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 focuses on effective means for long-term data management, following a curriculum developed and refined by the open science community. The curricula is open access and is listed below with the past courses.
Reproducible Practices for Arctic Research Using R
Taught virtually
February 26 – March 1, 2024
This remote workshop 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..
Fundamentals in Data Management for Qualitative and Quantitative Arctic Research
Held at National Center for Ecological Analysis and Synthesis, Santa Barbara, California
January 22nd – 26th, 2024
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.
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 R
- Human subjects research considerations
- Reproducible survey workflows
- Text analysis in R
Scalable and Computationally Reproducible Approaches to Arctic Research
National Center for Ecological Analysis and Synthesis, Santa Barbara, California
March 27 – March 31, 2023
This workshop provided researchers with an introduction to advanced topics in computationally reproducible research in python, including software and techniques for working with very large datasets. The workshop also covered 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.
Reproducible Practices for Arctic Research Using R
Taught virtually
February 27 – March 3, 2023
This remote workshop 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..
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 workshop provided 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.
Scalable and Computationally Reproducible Approaches to Arctic Research
National Center for Ecological Analysis and Synthesis, Santa Barbara, California
September 19 – September 23, 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:
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
Reproducible Practices for Arctic Research Using R
Virtual
February 14th – February 18th 2022
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 included:
Literate analysis (RMarkdown),
Data wrangling (tidyr/dplyr),
Data publishing,
Visualization (ggplot2/sf),
Code versioning (git),
Ethical data procedures (CARE principles)
Past Talks:
As well as hosting courses and workshops, the Arctic Data Center also holds workshops at various conferences.
2022 Arctic Science Summit Week and the Arctic Observing Summit
Tromso, Norway
March 26th – April 2nd
In collaboration with ELOKA and NNA Community Office, Noor Johnson (ELOKA), Andy Barrett (NNA), Amber Budden (Arctic Data Center) and Jeanette Clark (Arctic Data Center) presented Open Science: Best Practices, Data Sovereignty and Co-production. All content from this workshop can be found here.
2021 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