Upcoming Training 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. Applications for our 2025 courses are now rolling out!

Fundamentals of Qualitative and Quantitative Arctic Research Using R

Course Dates: January 27th – 31st, 2025
Taught in-person at the National Center for Ecological Analysis and Synthesis, Santa Barbara, California

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 will 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.

A variety of topics will be discussed, such as:

  • Reproducible research 101
  • Qualitative data management for reproducible research
  • Definitions of data and best practices for management
  • Data publishing
  • Cleaning and wrangling data
  • Ethical data collection (CARE principles)
  • Introduction to programming R
  • Reproducible survey workflows
  • Text analysis in R
  • Metadata 
  • Working with census data

Applications will remain open until August 16, 2024!

Link to Application

Eligibility

Participation in all workshops is limited. We encourage both early-career and established researchers from the Arctic research community to apply. Selection will be based on:

  • Current research or work activities
  • Previous experience with open science practices, data management techniques, and analysis methods
  • Access to training in these areas, both current and former

Priority will be given to individuals currently funded through NSF Polar Programs.

How to Apply

Applicants should complete the online application form at the link above.  The application form requests basic demographics in addition to information about research background and data science training and skills. Please also submit a 2-page Curriculum Vita in PDF format. 

Other Courses to Come

Reproducible Approaches to Arctic Research Using R

Course Dates: February 24-28, 2025
Taught all VIRTUALLY

This 5-day remote workshop will provide 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. Applications are set to open on August 5th, 2024!

Topics include:

  • Literate analysis (RMarkdown),
  • data wrangling (tidyr/dplyr),
  • data publishing,
  • visualization (ggplot2/sf),
  • code versioning (git),
  • ethical data procedures (CARE principles)

Scalable and Computationally Reproducible Approaches to Arctic Research

Course Dates: April 7-11, 2025
Taught in-person at the National Center for Ecological Analysis and Synthesis, Santa Barbara, CA

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. This course is intended for Arctic researchers with a solid foundation in programming (R, python, or similar). Applications are set to open on September 2nd, 2024!

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