This five-day virtual workshop will provide researchers an overview of best data management practices, data science tools for cleaning and analyzing data, and concrete steps and methods for more easily documenting and preserving their data at the Arctic Data Center. Examples tools include R, RMarkdown, and git/GitHub.

This course will provide background in both the theory and practice of reproducible research, spanning all portions of the research life-cycle, from ethical data collection following the CARE principles to engage with local stakeholders, to data publishing. Organizers strongly encourage applicants to have a moderate understanding of R in order to maximize their learning experience in this course.

Topics covered will include:

  • Literate analysis (RMarkdown),
  • Data wrangling (tidyr/dplyr),
  • Data publishing,
  • Visualization (ggplot2/sf),
  • Code versioning (git), and
  • Ethical data procedures (CARE principles).

Registration deadline: 31 October 2023

For more information and to register, go to:
Registration webform

For questions, contact:

Angie Garcia