Established in 2003, the Journal of Data Science aims to advance and promote data science methods, artificial intelligence, computing, and applications in all scientific fields where knowledge and insights are to be extracted from data. The journal publishes research works on the full spectrum of data science, including statistics, machine learning, artificial intelligence, computer science, and domain applications. The topics can cover any aspect of the data science lifecycle (collecting, processing, analyzing, modeling, communicating, etc.) from any field that involves understanding and making effective use of data. The emphasis is on applications, case studies, statistical and AI methods, computational tools, reproducible data science, and reviews of emerging advances in data science and artificial intelligence.