Training opportunities for the Arctic research community

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. Those opportunities and activities are listed below. We also launched a Data Science Fellowship in January 2018, and have developed materials for undergraduate instructors as well.

Additionally, we offer trainings and presentations at various scientific meetings and online webinars.

Upcoming Trainings and Presentations

Presentations

All upcoming training courses are funded by the Arctic Data Center award from NSF and are specialized for Arctic research data needs. For in-person trainings we have limited funds to support travel and accommodation expenses, and the opportunity to opt-in for partial or full funding will be provided in the course application (coming soon).

Reproducible Practices for Arctic Research using R
Virtual
February 14th – February 18th 2022
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 include R, Rmarkdown, and git/GitHub. This course provides 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 who have moderate programming experience (R preferred) and an interest in gaining practical skills in reproducible research techniques.

Scalable and Computationally Reproducible Approaches to Arctic Research
National Center for Ecological Analysis and Synthesis, Santa Barbara, California
March 21st – March 25th 2022
This 5-day in-person workshop will provide researchers with an introduction to advanced topics in computationally reproducible research in Python and R, 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.

Fundamentals in Data Management for Qualitative and Quantitative Arctic Research
National Center for Ecological Analysis and Synthesis, Santa Barbara, California
April 18th – April 22nd 2022
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 little to no programming experience who want to gain skills in ethical reproducible research for qualitative and/or quantitative data.

Conferences:

American Geophysical Union Fall Meeting
Virtual & New Orleans, LA
December 13th – December 17th 2021
Arctic Data Center staff will be volunteering at the AGU Data Help Desk. More information will be available soon.

Arctic Science Summit Week
Virtual & Tromsø, Norway
March 26th – April 1st 2022
More information will be available soon.

Past Trainings and Presentations

We’ve participated in a variety of meetings, both in person and virtual, domain-specific and polar-specific. Take a walk down memory lane – most presentations are linked or have video recordings available.

Arctic Science Summit Week
Virtual
March 19th – March 26th 2021
Chris Beltz, a data fellow of the Arctic Data Center, presented the following talk – Analysis of Arctic Data Center Metadata using FAIR principles shows increased quality across multiple metrics – in session ID:68 – Progress Towards Realizing Data Sharing for the Arctic Region and Beyond (2).

International Congress of Arctic Social Sciences X
Virtual & Arkhangelsk, Russia
June 15th – June 19th 2021
Erin McLean, Community Engagement and Outreach Coordinator, presented the following talk – Managing sensitive qualitative data from Arctic social science fields.

For questions, contact support@arcticdata.io