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 peer-reviewed, high-impact on all fields of data science including 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.
and it is increasingly becoming part of sciences and businesses world-wide across numerous disciplines. JDS aims to serve a diverse community of scientists and practitioners, help develop a common language and make sure that the best results are easily accessible and most crucially recognizable broadly. To achieve these goals we are bridging numerous communities together across two scientific societies blending diverse research expertise and practices.
and it is increasingly becoming part of sciences and businesses world-wide across numerous disciplines. JDS aims to serve a diverse community of scientists and practitioners, help develop a common language and make sure that the best results are easily accessible and most crucially recognizable broadly. To achieve these goals we are bridging numerous communities together across two scientific societies blending diverse research expertise and practices.
Visit the Authors page for more details on deadlines and review timeline, submission templates, reproducibility requirements, and the ACM author instructions.
