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Design a new program to help researchers set up their Research lab in a Collaborative and Reproducible way: https://rds.library.ucsb.edu/reproducible-lab/
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Co-develop a Workshop on AI-assisted coding for researchers https://carpentry.library.ucsb.edu/ai-coding-workshop/
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Teaching database to introduce environmental data scientists to relational data modeling and SQL: https://github.com/UCSB-Library-Research-Data-Services/ASDN-database
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lterdatasampler: Co-led with Dr. Allison Horst, this project aims at developing an R package with 28 datasets from the LTER network to facilitate the teaching of (environmental) data science. FEEDBACK wanted :)
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metajam (maintainer): easily download and read data and metadata from repositories in the DataONE data repositories federation.
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Brun, J., Lyon, N.J., Chen, A., Slette, I., De La Rosa, G., Caselle, J.E., Davis, F.W., Downs, M.R., Enabling data‐driven collaborative and reproducible environmental synthesis science. Methods Ecol Evol. 2025;16: 1061–1074. doi:10.1111/2041-210X.70036
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Brun, J., Janée G., Curty R.G. Ten quick tips for developing a reproducible Shiny application. PLOS Computational Biology. 2025;21: e1013551. doi:10.1371/journal.pcbi.1013551
Here is my personal website https://brunj7.github.io/ to learn more!