Collaborative Research: SCIPE: Enhancing the Transdisciplinary Research Ecosystem for Earth and Environmental Science with Dedicated Cyber Infrastructure Professionals

合作研究:SCIPE:通过专门的网络基础设施专业人员增强地球与环境科学的跨学科研究生态系统

基本信息

  • 批准号:
    2321009
  • 负责人:
  • 金额:
    $ 99.97万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-11-01 至 2027-10-31
  • 项目状态:
    未结题

项目摘要

In this age of big data, cutting-edge Earth and Environmental Science research increasingly requires Cyber Infrastructure (CI) expertise. Prior advances, including the prediction of climate change, the role and importance of biodiversity, and changes in the condition of oceans and fisheries, were all underpinned by the collection, organization, and analysis of massive quantities of data derived from advanced sensors and models. Increased data throughput in analysis pipelines has spurred advances in artificial intelligence, forecasting models, and reliance on scientific computing. Maintaining these cutting-edge research programs requires constant CI innovation, including collaboration with experts trained to innovate in findable, accessible, interoperable, and reusable data and analysis. Identifying solutions to the world’s most pressing environmental problems requires that CI experts collaborate with researchers, science communicators, environmental agencies, and nongovernmental organizations. This project will create this network through development of a CyberCollaboratory, where interdisciplinary groups across institutions can collaborate with Cyber Infrastructure Professionals (CIPs), leveraging high-performance and cloud computing, open data science, and geospatial analytics, in facilitated, scalable, and cyber-supported virtual and in-person spaces. The CyberCollaboratory is a collaboration between the University of Maryland Center for Environmental Science (UMCES) and the University of Maryland, Baltimore County (UMBC). The project will have a broad impact on the research-facing CIP community, offer opportunities for training diverse groups of students from UMBC Information Systems to engage with applied Earth and Environmental Science research, and support these professionals as they grow into a foundational component of the environmental research, policy, and management community. We will develop a knowledge portal that provides opportunities to extend the impact of this project beyond UMCES and UMBC to academic partnerships elsewhere that are also engaging in CI professionalization. This project is developing and supporting a team of CIPs that integrates seamlessly with our diverse research enterprise. Through an inter-institutional partnership between UMCES and UMBC Information Systems the project will accelerate the development of open data science, software tools, integrated ecosystem models, and machine learning applications; engage faculty, students, and environmental management agencies (and other stakeholders) in co-development research training; and staff a ticket-based help desk. UMCES and UMBC will collaboratively: (1) Build a diverse workforce of CIPs responsive to the needs of the multi-institutional and stakeholder-inclusive environmental research community to which UMCES and UMBC contribute; (2) Develop a hub, with physical and virtual components, that facilitates interactions among domain researchers, CIPs, and other stakeholders, including opportunities for CI skills training and team science training; and (3) Establish the CyberCollaboratory as a robust and pervasive source for CI expertise and collaboration. The CI team will adapt to evolving research priorities enabled by the co-development process but will initially support four active projects at UMBC and UMCES: (a) Harnessing data and model revolution in the polar regions (iHARP); (b) Developing a nutrient information system for agricultural sustainability; (c) Ecological forecasting for evaluating restoration actions in estuaries, and (d) Understanding the ecological consequences of expanding offshore wind energy generation.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.
在这个大数据时代,尖端的地球和环境科学研究越来越需要网络基础设施(CI)的专业知识。之前的进展,包括气候变化的预测,生物多样性的作用和重要性,以及海洋和渔业状况的变化,都是通过收集,组织和分析来自先进传感器和模型的大量数据来支撑的。分析管道中数据吞吐量的增加刺激了人工智能、预测模型和对科学计算的依赖的进步。维持这些尖端的研究项目需要不断的CI创新,包括与经过培训的专家合作,在可查找、可访问、可互操作和可重复使用的数据和分析方面进行创新。确定世界上最紧迫的环境问题的解决方案需要CI专家与研究人员,科学传播者,环境机构和非政府组织合作。该项目将通过开发网络协作实验室来创建这个网络,跨机构的跨学科小组可以与网络基础设施专业人员(CIP)合作,利用高性能和云计算,开放数据科学和地理空间分析,在便利,可扩展和网络支持的虚拟和面对面空间中。网络合作实验室是马里兰州大学环境科学中心(UMCES)和马里兰州大学巴尔的摩县分校(UMBC)之间的合作项目。该项目将对面向研究的CIP社区产生广泛的影响,为来自UMBC信息系统的不同学生群体提供培训机会,以参与应用地球和环境科学研究,并支持这些专业人士成长为环境研究,政策和管理社区的基础组成部分。我们将开发一个知识门户网站,提供机会,扩大该项目的影响超越UMCES和UMBC的学术合作伙伴关系,在其他地方也在从事CI专业化。该项目正在开发和支持一个CIP团队,与我们多样化的研究企业无缝集成。通过UMCES和UMBC信息系统之间的机构间合作伙伴关系,该项目将加速开放数据科学,软件工具,集成生态系统模型和机器学习应用程序的开发;让教师,学生和环境管理机构(以及其他利益相关者)参与共同开发研究培训;并为基于票证的帮助台提供人员。UMCES和UMBC将合作:(1)建立一个多元化的CIP劳动力队伍,以满足UMCES和UMBC所贡献的多机构和包容所有者的环境研究社区的需求;(2)开发一个具有物理和虚拟组件的中心,促进领域研究人员,CIP和其他利益相关者之间的互动,包括CI技能培训和团队科学培训的机会;以及(3)建立网络协作实验室,作为CI专业知识和协作的强大而普遍的来源。传播和信息小组将适应共同发展进程所促成的不断变化的研究优先事项,但最初将支持UMBC和UMCES的四个积极项目:(a)利用极地地区的数据和模型革命(iHARP);(B)开发农业可持续性的营养信息系统;(b)开发农业可持续性的营养信息系统。(c)进行生态预测,以评价河口的恢复行动,以及(d)了解扩大海上风能发电的生态后果。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响进行评估,被认为值得支持审查标准。

项目成果

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Vandana Janeja其他文献

Adopting Foundational Data Science Curriculum with Diverse Institutional Contexts
采用具有不同机构背景的基础数据科学课程
Understanding the Role of 2019 Amazon Wildfires on Antarctic Sea Ice Extent Using Data Science Approaches
使用数据科学方法了解 2019 年亚马逊野火对南极海冰范围的影响
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sudip Chakraborty;Chhaya Kulkarni;Atefeh Jabeli;Akila Sampath;Gehan Boteju;Jianwu Wang;Vandana Janeja
  • 通讯作者:
    Vandana Janeja

Vandana Janeja的其他文献

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{{ truncateString('Vandana Janeja', 18)}}的其他基金

EAGER: DCL: SaTC: Enabling Interdisciplinary Collaboration: Improving Human Discernment of Audio Deepfakes via Multi-level Information Augmentation
EAGER:DCL:SaTC:实现跨学科合作:通过多级信息增强提高人类对音频深赝品的识别能力
  • 批准号:
    2210011
  • 财政年份:
    2022
  • 资助金额:
    $ 99.97万
  • 项目类别:
    Standard Grant
HDR Institute: HARP- Harnessing Data and Model Revolution in the Polar Regions
HDR 研究所:HARP——利用极地地区的数据和模型革命
  • 批准号:
    2118285
  • 财政年份:
    2022
  • 资助金额:
    $ 99.97万
  • 项目类别:
    Cooperative Agreement

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