NRT-DESE: Interdisciplinary Graduate Training to Understand and Inform Decision Processes Using Advanced Spatial Data Analysis and Visualization

NRT-DESE：使用高级空间数据分析和可视化来理解和指导决策过程的跨学科研究生培训

• 批准号: 1633299
• 负责人: Robert Harrison
• 金额: $ 299.39万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-15 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1633299&HistoricalAwards=false
• 关键词: NRT; DESE; Interdisciplinary; Graduate; Training

This National Science Foundation Research Traineeship (NRT) award to SUNY at Stony Brook will provide science and engineering graduate students with unique interdisciplinary skills to assist and eventually lead in the translation of complex data-enabled research into informed decisions and sound policies. Within all sectors of industry and government, effective decision making depends on the ability of scientists to interpret data and communicate results in a way that supports the decision-making process. This new training program responds to this challenge with an interdisciplinary set of new courses and a suite of activities united by the theme of "Scientific Training and Research to Inform DEcisions" (STRIDE). It specifically will include the rarely explicitly taught skills of decision support, such as understanding the perspectives of stakeholders, science communication, and translating scientific uncertainty. The project anticipates training 90 PhD students, including at least 20 funded doctoral trainees, and a similar number of non-trainee MS and PhD students that will participate in program components from the departments of atmospheric and marine sciences, ecology and evolution, computer science, biomedical informatics, applied mathematics and statistics, journalism, and advanced computational science. STRIDE will initially target environmental sustainability (including climate change, marine ecology and natural resource management, and illegal deforestation) and energy sustainability, and will add population health in the third year. Research in advanced visual data analytics to support decisions will be pervasive in all areas. The cross fertilization between disciplines focused on decision making will prepare students to make discoveries in the domain sciences and will lead to innovations in visual data analytics. To develop research skills in new contexts and to diversify career perspectives, trainees will have summer externships at non-academic partners such as IBM Research, Brookhaven National Laboratory, and the National Marine Fisheries Service, with new partners being added each year. The program comprises three major components: 1) a set of specially designed courses on decision support, spatial data analysis, visualization, and communication required for all students; 2) training in a STEM domain discipline; and 3) a set of non-course-based program elements in which all students will participate, including recruitment, skill development, professional development, and personal development. In addition to degrees in their domain-science disciplines, students will receive a graduate certificate from STRIDE after completing the three proposed courses and program activities. Specific innovations to be tested by rigorous evaluation include the seminar course in scientific decision support that will feature many government/industry scientists, decision makers, and journalists remotely leading discussions on the science, societal, and other challenges associated with decision support in their respective fields. Another new course focusing on science communication for decision makers will be provided by the Alan Alda Center for Communicating Science in the School of Journalism.The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.

美国国家科学基金会授予纽约州立大学石溪分校的研究实习生 (NRT) 奖，将为科学和工程研究生提供独特的跨学科技能，以协助并最终领导将复杂的数据支持研究转化为明智的决策和健全的政策。在工业和政府的所有部门中，有效的决策取决于科学家以支持决策过程的方式解释数据和传达结果的能力。这个新的培训计划通过一套跨学科的新课程和一系列以“科学培训和研究为决策提供信息”（STRIDE）为主题的活动来应对这一挑战。具体来说，它将包括很少明确教授的决策支持技能，例如理解利益相关者的观点、科学传播和转化科学不确定性。该项目预计培训 90 名博士生，其中包括至少 20 名受资助的博士生，以及类似数量的非受训硕士和博士生，他们将参加来自大气和海洋科学、生态与进化、计算机科学、生物医学信息学、应用数学和统计学、新闻学和高级计算科学。 STRIDE最初的目标是环境可持续性（包括气候变化、海洋生态和自然资源管理以及非法砍伐森林）和能源可持续性，并将在第三年增加人口健康。支持决策的高级可视化数据分析研究将遍及所有领域。专注于决策的学科之间的交叉融合将为学生在领域科学领域的发现做好准备，并将带来可视化数据分析的创新。为了在新环境中培养研究技能并实现职业前景多元化，学员将在 IBM 研究中心、布鲁克海文国家实验室和国家海洋渔业局等非学术合作伙伴处进行暑期实习，并且每年都会增加新的合作伙伴。该项目包括三个主要部分：1）一套专门设计的课程，涉及所有学生所需的决策支持、空间数据分析、可视化和沟通； 2) STEM 领域学科培训； 3) 所有学生都将参与的一系列非课程项目要素，包括招聘、技能发展、专业发展和个人发展。除了其领域科学学科的学位外，学生在完成三门拟议课程和项目活动后还将获得 STRIDE 的研究生证书。通过严格评估测试的具体创新包括科学决策支持研讨会课程，许多政府/行业科学家、决策者和记者将远程主持有关各自领域决策支持相关的科学、社会和其他挑战的讨论。新闻学院的艾伦·阿尔达科学传播中心将向决策者提供另一门关注科学传播的新课程。 NSF 研究实习生 (NRT) 计划旨在鼓励开发和实施大胆的、具有潜在变革性的新模型STEM 研究生教育培训。培训课程致力于通过创新、循证且符合不断变化的劳动力和研究需求的综合培训模式，对高度优先的跨学科研究领域的 STEM 研究生进行有效培训。

项目成果

Forests, Coca, and Conflict: Grass Frontier Dynamics and Deforestation in the Amazon-Andes

森林、古柯和冲突：亚马逊-安第斯山脉的草地边界动态和森林砍伐

• DOI: 10.31389/jied.87
• 发表时间: 2021
• 期刊: Journal of Illicit Economies and Development
• 作者: Davalos, Liliana M.;Davalos, Eleonora;Holmes, Jennifer;Tucker, Clara;Armenteras, Dolors
• 通讯作者: Armenteras, Dolors

Spatial autocorrelation reduces model precision and predictive power in deforestation analyses

• DOI: 10.1002/ecs2.1824
• 发表时间: 2017-05-01
• 期刊: ECOSPHERE
• 影响因子: 2.7
• 作者: Mets, Kristjan D.;Armenteras, Dolors;Davalos, Liliana M.
• 通讯作者: Davalos, Liliana M.

Opposition Support and the Experience of Violence Explain the Colombian Peace Referendum. Journal of Politics in Latin America 10(2): 99-122

反对派支持和暴力经历解释哥伦比亚和平公投。

• 发表时间: 2018
• 期刊: Journal of politics in Latin America
• 影响因子: 1.3
• 作者: Dávalos, E.

Perceptions of Barriers to Career Progression for Academic Women in STEM

• DOI: 10.3390/soc11020027
• 发表时间: 2021-06-01
• 期刊: SOCIETIES
• 影响因子: 2.1
• 作者: O'Connell, Christine;McKinnon, Merryn
• 通讯作者: McKinnon, Merryn

Perceptions of stereotypes applied to women who publicly communicate their STEM work

• DOI: 10.1057/s41599-020-00654-0
• 发表时间: 2020-12-25
• 期刊: HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
• 作者: McKinnon, Merryn;O'Connell, Christine
• 通讯作者: O'Connell, Christine