Upcoming Learning Opportunities

Each year, our training and outreach staff help provide hands-on training at Arctic research conferences and in dedicated training sessions targeting early-career and under-represented populations. Training and outreach focus on effective means for long-term data management, following a curriculum developed and refined by the open science community. Currently, three different courses are offered for Spring 2022 and theses are free to attend. Those opportunities and activities are listed below.

Scalable and Computationally Reproducible Approaches to Arctic Research

National Center for Ecological Analysis and Synthesis, Santa Barbara, California
March 27 – March 31, 2023

This 5-day in-person workshop will provide researchers with an introduction to advanced topics in computationally reproducible research in python, including software and techniques for working with very large datasets. This includes working in cloud computing environments, docker containers, and parallel processing using tools like parsl and dask. The workshop will also cover concrete methods for documenting and uploading data to the Arctic Data Center, advanced approaches to tracking data provenance, responsible research and data management practices including data sovereignty and the CARE principles, and ethical concerns with data-intensive modeling and analysis.

Topics include:

  • Scalable computing
  • Cloud computing concepts 
  • Docker environments
  • Remote computing
  • Parallel processing and concurrency
  • Large data transfer, data staging
  • Data extraction, I/O efficiency


Who should apply:
Arctic researchers with a solid foundation in programming (R, python, or similar), who have a need to take their skills to the next level to maximize efficiency working with big datasets or running computing-intensive processes.
Deadline: December 5, 2022
Contact training@arcticdata.io with questions

Fundamentals in Data Management for Qualitative and Quantitative Arctic Research

National Center for Ecological Analysis and Synthesis, Santa Barbara, California
January 30 – Feb 3, 2023

This 5-day in-person workshop will provide researchers with an overview of reproducible and ethical research practices, steps and methods for more easily documenting and preserving their data at the Arctic Data Center, and an introduction to programming in R. Special attention be paid to qualitative data management, including practices working with sensitive data. Example datasets will draw from natural and social sciences, and methods for conducting reproducible research will be discussed in the context of both qualitative and quantitative data. Responsible and reproducible data management practices will be discussed as they apply to all aspects of the data life cycle. This includes ethical data collection and data sharing, data sovereignty, and the CARE principles. The CARE principles are guidelines that help ensure open data practices (like the FAIR principles) appropriately engage with Indigenous Peoples’ rights and interests.

Topics include:

  • Reproducible research 101
  • Qualitative data management for reproducible research
  • Definitions of data and best practices for management
  • Data publishing
  • Ethical data collection (CARE principles)
  • Introduction to programming ®
  • Human subjects research considerations
  • Reproducible survey workflows
  • Text analysis in R


Who should apply:
Arctic researchers with entry level skills in R, and a need to learn how to use R for data management
Deadline: Applications are closed for 2023, but will open for 2024 next fall
Contact training@arcticdata.io with questions

Reproducible Practices for Arctic Research Using R

Taught virtually
February 27 – March 3, 2023

This 5-day remote workshop will provided researchers with 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. Example tools included R, Rmarkdown, and git/GitHub. This course provided background in both the theory and practice of reproducible research, spanning all portions of the research lifecycle, from ethical data collection following the CARE principles to engage with local stakeholders, to data publishing..

Topics include:

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


Who should apply:
Arctic researchers with intermediate level skills in R
Deadline: Applications are closed for 2023, but will open for 2024 next fall
Contact training@arcticdata.io with questions