Cross-Cutting Improvements: The Development of a Geospatial Big-Data Infrastructure Supporting Socially and Environmentally Relevant Spatial Decision-Making and Analysis

该研究协调网络将促进地理信息系统（GIS）和开放数据科学支持教师和学生研究人员在HBCU（历史上的黑人学院和大学），MSI（少数民族服务机构）和当地社区的区域集群。 该项目将由北卡罗来纳州中央大学新成立的健康与科学学院（CHAS）多个部门的研究人员团队以及该地区其他三个少数民族服务机构领导。 该研究协调网络将为区域和更大的科学界提供服务，在开发和部署数据基础设施和服务方面推进开放科学实践和原则，以支持在社会和环境相关研究活动中使用地理空间数据。地理空间数据分析已被证明可以促进对影响COVID-19发病率的健康社会决定因素的理解，以及其他各种各样的社会和环境相关的研究问题。 该项目将协调建立大量新的地理信息系统数据层，并按照公平数据共享原则以及丰富的、基于标准的和机器可读的元数据，将其提供给更大的多学科研究界。来自不同来源和学科的地理参考数据将通过基于元数据模式的标准化描述信息得到丰富和规范化，由专家社区推动，目的是-用户，并与国际和联邦授权的ISO 19115标准兼容，并利用州和地方政府开发和使用的元数据配置文件。高级网络基础设施办公室的这一奖项由该奖项反映了NSF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。

This research coordination network will foster GIS (geographic information systems) and open data science support for faculty and student researchers in a regional cluster of HBCU (Historically Black Colleges and Universities), MSI (minority serving institutions), and local communities. The project will be led by a team of researchers across multiple departments in the newly formed College of Health and Science (CHAS) at North Carolina Central University together with three other minority serving institutions in the region. This research coordination network will serve both the regional and larger scientific communities by advancing open science practices and principles in the development and deployment of data infrastructure and services needed to support the use of geospatial data in socially and environmentally relevant research activities.Geospatial data analysis has been proven to advance the understanding of social determinants of health affecting COVID-19 incidence rates, as well as a wide variety of other socially and environmentally relevant research issues. This project will coordinate the creation of a large number of new GIS data layers and make them available to the larger multidisciplinary research community in accordance with FAIR data sharing principles together with rich, standards-based and machine-readable metadata. Georeferenced data from disparate sources and disciplines will be enriched and normalized by standardized descriptive information based on a metadata schema, driven by the community of experts and intended end-users and compatible with international and federally mandated ISO 19115 standard and utilizing metadata profiles developed and used by state and local governments.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Directorate for Education and Human Resources and the HBCU Excellence in Research Program.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.