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ACM Proceedings of the ACM on Management of Data – The Proceedings of the ACM on Management of Data (PACMMOD) is concerned with the principles, algorithms, techniques, systems, and applications of database management systems, data management technology, and science and engineering of data. We invite the submission of original data management, data engineering, and data science research targeting the data life cycle of real applications, studying phenomena at scales, complexities, and granularities never before possible. This data life cycle encompasses databases/data management/data systems/data engineering often leveraging statistical, machine learning, and artificial intelligence methods and, in many instances, using massive and heterogeneous collections of potentially noisy datasets. Articles that address data challenges at various stages of the data lifecycle, from modeling, acquisition, cleaning, integration, indexing, querying, analysis, exploration, visualization, interpretation, and explanation fit within the areas of coverage. Papers are generally expected to focus on data-intensive components of data science pipelines; and solve problems in areas of interest to our community (e.g., data curation, optimization, performance, storage, systems) operating within accuracy, privacy, fairness, and diversity constraints. Submissions describing deployed systems and solutions to data science pipelines and/or fundamental experiences and insights from evaluating real-world data science problems are encouraged.
