Merge pull request #485 from NCEAS/2024-02-arctic

Merging content from 2024-ADC reproducible course to main

materials/DESCRIPTION

@@ -26,8 +26,10 @@ Imports:
     ggforce,
     ggmap,
     ggpmisc,
+    ggspatial,
     googlesheets4,
     gutenbergr,
+    here,
     htmlwidgets,
     httr,
     janitor,

materials/_quarto.yml

@@ -3,7 +3,7 @@ project:
   output-dir: _book
 
 book: 
-  title: "Fundamentals in Data Management for Qualitative and Quantitative Arctic Research"
+  title: "Reproducible Approaches to Arctic Research Using R"
   # date: "January 22-26, 2024"
   reader-mode: false
 
@@ -23,28 +23,31 @@ book:
       - icon: twitter
         href: https://twitter.com/ucsb_nceas
       - icon: github
-        href: https://github.com/NCEAS/nceas-training/tree/2024-01-arctic
+        href: https://github.com/NCEAS/nceas-training/tree/2024-02-arctic
 
   chapters:
     - index.qmd # preface 
     - session_01.qmd # ADC intro
-    - session_02.qmd # r setup 
-    - session_03.qmd # intro to R programming
-    - session_04.qmd # Thinking preferencees + Social aspects of collab
-    - session_05.qmd # DMP
-    - session_06.qmd # Literate analysis
-    - session_07.qmd # ADC-Fundamental practice 1 
-    - session_08.qmd # Data Modeling Essentials
-    - session_09.qmd # Cleaning and Wrangling
-    - session_10.qmd # intro data viz
-    - session_11.qmd # Ethical Data Collection
-    - session_12.qmd # ADC-Fundamentals practice 2
-    - session_13.qmd # text data
-    - session_18.qmd # census data
-    - session_14.qmd # metadata best practices & publishing
-    - session_15.qmd # data portals
-    - session_16.qmd # Survey Workflows
-    - session_17.qmd # Repro and Provenance
+    - session_02.qmd # r & git setup 
+    - session_03.qmd # Literate analysis
+    - session_04.qmd # DMP
+    - session_05.qmd # Documenting and publishing data
+    - session_06.qmd # Intro to Git
+    - session_07.qmd # data modeling essentials
+    - session_08.qmd # Cleaning and Wrangling 
+    - session_09.qmd # collaborating with git
+    - session_10.qmd # publising to the web
+    - session_11.qmd # intro data viz
+    - session_12.qmd # practice session I
+    - session_13.qmd # Thinking Preferences
+    - session_14.qmd # Social Aspects of collab
+    - session_15.qmd # Functions
+    - session_16.qmd # Packages
+    - session_17.qmd # Practice Session II
+    - session_18.qmd # Data Portals
+    - session_19.qmd # Spatial Data
+    - session_20.qmd # Repro and Provenance
+
 
 
 bibliography: book.bib

materials/index.qmd

@@ -1,53 +1,122 @@
-
 <!-- # Preface {.unnumbered} -->
 
-*January 22 - 26, 2024*
-
-
-<!-- ## "Fundamentals in Data Management for Qualitative and Quantitative Arctic Research -->
+*February 26 - March 1, 2024*
 
-:::column-margin
 
+::: column-margin
 ![](images/arctic-data-center.png){width="80%" fig-align="center"}
 :::
 
-
 ::: column-margin
 ![](cover.png){width="80%" fig-align="center"}
 :::
 
 ## About the course {.unnumbered}
 
-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.
+Welcome to the Reproducible Practices for Arctic Research Using R course. In recent years we have adapted this course to be able to offer a fully remote opportunity. This has allowed us to expand our pool of participants taking our courses. Although we have had to switch to a remote training model, we ask participants to be as engaged during the instructional period while understanding conflicts are unavoidable. Your engagement and participation are crucial to make the best of this learning experience.
 
+We will be using the following tools to facilitate this training:
 
+-   Zoom
+-   Slack (desktop app preferred)
+-   RStudio, accessed through a server (details below)
+-   Web browser:
+    -   Firefox (version 80+)
+    -   Chrome (version 80+)
+    -   Safari (version 13+)
+    -   Edge (version 81+)
 
+```{=html}
 <!--- ### Course Learning Objectives:
 
   Effectively manage data using `tidy` data practices and developing quality metadata
 -   Establish best practices and utilize tools like Git & GitHub, and Data Management Plans to optimize your collaboration
 -   Better communicate scientific analyses and results using Markdown, GitHub webpages, and R packages like `ggplot` and `leaflet`
 - Increase your familiarity and confidence with data science tools -->
-
+```
 ## Week's Schedule
 
-:::{.column-body-outset}
+::: column-body-outset
 ![](images/schedule.png)
 :::
 
+## Logistics
+
+### Server
+
+
+You should receive a separate email from NCEAS Account Services prompting you to change your password using the NCEAS account service. Please change your password and then ensure that you can log in at <https://included-crab.nceas.ucsb.edu/>. 
+
+
+### Monitors
+
+
+If you have a second monitor or second device, it would be useful for this training. You’ll need enough screen real estate to handle the primary Zoom window, the participant pane in Zoom, Slack, and a browser with tabs for RStudio and our training curriculum. We recommend either using two monitors or joining the Zoom room from a second device. Having two monitors could look like this:
+
+![](images/arctic-data-center/two-monitors.png)
+
+If you must be on one machine for everything, here’s an example of what it could look like when you are following along with the class and how your screen will shift when you have a more detailed question that requires breakout assistance. 
+
+![](images/arctic-data-center/one-monitor.png)
+
+When we’re in session, **please turn your camera on** and mute your microphone unless you would like to ask a question or contribute to a discussion. 
+
+### Working from Home 
+
+We recognize that working from home may come with challenges. The appearance or sound of other adults, children, and pets in remote meetings such as this is completely normal and understandable. Having your video on and enabling the instructors and your fellow participants to see you brings some humanity to this physically distant workshop, and we believe that this is a crucial element of its success. If you would like to use the Zoom virtual background feature to hide your surroundings, please do so, making sure your background of choice fits within the code of conduct ([here are some Arctic-themed backgrounds](https://www.arcus.org/resources/virtual-backgrounds) if you need inspiration). 
+
+### Non-Verbal Feedback 
+
+We’ll be using the Zoom “Non Verbal Feedback” buttons throughout this course. We will ask you to put a green check by your name when you’re all set and ready to move on with the lesson and a red x by your name if you’re stuck or need assistance. These buttons can be found in the participant's panel of the Zoom room. When you’re asked to answer using these buttons, please ensure that you select one so that the instructor has the feedback that they need to either continue the lesson or pause until everyone gets back on the same page. 
+
+![](images/arctic-data-center/Non-Verbal-Feedback.png){width="60%" fig-align="center"}
+
+
+#### Questions and Getting Help
+
+When you need to ask a question, please do so in one of the following ways:
+
+- Turn your mic on and ask. If you are uncomfortable interrupting the instructor, you may also raise your virtual hand (in the participant panel) and the session facilitator will ask the instructor to pause and call upon you. 
+- Ask your question in the slack channel.
+
+If you have an issue/error and get stuck, you can ask for help in the following ways:
+
+- Turn your mic on and ask for help. See also above regarding the use of a virtual raised hand.
+- Let one of the instructors know in the slack channel.
+- If prompted to do so, put a red X next to your name as your status in the participant window.
+
+When you have detailed questions or need one on one coding assistance, we will have zoom breakout rooms available with helpers. The helper will try to help you in Slack first. If the issue requires more in-depth troubleshooting, the helper will invite you to join their named Breakout Room. 
+
+![](images/arctic-data-center/breakout-room1.png){width="60%" fig-align="center"}
+
+Once you have been assigned a breakout room, but you don't see the pop-up shown in the image above, you can click on the "Join Breakout Room" button on the bottom menu and then click on "Join Breakout Room" in the pop-up message.
+
+![](images/arctic-data-center/breakout-room2.png){width="60%" fig-align="center"}
+
+### The Power of Open
+
+To facilitate a lively and interactive learning environment, we'll be calling on folks to share their code and to answer various questions posed by the instructor. It's completely okay to say "Pass" or "I Don't Know" - this is a supportive learning environment and we will all learn from each other. The instructors will be able to see your code as you go to help you if you get stuck, and the lead instructor may share participants' code to show a successful example or illustrate a teaching moment.
+
+
+
 ## Code of Conduct
 
+
 By participating in this activity you agree to abide by the [NCEAS Code of Conduct](https://www.nceas.ucsb.edu/sites/default/files/2021-11/NCEAS_Code-of-Conduct_Nov2021_0.pdf).
 
+
+![](images/nceas-logo.png)
+
+
 ## About this book
 
 These written materials are the result of a continuous and collaborative effort at NCEAS to help researchers make their work more transparent and reproducible. This work began in the early 2000's, and reflects the expertise and diligence of many, many individuals. The primary authors are listed in the citation below, with additional contributors recognized for their role in developing previous iterations of these or similar materials.
 
 This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/).
 
-**Citation:** Angie Garcia, Matthew B. Jones, Justin Kadi, Maggie Klope, Camila Vargas Poulsen (2024), Fundamentals in Data Management for Qualitative and Quantitative Arctic Research. Arctic Data Center & NCEAS Learning Hub. URL <https://learning.nceas.ucsb.edu/2024-01-arctic>.
-
+**Citation:** Jeanette Clark, Angie Garcia, Matthew B. Jones, Justin Kadi, Maggie Klope, Camila Vargas Poulsen (2024), Reproducible Approaches to Arctic Research Using R. Arctic Data Center & NCEAS Learning Hub. URL <https://learning.nceas.ucsb.edu/2024-02-arctic>.
 
 **Additional contributors:** Ben Bolker, Amber E. Budden, Julien Brun, Samantha Csik, Halina Do-Linh, Natasha Haycock-Chavez, S. Jeanette Clark, Julie Lowndes, Stephanie Hampton, Samanta Katz, Erin McLean, Bryce Mecum, Deanna Pennington, Karthik Ram, Jim Regetz, Tracy Teal, Daphne Virlar-Knight, Leah Wasser.
 
 This is a Quarto book. To learn more about Quarto books visit <https://quarto.org/docs/books>.
+

materials/sections/collaboration-social-data-policies.qmd

@@ -4,9 +4,8 @@ editor:
     wrap: sentence
 ---
 
-## Social Aspects of Collaboration
 
-### Developing a Code of Conduct
+## Developing a Code of Conduct
 
 Whether you are joining a lab group or establishing a new collaboration, articulating a set of shared agreements about how people in the group will treat each other will help create the conditions for successful collaboration.
 If agreements or a code of conduct do not yet exist, invite a conversation among all members to create them.
@@ -48,7 +47,7 @@ Below are other example codes of conduct:
 -   [Mozilla Community Participation Guidelines](https://www.mozilla.org/en-US/about/governance/policies/participation/)
 -   [Ecological Society of America Code of Conduct](https://www.esa.org/esa/code-of-conduct-for-esa-events/)
 
-### Authorship and Credit Policies
+## Authorship and Credit Policies
 
 ![](images/phdcomics_031305s_authorlist.gif)
 
@@ -104,7 +103,7 @@ Some key questions to consider as you are working with your team to develop the
 
 -   How will we resolve conflicts if they arise?
 
-### Data Sharing and Reuse Policies
+## Data Sharing and Reuse Policies
 
 As with authorship agreements, it is valuable to establish a shared agreement around handling of data when embarking on collaborative projects.
 Data collected as part of a funded research activity will typically have been managed as part of the Data Management Plan (DMP) associated with that project.
@@ -144,73 +143,3 @@ This policy is communicated with all incoming lab members, from undergraduate to
 </iframe>
 
 <br>
-
-### Research Data Publishing Ethics
-
-For over 20 years, the [Committee on Publication Ethics (COPE)](https://publicationethics.org/) has provided trusted guidance on ethical practices for scholarly publishing.
-The COPE guidelines have been broadly adopted by academic publishers across disciplines, and represent a common approach to identify, classify, and adjudicate potential breaches of ethics in publication such as authorship conflicts, peer review manipulation, and falsified findings, among many other areas.
-Despite these guidelines, there has been a lack of ethics standards, guidelines, or recommendations for data publications, even while some groups have begun to evaluate and act upon reported issues in data publication ethics.
-
-![Data retractions](images/ethical-dataset-retractions.png)
-
-To address this gap, the [Force 11 Working Group on Research Data Publishing Ethics](https://force11.org/groups/research-data-publishing-ethics/home/) was formed as a collaboration among research data professionals and the Committee on Publication Ethics (COPE) "to develop industry-leading guidance and recommended best practices to support repositories, journal publishers, and institutions in handling the ethical responsibilities associated with publishing research data." The group released the "Joint FORCE11 & COPE Research Data Publishing Ethics Working Group Recommendations" [@puebla_2021], which outlines recommendations for four categories of potential data ethics issues:
-
--   [Authorship and Contribution Conflicts](https://zenodo.org/record/5391293/files/Authorship%20%26%20Contributions_datapubethics.pdf?download=1)
-    -   Authorship omissions
-    -   Authorship ordering changes / conflicts
-    -   Institutional investigation of author finds misconduct
--   [Legal/regulatory restrictions](https://zenodo.org/record/5391293/files/Legal%20%26%20Regulatory%20Restrictions_datapubethics.pdf?download=1)
-    -   Copyright violation
-    -   Insufficient rights for deposit
-    -   Breaches of national privacy laws (GPDR, CCPA)
-    -   Breaches of biosafety and biosecurity protocols
-    -   Breaches of contract law governing data redistribution
--   [Risks of publication or release](https://zenodo.org/record/5391293/files/Risk_datapubethics.pdf?download=1)
-    -   Risks to human subjects
-        -   Lack of consent
-        -   Breaches of himan rights
-        -   Release of personally identifiable information (PII)
-    -   Risks to species, ecosystems, historical sites
-        -   Locations of endangered species or historical sites
-    -   Risks to communities or societies
-        -   Data harvested for profit or surveillance
-        -   Breaches of data sovereignty
--   [Rigor of published data](https://zenodo.org/record/5391293/files/Rigor_datapubethics.pdf?download=1)
-    -   Unintentional errors in collection, calculation, display
-    -   Un-interpretable data due to lack of adequate documentation
-    -   Errors of of study design and inference
-    -   Data manipulation or fabrication
-
-Guidelines cover what actions need to be taken, depending on whether the data are already published or not, as well as who should be involved in decisions, who should be notified of actions, and when the public should be notified.
-The group has also published templates for use by publishers and repositories to announce the extent to which they plan to conform to the data ethics guidelines.
-
-![Force11/COPE](images/force11-cope-logos.png)
-
-### Group Discussion
-
-::: callout-tip
-## Data publishing policies
-
-Consider the following hypothetical scenario:
-
-> The data coordinator at the Arctic Data Center receives an email in 2022 from a prior postdoctoral fellow who was employed as part of an NSF-funded project on microbial diversity in Alaskan tundra ecosystems.
-> The email states that a dataset from 2014 in the Arctic Data Center was published with the project PI as author, but omits two people, the postdoc and an undergraduate student, as co-authors on the dataset.
-> The PI retired in 2019, and the postdoc asks that they be added to the author list of the dataset to correct the historical record and provide credit.
-
-At the Arctic Data Center, we need to develop policies and procedures governing how we react to potential breaches of data publication ethics.
-This exercise, aims to **instigate a group discussion on how the Arctic Data Center should respond to reports of data ethics issues**, and whether we should adopt the Joint FORCE11 & COPE Research Data Publishing Ethics Working Group Policy [Templates](https://zenodo.org/record/6422102/files/Repository%20Policy%20Template%20v1.pdf?download=1) for repositories.
-
--   **Guiding questions:**
-    -   Should the repository adopt the repository [policy templates](https://zenodo.org/record/6422102/files/Repository%20Policy%20Template%20v1.pdf?download=1) from Force11?
-    -   Who should be involved in evaluation of the merits of ethical cases reported to ADC?
-    -    Who should be involved in deciding the actions to take?
-    -   What are the range of responses that the repository should consider for ethical breaches?
-    -   Who should be notified when a determination has been made that a breach has occurred?
-
-
-Consider the  hypothetical scenario described above to for your response.
-:::
-
-## Resources
-
--   [Cheruvelil, K. S., Soranno, P. A., Weathers, K. C., Hanson, P. C., Goring, S. J., Filstrup, C. T., & Read, E. K. (2014). Creating and maintaining high-performing collaborative research teams: The importance of diversity and interpersonal skills. Frontiers in Ecology and the Environment, 12(1), 31-38. DOI: 10.1890/130001](https://esajournals.onlinelibrary.wiley.com/doi/epdf/10.1890/130001) <!--- [Carroll, S. R., Garba, I., Figueroa-Rodríguez, O. L., Holbrook, J., Lovett, R., Materechera, S., … Hudson, M. (2020). The CARE Principles for Indigenous Data Governance. Data Science Journal, 19(1), 43. DOI: http://doi.org/10.5334/dsj-2020-043](http://doi.org/10.5334/dsj-2020-043)-->