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, 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.