RIDIR: Collaborative Research: A Data Science Platform and Mechanisms for Its Sustainability

RIDIR：协作研究：数据科学平台及其可持续性机制

• 批准号: 1831551
• 负责人: Laura LopezHoffman
• 金额: $ 150万
• 依托单位: University of Arizona
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831551&HistoricalAwards=false
• 关键词: RIDIR; Collaborative; Research; Data; Science

This research will design and develop a data science platform that provides access to documents. The platform will make available for the first-time analytical tools, using natural language computer processing and data science to enable systematic research and inquiry by practitioners, project proponents, scholars, and the public to answer a host of critical questions. Using natural language processing and data science, this research will design and develop a data science platform. The research team will produce a blueprint for the platform and validate its functionality with a community of scholars and practitioners. The team will establish the platform structure, ingest data, and refine analytical tools to integrate documents across many repositories, link text to metadata even when text comes from one source and the metadata from another, infer more detailed types of metadata that are not present in any of the existing repositories from analysis of the text, and allow researchers, contractors, and policy analysts to pose complex questions and answer them via analysis of documents. The team will also build a user community to catalyze scholarship and application and develop long-term mechanisms to ensure the sustainability and continued growth, management, and use of the platform and its resources.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.

这项研究将设计和开发一个数据科学平台，提供对文档的访问。该平台将首次提供分析工具，使用自然语言计算机处理和数据科学，使从业人员，项目支持者，学者和公众能够进行系统的研究和调查，以回答一系列关键问题。利用自然语言处理和数据科学，本研究将设计和开发一个数据科学平台。研究小组将为该平台制定蓝图，并与学者和从业人员共同验证其功能。该团队将建立平台结构，摄取数据，并改进分析工具，以整合许多存储库中的文档，即使文本来自一个来源，元数据来自另一个来源，也将文本链接到元数据，推断更详细的元数据类型，这些元数据不存在于任何现有的存储库中，通过分析文本，并允许研究人员，承包商，和政策分析师提出复杂的问题，并通过分析文件来回答这些问题。该团队还将建立一个用户社区，以促进奖学金和申请，并制定长期机制，以确保平台及其资源的可持续性和持续增长，管理和使用。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

Toward NEPA performance: A framework for assessing EIAs

迈向 NEPA 绩效：评估 EIA 的框架

• DOI: 10.1016/j.eiar.2022.106879
• 发表时间: 2022
• 期刊: Environmental Impact Assessment Review
• 影响因子: 7.9
• 作者: Emerson, Kirk;Baldwin, Elizabeth;Scott, Tyler A.;Pidot, Justin R.;Lien, Aaron M.;Currim, Faiz;Bethard, Steven;Ram, Sudha;Miller, Marc L.;López-Hoffman, Laura
• 通讯作者: López-Hoffman, Laura

Effectiveness in NEPA decision making: in search of evidence and theory

• DOI: 10.1080/1523908x.2019.1615421
• 发表时间: 2019-07-04
• 期刊: JOURNAL OF ENVIRONMENTAL POLICY & PLANNING
• 影响因子: 3.2
• 作者: Emerson, Kirk;Baldwin, Elizabeth
• 通讯作者: Baldwin, Elizabeth

Inferring missing metadata from environmental policy texts

• DOI: 10.18653/v1/w19-2506
• 发表时间: 2019-06
• 作者: Steven Bethard;Egoitz Laparra;Sophia Wang;Yiyun Zhao;Ragheb Al-Ghezi;Aaron M. Lien;L. López-Hoffman