Science Storms the Cloud
Science Storms the Cloud
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DOI：
10.1029/2020av000354
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发表时间：
2021-06-01
期刊：
影响因子：
8.4
通讯作者：
Signell, R. P.
中科院分区：
文献类型：
--
作者：
Gentemann, C. L.;Holdgraf, C.;Signell, R. P.
科学的核心工具（数据、软件和计算机）正在经历一场快速而历史性的演变，改变着科学家提出的问题以及他们如何找到答案。地球科学数据正在被转换为针对云存储进行优化的新格式，从而能够快速分析数PB的数据集。数据集正在从归档中心转移到巨大的云数据存储，与大型服务器农场相邻。开源的基于云的数据科学平台，通过网络浏览器窗口访问，使先进的，协作的，跨学科的科学可以在任何科学家可以连接到互联网的地方进行。用于机器学习和人工智能的专业软件和硬件正在被集成到数据科学平台中，使它们更容易被普通科学家使用。云中越来越多的数据和计算能力正在为数据驱动的发现开启新的方法。这是第一次，科学家在没有专业云计算知识的情况下，将他们的分析带到云中的数据中是真正可行的。这种范式的转变有可能降低进入门槛，扩大科学界，增加合作机会，同时促进科学创新，透明度和可重复性。然而，我们都目睹了一些有希望的新工具，这些工具在开始时似乎无害和有益，但后来却变成了破坏性或限制性的。随着这种新的科学研究方式的发展，我们需要考虑什么？
The core tools of science (data, software, and computers) are undergoing a rapid and historic evolution, changing what questions scientists ask and how they find answers. Earth science data are being transformed into new formats optimized for cloud storage that enable rapid analysis of multi-petabyte data sets. Data sets are moving from archive centers to vast cloud data storage, adjacent to massive server farms. Open source cloud-based data science platforms, accessed through a web-browser window, are enabling advanced, collaborative, interdisciplinary science to be performed wherever scientists can connect to the internet. Specialized software and hardware for machine learning and artificial intelligence are being integrated into data science platforms, making them more accessible to average scientists. Increasing amounts of data and computational power in the cloud are unlocking new approaches for data-driven discovery. For the first time, it is truly feasible for scientists to bring their analysis to data in the cloud without specialized cloud computing knowledge. This shift in paradigm has the potential to lower the threshold for entry, expand the science community, and increase opportunities for collaboration while promoting scientific innovation, transparency, and reproducibility. Yet, we have all witnessed promising new tools which seem harmless and beneficial at the outset become damaging or limiting. What do we need to consider as this new way of doing science is evolving?