Adding index page fpr all of ADC 2024 trainings

content/events/2024-01-arctic/index.md

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+---
+title: "Fundamentals in Data Management for Qualitative and Quantitative Arctic Research"
+output:
+  html_document:
+    df_print: paged
+type: page
+tags: ["Arctic Data Center"]
+date: 2024-01-22
+---
+
+
+
+__Dates__: January 22 - 26, 2024<br>
+__Location__: NCEAS <br>
+__Venue__: Santa Barbara, CA
+
+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](https://www.gida-global.org/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.
+
+
+
+## Materials
+
+[Link to course materials](https://learning.nceas.ucsb.edu/2024-01-arctic/)
+
+
+## Instructors
+
+|Name         | Email              |
+|-------------|--------------------|
+|Matt Jones | [email protected] |
+|Camila Vargas Poulsen |[email protected]|
+|Angie Garcia | [email protected] |
+|Justin Kadi | [email protected]|
+|Maggie Klope | [email protected]|
+|Natasha Haycock-Chavez | [email protected]|
+
+
+
+## Acknowledgements
+
+Work was supported by:
+
+- [NSF award #1546024](http://www.nsf.gov/awardsearch/showAward?AWD_ID=1546024) to M. B. Jones, S. Baker-Yeboah, A. Budden, J. Dozier, and M. Schildhauer
+
+Additional support was provided for working group collaboration by the National Center for Ecological Analysis and Synthesis, a Center funded by the University of California, Santa Barbara, and the State of California.

content/events/2024-02-arctic/index.md

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+---
+title: "Reproducible Practices for Arctic Research Using R"
+output:
+  html_document:
+    df_print: paged
+type: page
+tags: ["Arctic Data Center"]
+date: 2024-02-26
+---
+
+
+
+__Dates__: February 26 - March 1, 2024<br>
+__Location__: Online<br>
+<!--__Venue__: [NCEAS](https://www.nceas.ucsb.edu), 735 State St., Suite 300, UC Santa Barbara-->
+
+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 life cycle, from ethical data collection following the CARE principles to engage with local stakeholders, to data publishing..
+
+## Overview:
+
+Workshop topics will include:
+
+* Literate analysis (Quarto),
+* Data wrangling (tidyr/dplyr),
+* Data publishing,
+* Visualization (ggplot2/sf),
+* Code versioning (git),
+* Ethical data procedures (CARE principles)
+
+
+For more detailed information on how to prepare for the workshop, see preparing for the workshop (below).
+
+## Materials
+
+[Link to course materials](https://learning.nceas.ucsb.edu/2024-02-arctic/)
+
+
+## Organizers
+
+|Name         | Email              |
+|-------------|--------------------|
+|Jeanette Clark| [email protected] |
+|Camila Vargas-Poulsen| [email protected] |
+|Angie Garcia | [email protected] |
+|Justin Kadi | [email protected]|
+|Maggie Klope | [email protected]|
+
+## Acknowledgements
+Work on this package was supported by:
+
+- [NSF award #1546024](http://www.nsf.gov/awardsearch/showAward?AWD_ID=1546024) to M. B. Jones, S. Baker-Yeboah, A. Budden, J. Dozier, and M. Schildhauer
+
+Additional support was provided for working group collaboration by the National Center for Ecological Analysis and Synthesis, a Center funded by the University of California, Santa Barbara, and the State of California.

content/events/2024-03-arctic/index.md

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+---
+title: "Scalable and Computationally Reproducible Approaches to Arctic Research"
+output:
+  html_document:
+    df_print: paged
+type: page
+tags: ["Arctic Data Center"]
+date: 2024-03-25
+---
+
+
+
+__Dates__: March 25-29, 2024<br>
+__Location__: NCEAS <br>
+__Venue__: 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.
+
+
+
+## Materials
+
+[Link to course materials](https://learning.nceas.ucsb.edu/2024-03-arctic/)
+
+
+## Instructors
+
+|Name         | Email              |
+|-------------|--------------------|
+|Matt Jones | [email protected]|
+|Jeanette Clark | [email protected] |
+|Angie Garcia | [email protected] |
+|Justin Kadi | [email protected]|
+|Maggie Klope | [email protected]|
+|Angel Chen | [email protected]|
+
+## Acknowledgements
+
+Work was supported by:
+
+- [NSF award #2042102](http://www.nsf.gov/awardsearch/showAward?AWD_ID=2042102) to M. B. Jones, A. Budden, J. Dozier, and M. Schildhauer
+
+Additional support was provided for working group collaboration by the National Center for Ecological Analysis and Synthesis, a Center funded by the University of California, Santa Barbara, and the State of California.