Proto-OKN Theme 1: Creating A Cross-Domain Knowledge Graph to Integrate Health and Justice for Rural Resilience

提高我国农村社区面对各种公共卫生危机的复原力是一个紧迫的重要问题。这些地区对于长期保护空气质量、供水、食品生产和供应链等基本社会服务至关重要--新冠肺炎大流行的经历强调了这一点。这一原型-开放知识网络项目寻求与合作者合作，制定农村复原力所需的综合数据能力，特别是在公共卫生和环境危机的背景下。该项目将与其他相关努力协调，以帮助提高农村在公共卫生和环境领域的复原力。这一目标的核心是有能力收集和分析与健康结果和气候变化以及农村地区健康和正义的社会决定因素有关的数据。跨领域综合卫生和司法知识图谱将提供全面和可访问的信息资源，以服务于农村社区内在资源分配、政策制定和建立伙伴关系方面的各种应用。该项目将生成强大的学习科学方法、计算模型、设计框架、软件制品和经验数据的集合，以提供丰富的资源，进一步推动知识图谱在农村公共卫生中的使用。该项目通过跨各种数据集的迁移学习和生成性学习机制来解决数据的异质性、稀疏性和隐私方面的挑战，重点关注那些提供社会和文化背景的数据。它通过使用以社区为基础的参与性研究模式，通过积极吸引领域知识专家和广泛的利益攸关方来开发知识图谱，从而在社会科学研究方面取得进展。所采用的方法涉及构建跨学科知识图谱，旨在合并、描绘和互连先前分离的健康和司法数据集。该项目打算利用国家科学基金会资助的KnowWhere Graph开放式知识网络等资源提供的现有地理丰富服务。由此产生的知识资源可以帮助研究人员、从业者和教育工作者了解农村地区的风险环境和复原力。与阿拉巴马州公共卫生部和大学间政治和社会研究联盟(ICPSR)合作，该项目将针对不同的利益相关者群体，包括跨学科研究人员、教育工作者、学生、学校管理人员和多个实践领域的行业合作伙伴。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。

Enhancing the resilience of our nation’s rural communities in the face of various public health crises is a matter of pressing importance. These are regions of the country that are vital to the long-term preservation of essential societal services such as air quality, water supply, food production, and supply chains—a realization that has been underscored by the CoVID-19 pandemic experience. This Prototype-Open Knowledge Network project seeks to work with collaborators to map out the integrated data capabilities required for rural resilience, particularly in the context of public health and environmental crises. The project will coordinate with other related efforts to help enhance rural resilience in the areas of public health and the environmental. Central to this objective is the ability to collect and analyze data related to health outcomes and climate change along with social determinants of health and justice within rural locales. The cross-domain integrated health and justice knowledge graph will provide a comprehensive and accessible information resource to serve a variety of applications in resource allocation, policy development, and partnership establishment within rural communities. The project will generate a robust collection of learning science methodologies, computational models, design frameworks, software artifacts, and empirical data to provide a rich resource to further advance the use of knowledge graphs in rural public health.The project tackles data challenges in heterogeneity, sparsity, and privacy of data using transfer learning and generative learning mechanisms across a variety of datasets, with an emphasis on those data that provide social and cultural context. It makes advances in social science research via the use of a community-based participatory research model for developing a knowledge graph by actively engaging domain knowledge experts along with a broad spectrum of stakeholders. The methods employed involve construction of an interdisciplinary knowledge graph designed to merge, portray, and interconnect previously separate health and justice data sets. The project intends to utilize existing geo-enrichment services offered by resources such as the NSF-funded KnowWhereGraph open knowledge network. The resulting knowledge resource can help researchers, practitioners, and educators in their understanding of risk environments and resilience of rural locales. Working with the Alabama Department of Public Health and the Inter-University Consortium for Political and Social Research (ICPSR), the project will target a diverse group of stakeholders that includes interdisciplinary researchers, educators, students, school administrators, and industry partners across multiple practice domains.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.