Abstract
Optimum ways of addressing large data volumes across a variety of disciplines have led to the formation of national and institutional Data Science Institutes and Centers. The objectives and functions of such institutes and centers are summarized. In reflecting the driver of national priority, they are able to attract academic support within their institutions to bring together interdisciplinary expertise to address a wide variety of datasets from disciplines such as astronomy, bioinformatics, engineering, science, medicine, social science, and the humanities. All are generating increasing volumes of data, often in real time, and require efficient and effective solutions. The opportunities and challenges of data science are presented. The processes of knowledge discovery in data science often require new methods and software, new organizational arrangements, and new skills in order to be effective. Data science centers and institutes provide a focus for the development and implementation of such new structures and arrangements for the development of appropriate facilities, with academic leadership and professional support. These are summarized and reviewed.
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Earnshaw, R. (2019). Data Science Institutes and Data Centers. In: Data Science and Visual Computing. Advanced Information and Knowledge Processing(). Springer, Cham. https://doi.org/10.1007/978-3-030-24367-8_7
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DOI: https://doi.org/10.1007/978-3-030-24367-8_7
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