Convergence Accelerator Phase I (RAISE): The Urban Flooding Open Knowledge Network
Convergence Accelerator Phase I (RAISE): The Urban Flooding Open Knowledge Network
批准号:
1937099
负责人:
Lilit Yeghiazarian
金额:
$100.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2021-05-31
中文摘要
NSF融合加速器支持基于团队的多学科努力,以应对国家重要性的挑战,并在不久的将来显示出交付成果的潜力。这一融合加速器第一阶段项目的更广泛的影响和潜在的社会效益是将美国未来城市洪水造成的经济和人员损失降至最低。洪水影响了一系列相互关联的城市系统(在本项目中称为城市综合体),包括电网和交通网络、地表水和地下水、污水和饮用水系统、内河航运和大坝以及其他系统,所有这些都与社会经济和公共卫生部门交织在一起。该项目采用一种融合的方法来整合这些相互关联的多个系统,并融合了水文学和水利工程、系统分析、优化和控制、机器学习、数据和计算机科学、流行病学、社会经济学以及交通和电气工程方面的最新实践,以建立一个城市防洪开放知识网络(UF-OKN)。UF-OKN将由来自工程学、计算机科学、社会科学和经济学的学术和非学术研究人员组成。UF-OKN的设想是赋予决策者和公众权力,不仅提供关于未来事件可能发生多少洪水的信息,而且还显示洪水事件对城市地区自然和工程基础设施的级联影响,以便进行更有效的规划和决策。洪水对整个城市综合体的真正影响目前无法量化,因为许多系统虽然是相互关联的,但都是独立设计和管理的。因此,迫切需要一个开放的知识网络,以便详细了解这些系统的相互关联性以及它们如何相互影响。这个第一阶段的工作将填补的一个重要空白是开发一组通用的本体,用于描述和遍历Urban Multiplex子系统之间的数据关系。这一第一阶段的工作将为第二阶段生产规模的UF-OKN奠定基础,但也将使UF-OKN的原型及其应用公开。潜在的第二阶段项目的结果将是一个功能齐全的UF-OKN,它将回应简单的英语互联网查询,提供有关城市综合体的哪些基础设施将在暴风雨和洪水期间受到影响的可行信息,并利用与不同决策相关的可持续性指标信息促进短期和长期规划。这一成果可能会对研究人员、决策者和公众在如何参与城市洪水信息并对其采取行动方面产生潜在的变革。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 NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future. The broader impact and potential societal benefit of this Convergence Accelerator Phase I project is to minimize economic and human losses from future urban flooding in the United States. Floods impact a series of interconnected urban systems (referred to in this project as the Urban Multiplex) that include the power grid and transportation networks, surface water and groundwater, sewerage and drinking water systems, inland navigation and dams, and other system, all of which are intertwined with the socioeconomic and public health sectors. This project uses a convergent approach to integrate these multiple interconnected systems and merges state-of-the-art practices in hydrologic and hydraulic engineering; systems analysis, optimization and control; machine learning, data and computer science; epidemiology; socioeconomics; and transportation and electrical engineering to develop an Urban Flood Open Knowledge Network (UF-OKN). The UF-OKN will be built by bringing together academic and non-academic researchers from engineering, computer science, social science, and economics. The UF-OKN is envisioned to empower decision makers and the general public by providing information not just on how much flooding may occur from a future event, but also to show the cascading impact of a flood event on natural and engineered infrastructure of an urban area, so that more effective planning and decision-making can occur.The real impacts of flooding across the Urban Multiplex is currently unquantifiable because many of the systems, although interconnected, are independently designed and managed. Therefore, an open knowledge network that facilitates detailed understanding of the interconnectedness of these systems and how they impact each other is critically needed. An important gap that this Phase I effort will fill is the development of a common set of ontologies for describing and traversing the data relationships among Urban Multiplex subsystems. This Phase I effort will lay the groundwork for a production-scale UF-OKN in Phase II but will also make publicly available the prototype UF-OKN and its applications. The outcome of a potential Phase II project would be a fully functional UF-OKN that would respond to plain English Internet queries with actionable information on what infrastructure across the Urban Multiplex would be impacted during storms and flooding, facilitating both short-term and long-term planning with information on sustainability metrics associated with different decisions. This deliverable would be potentially transformative to researchers, decision-makers and the general public in terms of how they engage with and act upon information about urban flooding.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(3)
专著(0)
科研奖励(0)
会议论文
Model-Finding for Externally Verifying FOL Ontologies: A Study of Spatial Ontologies
外部验证 FOL 本体的模型寻找:空间本体的研究
DOI:
10.3233/faia200675
发表时间:
2020
期刊:
Proc. of the International Conference on Formal Ontology in Information System (FOIS-2020
影响因子:
--
作者:
[Stephen, S., Hahmann, T.]
通讯作者:
Hahmann, T.
Automatically Extracting OWL Versions of FOL Ontologies
自动提取 FOL 本体的 OWL 版本
DOI:
--
发表时间:
2021
期刊:
International Semantic Web Conference (ISWC 2021
影响因子:
--
作者:
[Hahmann, Torsten, Powell, Robert]
通讯作者:
Powell, Robert
Proto-OKN Theme 1: The Water-Energy Nexus Open Knowledge Network (WEN-OKN)
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批准号:2333726
-
项目类别:Cooperative Agreement
-
资助金额:$147.2万
-
财政年份:2023
-
负责人:Lilit Yeghiazarian
-
依托单位:
A1: The Urban Flooding Open Knowledge Network (UF-OKN): Delivering Flood Information to AnyOne, AnyTime, AnyWhere
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批准号:2033607
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项目类别:Cooperative Agreement
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资助金额:$500.0万
-
财政年份:2020
-
负责人:Lilit Yeghiazarian
-
依托单位:
A systems approach to managing the Urban Infrastructure Grid
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批准号:1929869
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项目类别:Standard Grant
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资助金额:$5.0万
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财政年份:2019
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负责人:Lilit Yeghiazarian
-
依托单位:
CAREER:Integrated Research & Education In Stochastic Systems-Based Watershed Management & Water Safety (SWMS)
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批准号:1351361
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项目类别:Continuing Grant
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资助金额:$40.96万
-
财政年份:2014
-
负责人:Lilit Yeghiazarian
-
依托单位:
EAGER: MONITORING NATION'S WATERS - TOWARDS A SWIMMING BIOSENSOR TO DYNAMICALLY MAP MICROBIAL CONTAMINATION
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批准号:1248385
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项目类别:Standard Grant
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资助金额:$10.0万
-
财政年份:2012
-
负责人:Lilit Yeghiazarian
-
依托单位:
国内基金
海外基金
大规模非确定图数据分析及其Multi-Accelerator并行系统架构研究
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批准号:62002350
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项目类别:青年科学基金项目
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资助金额:24.0万元
-
批准年份:2020
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负责人:张珩
-
依托单位: