Rosa Reinaldo R
Lab for Computing and Applied Mathematics (LABAC), National Institute for Space Research (INPE), Av. dos Astronautas 1758, 12245-690 São José dos Campos, SP, Brazil.
An Acad Bras Cienc. 2020 Sep 28;93(suppl 1):e20200861. doi: 10.1590/0001-3765202020200861. eCollection 2020.
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.
本文旨在识别并提出数据科学策略，以加强天文学领域的科学研究。这些策略所能带来的数据工作流程性能提升，对于多信使天文学（MMA）而言可能至关重要。特别关注金砖国家天文学计划在大数据网络背景下对原始数据的处理。本文还展示了一个将MMA数据立方体纳入数据湖系统的原型的初步设计。
