HDR Institute: Geospatial Understanding through an Integrative Discovery Environment

HDR 研究所：通过综合发现环境了解地理空间

• 批准号: 2118329
• 负责人: Shaowen Wang
• 金额: $ 1500万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2118329&HistoricalAwards=false
• 关键词: HDR; Institute; Geospatial; Understanding; through

This project establishes the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE). In today’s interconnected world, disasters such as floods and droughts are rarely isolated events, and their cascading effects are often felt far beyond their locations of origin. I-GUIDE creates an integrative discovery environment that enables the harnessing of geospatial data for understanding interconnected interactions across diverse socioeconomic-environmental systems to enhance community resilience and environmental sustainability. I-GUIDE nurtures a diverse and inclusive geospatial discovery community across many disciplines by bridging disciplinary digital data divides with broader impacts amplified through a well-trained and diverse workforce and proactive engagement of minority and underrepresented groups. The project leverages existing collaborations with its diverse member and partner organizations, representing academic, governmental, and industrial institutions, thereby extending its reach across the U.S. and the globe. The influence of I-GUIDE’s new knowledge frontiers impact solutions to real-world problems and geospatial decisions, with significance ranging from the nation’s economic development to security. I-GUIDE builds upon relationships with the museum and informal science education communities as well as libraries and news media to raise public awareness about the contributions of the geospatial data revolution to society. Globalization has intensified and extended the impacts of socioeconomic-environmental interactions across long distances, a process known as telecoupling. I-GUIDE’s integrative discovery environment is vital to transform innovative theories, concepts, methods, and tools focusing geospatial synthesis that drive novel capabilities for addressing scientific questions of how to harness geospatial data for multi-scale and telecoupling discoveries to enhance community resilience and environmental sustainability. Two substantive and convergent scientific problems are addressed: (1) Water security, to evaluate geospatial and socioeconomic impacts of hydroclimatic extremes that are related to environmental and infrastructure sustainability, and (2) Biodiversity and food security, to enhance basic understanding of biodiversity dynamics in the face of nearby and distant disasters, global changes, international trade, and dynamic land use transitions. Transformative geospatial understanding gained from solving these interrelated problems are translated into digital resources and tools made available online through an open I-GUIDE platform for a variety of educational and training activities to serve a broad and diverse audience. Through this platform, the next-generation workforce can acquire geospatial knowledge coupled with data-driven technological skills for decision-making and problem-solving experiences. This project is part of the National Science Foundation's Big Idea activities in Harnessing the Data Revolution (HDR). The award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Behavioral and Cognitive Sciences, the Division of Social and Economic Sciences, and the Office of Multidisciplinary Activities within the Directorate for Social, Behavioral and Economic Sciences; the Division of Earth Sciences within the Directorate for Geosciences; the Division of Mathematical Sciences within the Directorate for Mathematical and Physical Sciences, and by the Division of Information and Intelligent Systems within the Directorate for Computer and Information Science and Engineering.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.

该项目建立了通过综合发现环境了解地理空间研究所。在当今相互关联的世界中，洪水和干旱等灾害很少是孤立的事件，其连带影响往往远远超出其发生地。I-GUIDE创造了一个综合性的发现环境，使人们能够利用地理空间数据来了解不同社会经济环境系统之间相互关联的相互作用，以增强社区的复原力和环境的可持续性。I-GUIDE通过弥合学科数字数据鸿沟，培养了一个跨越许多学科的多元化和包容性的地理空间发现社区，并通过训练有素和多元化的员工队伍以及少数群体和代表性不足群体的积极参与扩大了更广泛的影响。该项目利用与代表学术、政府和工业机构的不同成员和合作伙伴组织的现有合作，从而将其影响力扩展到美国和地球仪。I-GUIDE的新知识前沿的影响力影响了现实世界问题和地理空间决策的解决方案，其意义从国家的经济发展到安全。I-GUIDE建立在与博物馆和非正式科学教育界以及图书馆和新闻媒体的关系基础上，以提高公众对地理空间数据革命对社会贡献的认识。全球化加强和扩大了远距离社会经济-环境相互作用的影响，这一过程被称为远距离耦合。I-GUIDE的综合发现环境对于转变创新理论、概念、方法和工具至关重要，这些创新理论、概念、方法和工具侧重于地理空间综合，推动新的能力，以解决如何利用地理空间数据进行多尺度和远距离耦合发现的科学问题，从而增强社区复原力和环境可持续性。解决了两个实质性和趋同的科学问题：（1）水安全，以评估与环境和基础设施可持续性有关的水文气候极端事件的地理空间和社会经济影响，以及（2）生物多样性和粮食安全，以加强对生物多样性动态的基本理解，面对附近和遥远的灾害，全球变化，国际贸易和动态土地使用过渡。通过解决这些相互关联的问题而获得的变革性地理空间认识转化为数字资源和工具，通过开放的I-GUIDE平台在线提供，用于各种教育和培训活动，为广泛和多样化的受众服务。通过这个平台，下一代劳动力可以获得地理空间知识以及数据驱动的技术技能，以获得决策和解决问题的经验。该项目是国家科学基金会利用数据革命（HDR）的大创意活动的一部分。 高级网络基础设施办公室的奖项得到了行为和认知科学司、社会和经济科学司以及社会、行为和经济科学局多学科活动办公室的联合支持;地球科学局地球科学司;数学和物理科学理事会内的数学科学司，以及计算机和信息科学与工程理事会信息和智能系统司。该奖项反映了NSF的法定使命，并已被认为是值得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的支持。

项目成果

The Value of Water in US Agriculture: integrating spatially and temporally heterogeneous hydroclimatic and economic data

水在美国农业中的价值：整合时空异质水文气候和经济数据

• DOI: 10.13019/9mxe-t280
• 发表时间: 2023
• 期刊: MyGeoHUB
• 作者: Haqiqi, Iman

CyberGIS-Cloud: A unified middleware framework for cloud-based geospatial research and education

Cyber​​GIS-Cloud：用于基于云的地理空间研究和教育的统一中间件框架

• DOI: 10.1145/3491418.3535148
• 发表时间: 2022
• 期刊: PEARC '22: Practice and Experience in Advanced Research Computing
• 作者: Baig, Furqan;Michels, Alexander;Xiao, Zimo;Han, Su Yeon;Padmanabhan, Anand;Li, Zhiyu;Wang, Shaowen
• 通讯作者: Wang, Shaowen

On constructing limits-of-acceptability in watershed hydrology using decision trees

利用决策树构建流域水文学的可接受限度

• DOI: 10.1016/j.advwatres.2023.104486
• 发表时间: 2023
• 期刊: Advances in Water Resources
• 影响因子: 4.7
• 作者: Gupta, Abhinav;Govindaraju, Rao S.;Li, Pin-Ching;Merwade, Venkatesh
• 通讯作者: Merwade, Venkatesh

Few-Shot Fine-Grained Entity Typing with Automatic Label Interpretation and Instance Generation

• DOI: 10.1145/3534678.3539443
• 发表时间: 2022-06
• 期刊: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
• 作者: Jiaxin Huang;Yu Meng;Jiawei Han

Building cyberinfrastructure for the reuse and reproducibility of complex hydrologic modeling studies

构建网络基础设施以实现复杂水文模型研究的重用和可重复性

• DOI: 10.1016/j.envsoft.2023.105689
• 发表时间: 2023
• 期刊: Environmental Modelling & Software
• 影响因子: 4.9
• 作者: Maghami, Iman;Van Beusekom, Ashley;Hay, Lauren;Li, Zhiyu;Bennett, Andrew;Choi, YoungDon;Nijssen, Bart;Wang, Shaowen;Tarboton, David;Goodall, Jonathan L.
• 通讯作者: Goodall, Jonathan L.