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The scope of ACM Transactions on Data Science includes cross disciplinary innovative research ideas, algorithms, systems, theory and applications for data science. Papers that address challenges at every stage, from acquisition on, through data cleaning, transformation, representation, integration, indexing, modeling, analysis, visualization, and interpretation while retaining privacy, fairness, provenance, transparency, and provision of social benefit, within the context of big data, fall within the scope of the journal.
By its very nature, data science overlaps with many areas of computer science. However, the objective of the journal is to provide a forum for cross-cutting research results that contribute to data science as defined above. Papers that address core technologies without clear evidence that they propose multi/cross-disciplinary technologies and approaches designed for management and processing of large volumes of data, and for data-driven decision making will be out of scope of this journal.
(updated Jan 25th 2019)