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水、食物/能源/水关系以及相互依存的基础设施系统相关的问题，是人类面临的最大挑战之一。弹性和可持续性经常被用来构建和研究这些“邪恶”的家庭。问题。为了解决这些挑战，解决方案必须考虑许多复杂和相互关联的社会环境系统。总的来说，这些社会挑战只能由有效的跨学科团队来解决，需要一种融合的研究方法。该计划拨款以工程研究中心（ERC）的愿景为指导，该中心旨在使用通用的分层系统的系统（gtso）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容易合作的领域（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，从而改善对世界上一些最困难问题的集体治理。计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。总的来说，这个群体代表了多个知识领域，包括水资源、生态学、农业、系统工程、经济学、人类学、健康和教育，这些都是解决复杂社会环境问题所必需的。新的GTSoS框架融合了数据科学、领域科学和系统建模，设计成既可扩展又可扩展的，既能捕捉单个系统的动态，也能捕捉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进行一系列的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。讲习班还将促进形成具有适当机构专业知识的强大和多样化的团队，以支持ERC的实施和管理。ERC最初将侧重于两个核心领域，其中一个解决方法方法，而另一个解决食品/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ERC的成熟而添加其他问题家族。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克服学科和地理界限，并确保深度协作和包容的文化来实现。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为决策提供支持，有效地加强ERC的领导和管理。一个主要的研讨会将有一个科学和建模组件来解决GTSoS建模和数据科学框架中的关键挑战，一个过程组件来揭示ERC的组织结构如何优化以加速进步和发现。最后的综合研讨会将制定一个有效的ERC结构，以及ERC提案的详细大纲和关于经验教训的手稿。该奖项反映了美国国家科学基金会的法定使命，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.