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CyberTraining: Pilot: Justice in Data: An intensive, mentored online bootcamp developing FAIR data competencies in undergraduate researchers in the water and energy sectors

CyberTraining: Pilot: Justice in Data: An intensive, mentored online bootcamp developing FAIR data competencies in undergraduate researchers in the water and energy sectors
网络培训:试点:数据正义:一个强化的、有指导的在线训练营,旨在培养水和能源领域本科研究人员的公平数据能力
批准号:
2230054
负责人:
Jessica Eisma
金额:
$29.88万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-01-01 至 2024-12-31

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英文摘要
Dramatic development of information technology has produced an unprecedented volume of data around the world, providing an opportunity for researchers to leverage cyberinfrastructure (CI) to develop data-driven solutions to global issues. However, the research workforce in the energy and water fields are often under-equipped to incorporate CI into their workflows. This project creates a unique cybertraining opportunity for undergraduate researchers in the energy and water fields through an online, weeklong bootcamp, summer mentoring, and a closing research symposium. Students train in every facet of CI, from data access and sharing to data analytics and visualization, which are precursors to knowledge and discovery. The bootcamp and training materials will increase the application of Findable, Accessible, Interoperable, and Reusable (FAIR) data principles in research, encouraging a transition towards just practices in research. Faculty participation in two workshops complement and extend the mission of the undergraduate researcher components. The overall goal of this project is to develop and test an extracurricular CI instructional framework while also identifying the CI adoption and implementation needs of the established research workforce, thus fulfilling NSF's mission to promote the progress of science. This project seeks to develop and test an accessible framework and instructional materials for expanding CI adoption among diverse, budding researchers and to broaden the adoption of CI in established research laboratories. To do so, the project creates an intensive weeklong FAIR data principles and introductory machine learning bootcamp with an innovative research justice theme for undergraduate students conducting summer research in water or energy and delivers two workshops. The bootcamp explores high-impact topics for new CI users, including large-scale data access, data analytics, and data visualization. Mentoring of bootcamp participants will continue throughout the summer, and an end-of-summer online research symposium provides a forum for bootcamp participants to describe how they (1) applied FAIR principles in their summer research and (2) developed workflows and tools for research-related tasks, which may be developed into publishable resources. The two workshops identify opportunities for expanding CI in civil engineering research and explore ways to improve and scale bootcamp content and delivery. The FAIR bootcamp content is designed to encourage students to internalize the content and integrate it into their research, while simultaneously increasing the potential for participants to share their new knowledge and skills with summer research colleagues. This novel bottom-up approach to spreading CI knowledge strengthens the future science and engineering workforce by rapidly growing the number of active researchers with CI competencies.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.
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