Elements: Open-Source Cyberinfrastructure as a Decision Engine for Socioeconomic Disaster Risk (DESDR)

要素：开源网络基础设施作为社会经济灾害风险决策引擎 (DESDR)

• 批准号: 2103794
• 负责人: Daniel Osgood
• 金额: $ 60万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103794&HistoricalAwards=false
• 关键词: Elements; Open; Source; Cyberinfrastructure; Decision

Natural disasters can have long-lasting financial consequences for vulnerable populations such as farmers, but disparate disaster impacts make the accurate and timely deployment of limited resources such as disaster funding and relief very difficult. This project will develop an open-source suite of cyberinfrastructure tools, called the Decision Engine for Socioeconomic Disaster Risk (DESDR), to fill data voids by collecting and cleaning disaster risk data directly from affected populations. As well, the project will combine those data with satellite data to provide farmers and others with data and tools to make better informed decisions about disaster risk management. Existing approaches for disaster detection, mapping, and prediction primarily rely on satellite and sensor data that are susceptible to errors and do not measure how disasters directly affect regions and individuals. This project will develop open-source software infrastructure employing data from rural populations, and then use the data to build more accurate disaster risk models. The cyberinfrastructure, DESDR, will provide a scalable, customizable data collection platform using mobile messaging services that take local incentives and community norms into account, and will be used to gather data on from affected communities. A data visualization and cleaning platform will enable local partners and researchers to cross-reference the data with satellite and sensor data sources, and to identify and clean data errors. A database architecture will store the data in an interoperable format. And, a web-based interface will provide government agencies, policy makers, researchers, and other stakeholders the ability to interactively create and back-test disaster risk models. DESDR will be disseminated as open-source, ready-to-deploy software to a user community of governmental meteorological agencies, humanitarian program officers, insurers and affiliated agricultural and social scientists. By combining these tools into an integrated, extensible process cyberinfrastructure, DESDR will directly involve vulnerable populations in the design of solutions, enabling disaster risk managers to scale up critical relief programs to reach multitudes of farmers and others while providing an unprecedented voice to the project beneficiaries.This project is funded by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering, and by the Division of Social and Economic Sciences in the Directorate for Social, Behavioral & Economic Sciences.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.

自然灾害可能对农民等弱势群体造成长期的财政后果，但不同的灾害影响使准确和及时部署救灾资金和救济等有限资源变得非常困难。该项目将开发一套开源的网络基础设施工具，称为社会经济灾害风险决策引擎（DESDR），通过直接从受影响人口收集和清理灾害风险数据来填补数据空白。此外，该项目将把这些数据与卫星数据联合收割机结合起来，为农民和其他人提供数据和工具，以便就灾害风险管理作出更明智的决定。现有的灾害检测、制图和预测方法主要依赖于卫星和传感器数据，这些数据容易出错，而且无法衡量灾害如何直接影响地区和个人。该项目将利用来自农村人口的数据开发开源软件基础设施，然后利用这些数据建立更准确的灾害风险模型。网络基础设施DESDR将提供一个可扩展、可定制的数据收集平台，使用考虑到当地激励措施和社区规范的移动的信息服务，并将用于收集受影响社区的数据。一个数据可视化和清理平台将使当地合作伙伴和研究人员能够将数据与卫星和传感器数据源进行交叉引用，并识别和清理数据错误。数据库体系结构将以可互操作的格式存储数据。此外，一个基于网络的界面将为政府机构、决策者、研究人员和其他利益相关者提供交互式创建和回溯测试灾害风险模型的能力。DESDR将作为开放源代码、随时可部署的软件分发给政府气象机构、人道主义方案官员、保险公司和附属农业和社会科学家的用户社区。通过将这些工具组合成一个集成的、可扩展的过程网络基础设施，DESDR将直接让弱势群体参与解决方案的设计，使灾害风险管理人员能够扩大关键的救援计划，以达到广大农民和其他人，同时为项目受益人提供前所未有的声音。该项目由计算机和信息科学局高级网络基础设施办公室资助，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。

项目成果

Reptile: Aggregation-level Explanations for Hierarchical Data

Reptile：分层数据的聚合级解释

• DOI: 10.1145/3514221.3517854
• 发表时间: 2022
• 期刊: SIGMOD
• 作者: Huang, Zezhou;Wu, Eugene
• 通讯作者: Wu, Eugene