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

复杂的社会环境问题，包括与沿海和内陆洪灾、粮食/能源/水的关系以及相互依存的基础设施系统有关的问题，是人类面临的最大挑战。韧性和可持续性经常被用来框定和研究这些邪恶的家庭。有问题。要解决这些挑战，解决方案必须考虑许多复杂和相互关联的社会环境系统。总体而言，这些社会挑战只能由有效的跨学科团队来解决，需要一种趋同的研究方法。这项规划拨款是以工程研究中心(ERC)的愿景为指导的，该中心旨在使用通用的分层系统(GTSoS)建模和数据科学框架来管理几个复杂的社会环境问题家族。综合的跨学科方法可以以新的和高效的方式将不总是容易协作的领域(工程、自然科学和社会科学)联系起来。此外，研究人员和广泛的利益相关者之间富有成效和持久的跨学科参与和合作将支持决策，以改善对世界上一些最困难问题的集体治理。规划项目的参与者将包括生物物理学家和工程师、社会科学家以及计算机和数据科学家。总体而言，这一群体代表了解决复杂的社会环境问题所需的多种知识领域，包括水资源、生态学、农业、系统工程、经济学、人类学、卫生和教育。新的GTSoS框架融合了数据科学、领域科学和系统建模，旨在具有可伸缩性和可扩展性，捕捉单个系统的动态以及相互关联的社会环境系统的复杂动态。为了准备ERC的基础，规划团队将与许多专家和利益相关者参加一系列虚拟会议和面对面的研讨会，这些会议和研讨会将产生知识和见解，使ERC的成功设计成为可能。讲习班还将促进出现具有适当机构专门知识的强大和多样化的团队，以支持对外关系与合作委员会的实施和管理。环境与和解委员会最初将侧重于两个核心领域，其中一个领域涉及方法方法，另一个领域涉及食品/能源/水系统。方法核心概括了解决复杂社会环境问题的方法，并允许随着环境资源中心的成熟增加更多的问题家族。有效的跨学科团队将通过利用组织设计和适当部署协作技术来实现，以克服学科和地理界限，并确保深度协作和包容的文化。决策分析、多尺度决策理论和社会选择理论的原理和方法将支持决策，有效地加强对环境资源委员会的领导和管理。初级讲习班将有一个科学和建模部分，以解决GTSoS建模和数据科学框架中的关键挑战，以及一个流程部分，以揭示如何优化电子资源中心的组织结构，以加快进步和发现。最终的综合研讨会将开发一个有效的ERC结构，以及ERC提案的详细大纲和关于经验教训的手稿。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。

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.