers that develop new graphical methods, resampling, and other computationally intensive methods will be particularly welcomed.

     Computational-intensive assessments of statistical methodologies and comparisons of the performance statistical models for real-world applications in various fields will also be considered for publication. Special issues dedicated to a specific topic of current interest in statistics and multidisciplinary research providing comprehensive and up-to-date reviews will also be published periodically.

     To let individual researchers and libraries have access to the most recent research findings in the field, the journal allows open-access to its articles. This journal utilizes the Magiran and Noormags preservation systems to create a distributed archiving system for individual and libraries and to permit libraries stakeholders to create permanent archives of the journal.