Merge branch 'main' into researchers-lmu

.gitignore

@@ -62,3 +62,4 @@ _outline.md
 
 # Other files created by the project
 grateful-refs.bib
+data.csv

README.md

@@ -3,7 +3,7 @@
 This repository is for day 2 of the self-paced Reproducible Manuscripts Quarto Workshop.
 The repository is structured as follows:
 
-1. The folder "01_Example" contains a **minimal reproducible example** with a Quarto manuscript using the Palmer Penguins dataset. All necessary files are there, including the .qmd-file, the data in .csv format, a .bib-file with references, and a citation style csl.-file.
+1. The folder "01_Example" contains a **minimal reproducible example** with a Quarto manuscript using the Palmer Penguins data set. All necessary files are there, including the .qmd-file, the data in .csv format, a .bib-file with references, and a citation style csl.-file.
 2. The folder "02_Practise" contains the data in .csv format, a .bib-file with references, a .cls-file for *apaquarto*, and a citation style .csl-file. These are necessary components to **recreate the minimal reproducible example as a practise**, and would have to be copy-pasted anyway. Other files, like the .RProj-, renv-, and .qmd-files will be created by the participants during the practise in this folder.
 3. The folder "03_Supplement" contains a **checklist** that participants can use to go over their project at the end and see which reproducibility measures they were able to implement and how to take it one step further.
 4. The file "Instructions.qmd" contains the detailed instructions for day 2, i.e. how to execute the example, recreate it, apply the techniques to own data, and use the checklist, step-by-step.

_01_Example/Manuscript.qmd

@@ -40,14 +40,14 @@ format:
 Penguins are fascinating creatures that inhabit various regions of the Southern Hemisphere, including Antarctica and surrounding islands.
 The study of penguins provides valuable insights into ecosystem dynamics, climate change impacts, and evolutionary biology [@smith2020; @jones2018].
 
-This manuscript presents a minimal reproducible example utilizing the penguins dataset to demonstrate scientific workflows in R.
+This manuscript presents a minimal reproducible example utilizing the penguins data set to demonstrate scientific workflows in R.
 
 ```{r}
 #| label: "t-test"
 #| echo: false
 
 # Load penguins data set
-dat <- read.csv("Data.csv")
+dat <- read.csv("data.csv")
 
 # Remove rows with NA
 dat_clean <- dat[complete.cases(dat), ]

_01_Example/README.md

@@ -2,7 +2,7 @@ A minimal reproducible example on penguins for the workshop on Quarto manuscript
 This folder contains all relevant data to reproduce the manuscript: 
 * An R-project ```Example.Rproj``` that was set up using a reproducible environment ```renv```
 * An apaquarto manuscript ```Manuscript.qmd```
-* Primary data that are necessary to reproduce the analyses ```Data.csv```
+* Primary data that are necessary to reproduce the analyses ```data.csv```
 * A bibliography file that contains all references used in the manuscript ```Bibliography.bib```
 * Citation language style files that are necessary to format references in APA7 style ```apa7.csl``` and ```apa7.cls```
 * further files and folders that are created when you produce the document

_03_Supplement/Checklist.qmd

@@ -34,7 +34,7 @@ You will encounter some points that were not part of this workshop, but don't wo
     -   Are raw or preprocessed data being published? Clearly label the data as one or the other and describe any preprocessing steps in a README file.
     -   Are there any legal restrictions regarding the data? If your work involves patents, contracts, patient data, etc., contact your data protection officer for guidelines.
   + Accessibility
-    -   Where will the data be stored? Small datasets can be stored in Github, larger ones on the servers of storage providers, e.g. OSF or Figshare.
+    -   Where will the data be stored? Small data sets can be stored in Github, larger ones on the servers of storage providers, e.g. OSF or Figshare.
     -   Where will the data be archived? On your institution's servers and/or publicly.
     -   Under which license/restrictions is the data being published?
 

_Instructions.qmd

@@ -57,7 +57,7 @@ renv::init()
 2. Create a Quarto document and copy text from your existing manuscript into the document.
 3. Modify the formatting.
 4. Copy a figure into the project folder and insert it into the document.
-5. Create a table, either by hand or by importing your dataset into the project folder and using a package to generate a table.
+5. Create a table, either by hand or by importing your data set into the project folder and using a package to generate a table.
 6. Add your bibliography as a .bib file.
 7. Choose a citation style and download the appropriate .csl file from the web.
 8. Execute your modified scripts and review the generated manuscript files.

_quarto.yml

@@ -3,8 +3,8 @@ project:
 
 website:
   title: "Code Publishing Tutorial"
-  page-footer: 
-    center: "Copyright 2024 Open Science Center at LMU Munich"
+  page-footer:
+    center: "© 2024 Open Science Center at LMU Munich"
     border: false
   search:
     location: sidebar
@@ -15,8 +15,6 @@ website:
   favicon: images/LMU-OSC_favicon.jpg
   margin-header: |
     ![](/images/LMU-OSC_logo.jpg){width="175"}
-    
-    
   navbar:
     right:
       - about.qmd
@@ -32,27 +30,27 @@ website:
             url:  https://github.com/lmu-osc/code-publishing/issues
       - icon: house-heart
         url: https://www.osc.uni-muenchen.de/
-
-
   sidebar:
     contents:
       - intro.qmd
       - setup.qmd
       - choose_license.qmd
       - make_readme.qmd
       - archive.qmd
-
 
 format:
   html:
-    theme: 
+    theme:
       - cosmo
       - custom.scss
     css: styles.css
     toc: true
     fontsize: 13pt
     grid:
       sidebar-width: 300px
+    mermaid:
+      theme: neutral
 
 csl: apa.csl
 bibliography: literature.bib
+lang: en-US