Treffer: Enhancing Undergraduate Research Readiness in Water and Energy: A One-Week Bootcamp Integrating FAIR Data Principles, Python, and Machine Learning.

FAIR principles promote effective data management practices across domains, enhancing the value of digital assets. Despite their importance, few undergraduate programs systematically integrate and evaluate FAIR principles. The Justice in Data program, an NSF-funded initiative begun in 2023, targets undergraduates conducting research in water and energy. The program involved a one-week synchronous bootcamp focusing on Python programming basics, FAIR data principles, and machine learning followed by summer mentoring circles and a research symposium. This article discusses bootcamp features, and reports findings related to students' gains in i) familiarity, ii) research confidence, and iii) knowledge about cyberinfrastructure tools and FAIR principles, as well as their iv) highlighted characteristics of the bootcamp. Results indicate increased familiarity and confidence post-bootcamp, though knowledge gains were limited. Participants valued the bootcamp's robust Python and machine learning foundation, especially in water resources. Interactive sessions, hands-on practices, and expert FAIR guidance fostered a supportive learning environment. Suggestions for improvement included more interactive activities, extended program duration for deeper coverage, and flexible scheduling. Future iterations aim to enhance educational outcomes by addressing these recommendations. [ABSTRACT FROM AUTHOR]