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Mathematics of Computation and Data Science is an open-access section that provides an opportunity for the interaction among applied mathematicians, including computer scientists and statisticians; other scientists, including physicists, chemists, biologists and biomedical researchers; as well as those engineers, who are interested in the computational aspects of Data Science.
Originating from Computer Science over three decades ago, and quickly becoming an important subject of studies in Statistics, "Data Science” has been regarded, more recently, as an interdisciplinary field, encompassing mathematics, statistics, engineering, and just about all technological disciplines, by using data-bases, data mining, high-performance and cloud computing, knowledge management, and virtualization, to discover useful information from either structured or unstructured data. However, it is too early to consider “Data Science” as a mathematics or scientific discipline in its own right, without adequate mathematics or scientific contents, such as definitions, theorems, laws and rules, that are fundamental for researchers from other fields to explore their own research interests or projects concerning data.
The ultimate goal of this section is to play a pioneering role to establish “Data Science” as an important discipline within Applied and Computational Mathematics. But in view of its interdisciplinary nature and its potential high impact to scientific and technological advancement in just about all areas, the mission of the section is to publish not only research papers, but also surveys, tutorials, and interesting experimental results, that are instrumental to facilitate the theoretical and algorithmic development of "Data Science", with emphasis on computations and statistical analysis. More specifically, "Mathematics of Computation and Data Science" is an open-access section that provides an opportunity for the interaction among applied mathematicians, including computer scientists and statisticians; other scientists, including physicists, chemists, biologists and biomedical researchers; as well as those engineers, who are interested in the computational aspects of Data Science. The success of this section depends on the authors and the quality of the papers they submit. On behalf the Editorial Board of Associate Editors, we ask for your enthusiastic support.
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Mathematics of Computation and Data Science welcomes submissions of the following article types: Book Review, Code, Data Report, Editorial, General Commentary, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Protocols, Review and Specialty Grand Challenge.
All manuscripts must be submitted directly to the section Mathematics of Computation and Data Science, where they are peer-reviewed by the Associate and Review Editors of the specialty section.
Articles published in the section Mathematics of Computation and Data Science will benefit from the Frontiers impact and tiering system after online publication. Authors of published original research with the highest impact, as judged democratically by the readers, will be invited by the Chief Editor to write a Frontiers Focused Review - a tier-climbing article. This is referred to as "democratic tiering". The author selection is based on article impact analytics of original research published in all Frontiers specialty journals and sections. Focused Reviews are centered on the original discovery, place it into a broader context, and aim to address the wider community across all of Applied Mathematics and Statistics.
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