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		<doi>10.1590/0001-3765202020200861</doi>
		<issn>0001-3765</issn>
		<citationkey>Rosa:2020:DaScSt</citationkey>
		<title>Data science strategies for multimessenger astronomy</title>
		<year>2020</year>
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		<author>Rosa, Reinaldo Roberto,</author>
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		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>reinaldo.rosa@inpe.br</electronicmailaddress>
		<journal>Anais da Academia Brasileira de Ciencias</journal>
		<volume>93</volume>
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		<pages>e20200861</pages>
		<keywords>Astronomical data science, big data, data lake, data cube, MMA.</keywords>
		<abstract>This article aims to identify and suggest data science strategies to strengthen scientific research in astronomy. The improvements in data workflow performance that can be provided by these strategies can be crucial to the multimessenger astronomy (MMA). A special focus is given to the treatment of raw data in the context of big data networks for BRICS astronomy initiatives. A preliminary design of a prototype that incorporates an MMA data cube into a data lake system is presented.</abstract>
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