Collaborative Research: NNA Research: Capturing Indigenous Knowledge to Co-Design more Effective Operations, Maintenance and Management of Water Infrastructure

航行新北极(NNA)是NSF的十大想法之一。NNA项目解决了快速变化的北极地区汇聚的科学挑战。北极研究需要为国家、更大区域和全球的经济、安全和韧性提供信息。NNA增强了从地方到国际的新的研究伙伴关系，使下一代北极研究人员多样化，加强正式和非正式教育的努力，并在适当的情况下整合共同创造知识。该奖项通过在以下NNA重点领域解决社会系统、自然环境和建筑环境之间的相互作用来实现这一目标的一部分：弹性基础设施和教育。北极农村水利基础设施系统面临的一个挑战是如何成功地运营、管理和维护它们。在这些偏远地区，确保持续供水的运营、维护和管理(OMM)是困难的，原因有很多，例如获得技术资源和接受各种技能培训的机会有限。建议建设当地劳动力能力和培训，以弥补OMM的这一差距。然而，这些建议背后的假设是，用于建设水系统的知识与运营和与所述系统互动的人的当地知识相匹配。在阿拉斯加的农村，情况并不总是这样。该项目旨在弥合期望的工程技术和当地社区的实际技术之间的差距。该方法通过开发更好地植根于当地知识的水系统OMM培训材料，为当地运营商提供支持。在系统规模上，该项目还开发了描述阿拉斯加农村水系统的教育材料，旨在更广泛地教育非技术用户社区。通过在工程学和社会背景之间架起桥梁，该项目增强并扩大了当前和潜在的未来工程劳动力的参与。为了应对这一挑战，这个跨学科的研究团队采取了三个阶段的方法，整合了土木工程和环境工程学、社会学、人类学和人机交互的原理。第一阶段描述了社会-文化-技术知识领域之间的知识格局。这是通过民族志访谈来实现的，这些访谈试图了解与水有关的日常做法，以及相关的当地自然资源是如何分类和理解的。这一阶段还使用人工智能方法，如自然语言处理，评估从现有水务操作员培训和OMM支助材料中获得的OMM预期的工程知识。第二阶段由混合模式重点小组组成，以了解最终用户对水服务的评价和期望，并通过绘制混合知识结构图来开发跨文化信息资源，从而为运营商提供可获得的OMM资源。第三阶段评估跨理解领域的知识转移，希望开发可跨水系统和其他偏远社区扩展的协议和材料。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。

Navigating the New Arctic (NNA) is one of NSF's 10 Big Ideas. NNA projects address convergence scientific challenges in the rapidly changing Arctic. The Arctic research is needed to inform the economy, security and resilience of the Nation, the larger region and the globe. NNA empowers new research partnerships from local to international scales, diversifies the next generation of Arctic researchers, enhances efforts in formal and informal education, and integrates the co-production of knowledge where appropriate. This award fulfills part of that aim by addressing interactions among social systems, natural environment, and built environment in the following NNA focus areas: Resilient Infrastructure and Education. A challenge for rural water infrastructure systems in the Arctic is how to operate, manage, and maintain them successfully. Operations, maintenance, and management (OMM) that ensures continuous water access is difficult in these remote areas for many reasons, such as limited access to technical resources and to training across a broad range of skills. Building local workforce capacity and training has been recommended to address this OMM gap. However, underlying these recommendations is the assumption that the knowledge used to build the water systems matches the local knowledge of people operating and interacting with said systems. In rural Alaska, this is not always the case. This project seeks to bridge this gap between expected engineering know-how and the actual know-how of the local community. The approach supports local operators through developing water system OMM training material that is better grounded in local knowledge. At a systems scale, the project also develops educational material describing rural Alaskan water systems, aimed at educating the non-technical user community more broadly. Through bridging the connection between engineering and social context, this project empowers and broadens participation of the current and potential future engineering workforce. To make inroads into this challenge, this interdisciplinary research team engages in a three-phased approach that integrates principles from civil and environmental engineering, sociology, anthropology, and human computer interaction. Phase I characterizes the knowledge landscape between socio-cultural-technical knowledge domains. This is accomplished using ethnographic interviews that seek to understand daily practices that pertain to water, as well as how relevant local natural resources are classified and understood. This phase also uses artificial intelligence approaches, such as natural language processing, to assess the engineering knowledge expected for OMM as derived from existing water operator training and OMM support material. Phase II consists of mixed-modality focus groups to understand end-user valuations and expectations of water services and the development of cross-cultural information resources by mapping the mixed knowledge structures together to produce accessible OMM resources for operators. Phase III evaluates the knowledge transfer across domains of understanding with the hopes of developing protocols and materials that can scale across water systems and to other remote communities.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.