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arXiv 2402.12413astro-ph.IMphysics.data-an
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天文学中的全球数据:挑战与机遇

Global Data in Astronomy: Challenges and Opportunities

Renee Hložek, Chenzhou Cui, Mark Allen, Patricia Whitelock, Jess McIver, Giuseppe Longo, Christopher Fluke, Ajit Kembhavi, Pranav Sharma, Ashish Mahabal

AI总结:

本文基于2023年S20 Policy Webinar讨论,探讨天文学作为数据驱动科学在数据管理、存储、高性能计算及跨国开放科学合作方面的挑战与机遇,呼吁国家资助机构利用天文数据优势并加强政策层面准备。

摘要:

本政策简报基于“天文学中的全球数据:挑战与机遇”,提炼自2023年7月6日至7日举行的关于可持续发展天体信息学的S20 Policy Webinar研讨会上相关小组的讨论。天文学正日益成为一门数据驱动的科学。为了增进对宇宙物理机制的理解,我们需要建造更灵敏的望远镜来收集宇宙观测数据,以检验并推进我们的理论模型。为了将观测数据与理论模型进行对比,我们需要数据托管、归档和存储设施,以及高性能计算资源来运行理论计算,从而比较模拟与观测到的宇宙。我们还需要培养高技能人力资源。较新的大型项目通常通过国际合作与伙伴关系运行,推动了跨国界“开放科学”和协作结构的需求。虽然天文数据在科学上很有用,但不像医学/生物学数据那样具有伦理/隐私相关的限制。此外,将数据用于新科学分析的能力扩展了科学调查的影响和范围——这是国家资助机构应加以利用的优势。我们讨论了此类海量数据的管理与分析,以及需要政策层面准备的相应重大挑战。该政策研讨会于印度担任G20主席国(2023年)期间举行。基于七个小组的总结可见于:arxiv:2401.04623。

英文摘要:

Policy Brief on "Global Data in Astronomy: Challenges and Opportunities", distilled from the corresponding panel that was part of the discussions during S20 Policy Webinar on Astroinformatics for Sustainable Development held on 6-7 July 2023. Astronomy is increasingly becoming a data-driven science. Advances in our understanding of the physical mechanisms at work in the Universe require building ever-more sensitive telescopes to gather observations of the cosmos to test and advance our theoretical models of how the universe works. To confront the observed data with our theoretical models we require data hosting, archiving and storage and high-performance computing resources to run the theoretical calculations and compare our simulated and observed universe. We also require the sophisticated development of highly skilled human resources. Newer large projects are often run through international collaborations and partnerships, driving a need for 'open science' and collaborative structure across national boundaries. While astronomical data are useful scientifically, the data do not come with the same ethical/privacy-related restrictions as medical/biological data. Moreover, the ability to use data for new scientific analysis extends and expands the impact and reach of scientific surveys -- this is a strength that national funding agencies should capitalize on. We discuss the management and analysis of such large volumes of data and the corresponding significant challenges that require policy-level preparations. The policy webinar took place during the G20 presidency in India (2023). A summary based on the seven panels can be found here: arxiv:2401.04623.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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