Collaborative Research: Elements: SENSORY: Software Ecosystem for kNowledge diScOveRY - a data-driven framework for soil moisture applications

收集土壤湿度数据的工具（如原位土壤传感器和卫星）具有不同的能力。原位土壤湿度数据具有细粒度的空间和高时间分辨率，但仅在有限的地区可用；卫星数据可在全球范围内获得，但分辨率较粗。现有研究土壤水分数据动态特征的软件工具在多个时空尺度上模拟土壤水分的能力有限，这些局限性阻碍了科学家解决诸如野火管理、粮食和水安全等紧迫实际问题的能力。土壤湿度数据的准确收集和有效建模对于解决紧迫的环境挑战至关重要。这个跨学科项目为土壤湿度应用设计、构建和共享一个数据驱动的软件生态系统。这个软件生态系统模型和预测土壤湿度的尺度适合支持林业、精准农业和地表水文学的研究。该项目将科学界的多学科进展（如大规模生成数据集和支持基于云的网络基础设施）联系起来，开发一个数据驱动的软件生态系统，用于分析、可视化和从不断增长的数据收集（从细粒度的原位土壤传感器信息到粗粒度的全球卫星测量）中提取知识，并将这些知识发布到环境科学的应用中。具体而言，该项目(a)开发可扩展的方法来整合和分析多个时空尺度的土壤湿度数据；(b)实施数据驱动的软件生态系统，以获取复杂的信息，并提供基础和应用知识，以告知对土壤水分动力学感兴趣的研究人员和利益相关者（科学家、教育工作者、政府机构、政策制定者）；(c)建立网络基础设施，以支持云平台上的发现，降低资源障碍，提高可访问性和互操作性。该奖项由先进网络基础设施办公室颁发，由水文科学项目、地球科学部和美国国家科学基金会地球科学理事会综合与协作教育与研究部联合支持。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。

Tools for gathering soil moisture data (such as in situ soil sensors and satellites) have differing capabilities. In situ soil moisture data has fine-grained spatial and high temporal resolution, but is only available in limited areas; satellite data is available globally, but is more coarse in resolution. Existing software tools for studying the dynamic characteristics of soil moisture data are limited in their ability to model soil moisture at multiple spatial and temporal scales, and these limitations hamper scientists’ ability to address urgent practical problems such as wildfire management and food and water security. Accurate gathering and effective modeling of soil moisture data are essential to address pressing environmental challenges. This interdisciplinary project designs, builds, and shares a data-driven software ecosystem for soil moisture applications. This software ecosystem models and predicts soil moisture at scales suitable to support studies in forestry, precision agriculture, and earth surface hydrology.This project connects multi-disciplinary advances across the scientific community (such as generating datasets at scale and supporting cloud-based cyberinfrastructures) to develop a data-driven software ecosystem for analyzing, visualizing, and extracting knowledge from the growing data collections (from fine-grained, in situ soil sensor information to coarse-grained, global satellite measurements) and releasing this knowledge to applications in environmental sciences. Specifically, this project (a) develops scalable methodologies to integrate and analyze soil moisture data at multiple spatial and temporal scales; (b) implements a data-driven software ecosystem to access complex information and provide basic and applied knowledge to inform researchers and stakeholders interested in soil moisture dynamics (scientists, educators, government agencies, policy makers); and (c) builds cyberinfrastructures to support discovery on cloud platforms, lowering resource barriers to improve accessibility and interoperability.This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Hydrologic Sciences Program, the Division of Earth Sciences, and the Division of Integrative and Collaborative Education and Research within the NSF Directorate for Geosciences.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.