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NEON Operations and Maintenance: Evolving from a Strong Foundation

NEON Operations and Maintenance: Evolving from a Strong Foundation
NEON 运营和维护:从强大的基础发展而来
批准号:
2217817
负责人:
Paula Mabee
金额:
$41589.89万
依托单位:
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-11-01 至 2028-10-31

项目摘要

项目成果

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中文摘要
翻译
美国未来的健康、福利和安全取决于多样化的自然系统,这些系统可以被不断变化的世界所改变。国家生态观测网(NEON)是世界上第一个大陆尺度的设施,通过获取从地方尺度到大陆尺度的标准化生物和环境测量,研究这些变化的性质及其原因。它提供了关键数据,使科学家能够了解和预测变化,并使政策制定者能够潜在地减少有害影响。霓虹灯正在以前所未有的方式使人们获得这一科学领域的机会,向任何有兴趣从事高级生态和气候研究的人免费提供高质量的数据。霓虹灯在其20个生态区中的每一个都在全国范围内提供服务,以建立一个多样化、包容性和跨学科的下一代研究人员。霓虹灯与其合作伙伴一起,为广泛的利益相关者提供数据技能培训和教育材料。霓虹灯的任务是通过提供免费的、高质量的大陆和十年尺度的生态数据和样本,通过广泛的科学参与,使人们能够更好地了解和预测生态变化的驱动因素和应对措施。该项目的管理实体实现了这一使命,并通过强大、安全和可访问的网络基础设施、教育和推广计划、可查找、可访问、可互操作和可重复使用的公平数据合作伙伴以及霓虹灯生物资源库,提供对高质量霓虹灯数据和样品的快速和更广泛的访问,从而提高了发现的潜力。强大的霓虹灯网络基础设施提供免费和开放的数据和分析工具访问,将继续支持实践社区开发开放源代码、分析工具、标准化协议和派生的生态数据产品。霓虹灯基础设施在横跨美国大陆、阿拉斯加、夏威夷和波多黎各的20个不同生态区域的81个地点持续运行。使用传感器网络、机载遥感和人工现场观测和收集收集了180多个数据产品。这些免费和开放的数据通过霓虹灯数据门户(https://data.neonscience.org/).)提供给科学家、教育工作者和公众,以供社会使用物理样本通过霓虹灯生物信息库(https://biorepo.neonscience.org/portal/).)收集并提供使用霓虹灯通过一项可收回成本的可转让资产计划,提供对其基础设施的许多部分的定制访问,包括人员。集中式规划以数据的一致性和质量推动高效管理;20个霓虹域的分散执行适应了美国环境的多样性。霓虹灯推动跨学科知识的潜力将通过广泛的战略伙伴关系得到放大。霓虹灯将通过提供使用霓虹灯数据的培训,支持霓虹灯大使和合作伙伴,以及进行标准化生态实地采样方案的培训,建立一支多样化、包容性和跨学科的下一代研究人员和劳动力队伍。霓虹灯业务的持续改进,包括培训和外展活动,将由对照天文台绩效指标的定期外部评估推动。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The future health, welfare, and security of the U.S. depend upon diverse natural systems that can be altered by the changing world. The National Ecological Observatory Network (NEON), the first continental-scale facility of its kind in the world, addresses the nature of these changes and their causes by acquiring standardized biological and environmental measurements from the local to continental scale. It provides key data to enable scientists to understand and predict the changes and enable policy makers potentially to lessen detrimental effects. NEON is democratizing access to this area of science in unprecedented ways by providing high-quality data free of charge to anyone interested in pursuing advanced ecological and climate research. NEON provides outreach nationwide in each of its 20 ecological regions to build a diverse, inclusive, and interdisciplinary next generation of researchers. With its partners, NEON provides data skills training and educational materials to a wide variety of stakeholders. The NEON mission is to enable better understanding and prediction of the drivers of, and responses to, ecological changes by providing freely available, high-quality continental and decadal-scale ecological data and samples informed by broad scientific engagement. The managing entity for this project realizes this mission and advances the potential for discovery by providing rapid and broadened access to high-quality NEON data and samples through robust, secure, and accessible cyberinfrastructure, educational and outreach programs, findable, accessible, interoperable, and reusable - FAIR - data partners, and the NEON Biorepository. The robust NEON cyberinfrastructure that provides free and open access to data and analytic tools will continue to empower a community of practice to develop open-source code, analytic tools, standardized protocols, and derived ecological data products. NEON infrastructure is continuously operated at 81 sites in 20 distinct ecological regions spanning the continental United States, Alaska, Hawaii, and Puerto Rico. Over 180 data products are collected using a sensor network, airborne remote sensing, and manual field observations and collections. These free and openly available data are provided to scientists, educators, and the public for societal benefit through the NEON data portal (https://data.neonscience.org/). Physical samples are collected and made available for use through the NEON Biorepository (https://biorepo.neonscience.org/portal/). NEON provides customized access to many parts of its infrastructure, including personnel, through a cost-recoverable Assignable Assets program. Centralized planning drives efficient management with consistency and quality in data; decentralized execution across the 20 NEON Domains accommodates the diversity of environments in the US. The potential for NEON to advance interdisciplinary knowledge will be amplified by engaging in extensive strategic partnerships. NEON will build a diverse, inclusive, and interdisciplinary next generation of researchers and workforce by providing training in the use of NEON data, supporting NEON ambassadors and partners, and conducting training in standardized ecological field sampling protocols. Continual improvement of NEON operations, including training and outreach activities, will be driven by regular external evaluation against Observatory performance metrics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(8)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1029/2023gl104987
发表时间: 2023-11
期刊: Geophysical Research Letters
影响因子: 5.2
作者: [K. Aho;T. Maavara;K. M. Cawley;P. Raymond]
通讯作者: K. Aho;T. Maavara;K. M. Cawley;P. Raymond
The US National Ecological Observatory Network and the Global Biodiversity Framework: national research infrastructure with a global reach
美国国家生态观测站网络和全球生物多样性框架:具有全球影响力的国家研究基础设施
DOI: 10.5141/jee.23.076
发表时间: 2023
期刊: Journal of Ecology and Environment
影响因子: --
作者: [Thibault, Katherine M., Laney, Christine M., Yule, Kelsey M., Franz, Nico M., Mabee, Paula M.]
通讯作者: Mabee, Paula M.
DOI: 10.3389/feart.2023.1251138
发表时间: 2024-01
期刊: Frontiers in Earth Science
影响因子: 2.9
作者: [Brian J. Butterworth;Ankur R. Desai;D. Durden;H. Kadum;Danielle LaLuzerne;M. Mauder;Stefan Metzger;S. Paleri;Luise Wanner]
通讯作者: Brian J. Butterworth;Ankur R. Desai;D. Durden;H. Kadum;Danielle LaLuzerne;M. Mauder;Stefan Metzger;S. Paleri;Luise Wanner
Interactive Visualization and Portable Image Blending of Massive Aerial Image Mosaics
大规模航空图像马赛克的交互式可视化和便携式图像混合
DOI: 10.1109/bigdata59044.2023.10386428
发表时间: 2023
期刊: 2023 IEEE International Conference on Big Data (BigData
影响因子: --
作者: [Petruzza, Steve, Summa, Brian, Gooch, Amy, Laney, Christine M., Goulden, Tristan, Schreiner, John, Callahan, Steven, Pascucci, Valerio]
通讯作者: Pascucci, Valerio
共 8 条
    National Ecological Observatory Network Governing Cooperative Agreement
    • 批准号:
      2346114
    • 项目类别:
      Cooperative Agreement
    • 资助金额:
      $0.0万
    • 财政年份:
      2023
    • 负责人:
      Paula Mabee
    • 依托单位:
    Collaborative Research: Biology-guided neural networks for discovering phenotypic traits
    • 批准号:
      2022042
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $42.44万
    • 财政年份:
      2020
    • 负责人:
      Paula Mabee
    • 依托单位:
    Collaborative Research: Biology-guided neural networks for discovering phenotypic traits
    National Ecological Observatory Network: Operations Activities
    • 批准号:
      1724433
    • 项目类别:
      Cooperative Agreement
    • 资助金额:
      $12803.04万
    • 财政年份:
      2017
    • 负责人:
      Paula Mabee
    • 依托单位:
    海外基金