Planning Grant: Engineering research center for managing complex socio-environmental problems using a generic, tiered system-of-systems (GTSoS) modeling and data-science framework

规划拨款：工程研究中心，使用通用的分层系统（GTSoS）建模和数据科学框架来管理复杂的社会环境问题

• 批准号: 1937012
• 负责人: John Little
• 金额: $ 9.97万
• 依托单位: Virginia Polytechnic Institute and State University
• 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
• 起止时间: 2019-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937012&HistoricalAwards=false
• 关键词: Planning; Grant; Engineering; research; center

Complex socio-environmental problems, including those associated with coastal and inland flooding, the food/energy/water nexus, and interdependent infrastructure systems, are among the greatest challenges faced by humanity. Resilience and sustainability are often used to frame and study these families of ?wicked? problems. To resolve any of these challenges, solutions must consider many complex and interrelated socio-environmental systems. Collectively, these societal challenges, which can only be tackled by effective interdisciplinary teams, require a convergence research approach. This planning grant is guided by a vision for an Engineering Research Center (ERC) that aims to manage several families of complex socio-environmental problems using a generic, tiered system-of-systems (GTSoS) modeling and data-science framework. The comprehensive interdisciplinary approach can link domains that do not always collaborate easily (engineering, natural sciences, and social sciences) in new and highly productive ways. In addition, productive and durable transdisciplinary engagement and collaborations among researchers and a broad cross section of stakeholders will support decision-making that improves collective governance for some of the world's most difficult problems.The planning project participants will include biophysical scientists and engineers, social scientists as well as computer and data scientists. Collectively, this group represents the multiple knowledge domains, including water resources, ecology, agriculture, systems engineering, economics, anthropology, health, and education, necessary to address complex socio-environmental problems. The novel GTSoS framework, which fuses data science, domain science, and systems modeling, is designed to be both scalable and extensible, capturing the dynamics of individual systems as well as the complex dynamics of interconnected socio-environmental systems.To prepare the foundation of the ERC, the planning team will engage with many experts and stakeholders in a series of virtual meetings and in-person workshops which will generate knowledge and insights that will enable the successful design of the ERC. The workshops will also facilitate the emergence of strong and diverse teams with appropriate institutional expertise that support the implementation and management of the ERC. The ERC will initially focus on two core areas, one of which addresses the methodological approach, while the other tackles food/energy/water systems. The methodological core generalizes the approach to solving complex socio-environmental problems and allows additional families of problems to be added as the ERC matures. Effective interdisciplinary teams will be achieved by leveraging organizational design with the appropriate deployment of collaborative technology to overcome disciplinary and geographical boundaries and to ensure a culture of deep collaboration and inclusion. Principles and methods from decision analysis, multi-scale decision theory, and social choice theory will support decision-making, effectively enhancing leadership and management of the ERC. A primary workshop will have a science and modeling component to resolve key challenges in the GTSoS modeling and data-science framework and a process component to reveal how the organizational structure of the ERC can be optimized to accelerate advancement and discovery. A final synthesis workshop will develop an effective ERC structure, as well as detailed outlines of the ERC proposal and a manuscript on lessons learned.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.

人类面临的最大挑战之一。韧性和可持续性通常用于构架和研究这些邪恶的家庭？问题。为了解决这些挑战中的任何一个，解决方案必须考虑许多复杂且相互关联的环境系统。总的来说，这些社会挑战只能通过有效的跨学科团队来应对，需要采用融合研究方法。该计划赠款的指导下是对工程研究中心（ERC）的愿景，旨在使用通用的，分层的系统（GTSOS）建模和数据科学框架来管理几个复杂社会环境问题的家庭。综合的跨学科方法可以将不总是轻松协作（工程，自然科学和社会科学）链接到新的和高产的方式。此外，研究人员和广泛的利益相关者之间的富有生产力和耐用的跨学科参与和合作将支持决策，从而改善了一些世界上一些最困难的问题的集体治理。计划项目参与者将包括生物物理学科学家和工程师，社会科学家以及计算机和数据科学家。总的来说，该小组代表了多个知识领域，包括水资源，生态，农业，系统工程，经济学，人类学，健康和教育，以解决复杂的社会环境问题。融合数据科学，领域科学和系统建模的新型GTSO框架既既可扩展又可扩展，从而捕捉了各个系统的动态以及相互联系的社会环境系统的复杂动态，为了准备ERC的基础，计划团队将与许多专家和利益的启用者互动和利益的启用，该公司的企业和利益的企业构成了一系列的知识，并构成了一系列的知识，并实现了一系列的企业，并实现了一系列的企业，并启用了一系列的实现，并在实现了一系列的实现，并跨越了一系列的实现，并跨越了一系列的实现，并跨越了一系列的实现，并在现实中的企业进行了实现的实现。 ERC的成功设计。这些研讨会还将促进具有适当的机构专业知识的强大团队的出现，以支持ERC的实施和管理。 ERC最初将专注于两个核心领域，一个领域解决了方法论方法，而另一种则解决了食品/能量/水系统。方法论核心概括了解决复杂的社会环境问题的方法，并允许在ERC成熟时添加其他问题家族。通过适当部署协作技术来克服纪律和地理界限并确保深入协作和包容的文化，可以利用组织设计来实现有效的跨学科团队。决策分析，多规模决策理论和社会选择理论的原则和方法将支持决策，从而有效地增强ERC的领导力和管理。主要研讨会将具有科学和建模组件，以解决GTSOS建模和数据科学框架中的关键挑战，以及一个过程组件，以揭示如何优化ERC的组织结构以加速进步和发现。最终的综合研讨会将开发有效的ERC结构，并详细概述了ERC提案的概述，并在经验教训上进行了手稿。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准来评估的。

项目成果

Integrated assessment across building and urban scales: A review and proposal for a more holistic, multi-scale, system-of-systems approach

跨建筑和城市尺度的综合评估：对更全面、多尺度、系统系统方法的审查和建议

• DOI: 10.1016/j.scs.2022.103915
• 发表时间: 2022
• 期刊: Sustainable Cities and Society
• 影响因子: 11.7
• 作者: Bi, Chenyang;Little, John C.
• 通讯作者: Little, John C.

Applying a Coupled Hydrologic-Economic Modeling Framework: Evaluating Alternative Options for Reducing Impacts for Downstream Locations in Response to Upstream Development

应用水文经济耦合建模框架：评估减少下游地区影响以应对上游开发的替代方案

• DOI: 10.3390/su14116630
• 发表时间: 2022
• 期刊: Sustainability
• 影响因子: 3.9
• 作者: Amaya, Maria;Duchin, Faye;Hester, Erich;Little, John C.
• 通讯作者: Little, John C.

A Coupled Hydrologic-Economic Modeling Framework for Scenario Analysis

用于情景分析的水文经济耦合建模框架

• DOI: 10.3389/frwa.2021.681553
• 发表时间: 2021
• 期刊: Frontiers in Water
• 影响因子: 2.9
• 作者: Amaya, Maria;Baran, Ayden;Lopez-Morales, Carlos;Little, John C.
• 通讯作者: Little, John C.

Toward a complete interdisciplinary treatment of scale

迈向规模的完整跨学科治疗

• DOI: 10.1525/elementa.2020.00182
• 发表时间: 2021
• 期刊: Elementa: Science of the Anthropocene
• 作者: Iwanaga, Takuya;Wang, Hsiao-Hsuan;Koralewski, Tomasz E.;Grant, William E.;Jakeman, Anthony J.;Little, John C.
• 通讯作者: Little, John C.

Convergent Anthropocene Systems: Towards an Agile, System-of-Systems Engineering Approach

融合人类世系统：迈向敏捷的系统工程方法

• DOI: 10.1109/sose55472.2022.9812683
• 发表时间: 2022
• 期刊: 17th Annual System of Systems Engineering Conference (SOSE
• 作者: Farid, Amro M.;Little, John C.
• 通讯作者: Little, John C.