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Data Science Strategies for Multimessenger Astronomy

research-article

Author(s): REINALDO R. ROSA

Publication date (Print and electronic): 2021

Journal: Anais da Academia Brasileira de Ciências

Publisher: Academia Brasileira de Ciências

Keywords: Astronomical data science, big data, data lake, data cube, MMA

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Abstract

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.

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Most cited references 7

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The role of big data analytics in Internet of Things

Ejaz Ahmed, Athanasios V Vasilakos, Muhammad Imran … (2017)

0 comments Cited 85 times – based on 0 reviews      Review now

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Ideas for Citizen Science in Astronomy

Philip Marshall, Chris J. Lintott, Leigh N. Fletcher (2015)

0 comments Cited 14 times – based on 0 reviews      Review now

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Astronomy in the Big Data Era

Yongheng Zhao, Yanxia Zhang (2015)

0 comments Cited 13 times – based on 0 reviews      Review now

Author and article information

Journal

Journal ID (publisher-id): aabc

Title: Anais da Academia Brasileira de Ciências

Abbreviated Title: An. Acad. Bras. Ciênc.

Publisher: Academia Brasileira de Ciências (Rio de Janeiro, RJ, Brazil )

ISSN (Print): 0001-3765

ISSN (Electronic): 1678-2690

Publication date (Print and electronic): 2021

Volume: 93

Issue: suppl 1

Electronic Location Identifier: e20200861

Affiliations

[1] São José dos Campos SP orgnameNational Institute for Space Research (INPE) orgdiv1Lab for Computing and Applied Mathematics (LABAC) Brazil

Article

Publisher ID: S0001-37652021000200301 Publisher ID: S0001-3765(21)09300000301

DOI: 10.1590/0001-3765202020200861

SO-VID: 9469e8c7-5758-4e57-aaa0-416dbc140dd4

License:

This work is licensed under a Creative Commons Attribution 4.0 International License.

History

Date accepted : 24 June 2020

Date received : 03 June 2020

Page count

Figures: 0, Tables: 0, Equations: 0, References: 19, Pages: 0

Product

SciELO Brazil

Self URI: Full text available only in PDF format (EN)

Categories

Subject: Mathematical Sciences

Keywords: big data,MMA,data cube,data lake,Astronomical data science

Data availability:

Keywords: big data, MMA, data cube, data lake, Astronomical data science

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