ACM/IMS Journal of Data Science (JDS) is a joint journal of the Association of Computing Machinery (ACM) and the Institute of Mathematical Statistics (IMS), publishing high-impact research from all areas of data science, across foundations, applications and systems. The scope of the journal is multi-disciplinary and broad, spanning statistics, machine learning, computer systems, and the societal implications of data science. JDS accepts original papers as well as novel surveys that summarize and organize critical subject areas.
Data science is increasingly central to science and businesses world-wide, across disciplines. JDS aims to serve a diverse community of scientists and practitioners, helping to develop a common language and make the best research results easily accessible and broadly recognized.
The journal bridges numerous communities across two scientific societies, representing diverse areas of research expertise. By combining elements of journal and conference publishing, the journal aims to serve the needs of a rapidly evolving research landscape.
Details on deadlines and review timeline, submission templates, reproducibility requirements, copyright, open access, and the ACM author instructions.