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@@ -93,16 +93,16 @@ Let's assume I have convinced you that reproducibility and transparency are in y
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From day one and throughout the whole research life cycle! Before starting the project, you might have to learn tools like R or Git. If you wait too long while doing the analysis, you might lose a lot of time trying to remember what you did two months ago. When you write the paper, you want up-to-date numbers, tables, and figures. When you co-author a paper, you want to make sure that the analyses presented in a paper with your name on it are sound. When you review a paper, you can't judge the results if you don't know how the authors got there.
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[Alexander (2023)](https://rohanalexander.github.io/telling_stories-published) argues that reproducibility often starts out as a burden—something others require of you, and it can feel tedious or frustrating. But that perception usually changes the moment you return to a project after some time away. Then, it becomes clear that reproducibility isn’t just essential for advancing data science—it’s also a practical tool that makes your own work easier to understand and build upon later. To achieve reproducibility the author suggests a three-step approach:
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[Alexander (2023)](https://rohanalexander.github.io/telling_stories-published) argues that reproducibility often starts out as a burden—something others require of you, and it can feel tedious or frustrating. But that perception usually changes the moment you return to a project after some time away. Then, it becomes clear that reproducibility isn’t just essential for advancing data science—it’s also a practical tool that makes your own work easier to understand and build upon later. To achieve reproducibility, the author suggests a three-step approach:
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1) Ensure the entire workflow is documented. This may involve addressing questions such as:
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- How was the raw dataset obtained, and is access likely to be persistent and available to others?
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- What specific steps are being taken to transform the raw data in the data that were analyzed, and how can this be made available to others?
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- What specific steps are being taken to transform the raw data into the data that was analyzed, and how can this be made available to others?
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- What analysis has been done, which codes/scripts were used, and how can this be shared clearly?
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- How has the final paper or report been built, and to what extent can others follow that process themselves?
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2) Try to accomplish progressively the following requirements:
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2) Try to progressively accomplish the following requirements:
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- Can you run your entire workflow again?
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- Can another person run your entire workflow again?
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### Makes it easy to set your working directory and access files on your computer
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With RStudio, you can navigate to folders on your computer in the "Files" window, view any files you have in that folder, or go to your working directory. You can create projects that help you set your working directory and work with relative paths"to external" files (such as input data and figures) so it can also be used on other machines.
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With RStudio, you can navigate to folders on your computer in the "Files" window, view any files you have in that folder, or go to your working directory. You can create projects that help you set your working directory and work with relative pathsto external files (such as input data and figures), so it can also be used on other machines.
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### Integrates with collaboration and publishing tools
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## Why Quarto and not R Markdown?
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As noted before, Quarto is the next generation of R Markdown and the anatomy of `.rmd` and `.qmd` files are very similar. So why move to Quarto? While compatible with Python (and bash, Julia, C, SQL), R Markdown was designed primarily for R users. **Quarto does not require R.**Quarto runs computations into separate pluggable language "engine," which helps make this cross-language functionality easier to support and reduces infrastructure intensity with built-in applications. In addition, because Quarto is designed to be compatible with existing formats, you can render most existing `.Rmd` and Jupyter Notebooks with Quarto without modification. This low-pain process helps the transition to Quarto.
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As noted before, Quarto is the next generation of R Markdown, and the anatomy of `.rmd` and `.qmd` files is very similar. So why move to Quarto? While compatible with Python (and bash, Julia, C, SQL), R Markdown was designed primarily for R users. **Quarto does not require R.**It supports multiple languages by delegating code execution to external engines, such as Jupyter for Python and Julia, or knitr for R. This design helps support cross-language workflows and reduces infrastructure dependencies. In addition, because Quarto is designed to be compatible with existing formats, you can render most existing `.Rmd` and Jupyter Notebooks in Quarto without modification. This helps ease the transition to Quarto.
@@ -175,7 +175,7 @@ Nitsch, F. J., Sellitto, M., \& Kalenscher, T. (2021). Trier social stress test
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We will also be using a simplified version of the project directory containing data files and scripts published by the authors on Open Science Framework: <https://doi.org/10.17605/OSF.IO/6MVQ7>.
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The adapted paper template and project directory are used exclusively for instruction purposes with permission from the authors.
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The adapted paper template and project directory are used exclusively for instructional purposes with permission from the authors.
Copy file name to clipboardExpand all lines: episodes/02-quarto/01-basic-rstudio.md
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we will do a brief tour of the IDE, review R projects, and the best practices for
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organizing your work, and how to install or check packages you need to follow along.
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Now, let's open RStudio. After passing authentication, choose `RStudio`. If you want to follow along using your local RStudio, make sure you use IDE version RStudio v2023.06 or later and that it is running [Quarto version 1.4 or above](https://quarto.org/docs/download/prerelease.html). If you need to check that, for RStudio, choose `Help` and `About RStudio`. For the Quarto version checking, type in `packageVersion("quarto")` on the console.
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Now, let's open RStudio. After passing authentication, choose `RStudio`. If you want to follow along using your local RStudio, make sure you use IDE version RStudio v2023.06 or later and that it is running [Quarto version 1.4 or above](https://quarto.org/docs/download/release.html). If you need to check that, for RStudio, choose `Help` and `About RStudio`. For the Quarto version checking, type in `packageVersion("quarto")` on the console.
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we will do a brief tour of the IDE, review R projects, and the best practices for
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organizing your work, and how to install or check packages you need to follow along.
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Now, let's open RStudio. After passing authentication, choose `RStudio`. If you want to follow along using your local RStudio, make sure you use IDE version RStudio v2023.06 or later and that it is running [Quarto version 1.4 or above](https://quarto.org/docs/download/prerelease.html). If you need to check that, for RStudio, choose `Help` and `About RStudio`. For the Quarto version checking, type in `packageVersion("quarto")` on the console.
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Now, let's open RStudio. After passing authentication, choose `RStudio`. If you want to follow along using your local RStudio, make sure you use IDE version RStudio v2023.06 or later and that it is running [Quarto version 1.4 or above](https://quarto.org/docs/download/release.html). If you need to check that, for RStudio, choose `Help` and `About RStudio`. For the Quarto version checking, type in `packageVersion("quarto")` on the console.
Copy file name to clipboardExpand all lines: episodes/03-collaboration/04-publishing-your-project.md
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This list is expected to grow rapidly with new contributions submitted to the [Quarto Journal Templates Repository](https://github.com/quarto-journals). You may also create your own templates following [these guidelines](https://quarto.org/docs/journals/templates.html).
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Journal templates require features of Quarto version 1.2, so we must ensure we have the right version. You can check your Quarto version in the Terminal with the command: `quarto --version`. We should be good with that for this workshop, but if you are using a lab computer later on, you may need to update Quarto. See: [pre-release versions of Quarto](https://quarto.org/docs/download/prerelease.html)
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Journal templates require features of Quarto version 1.2 or later, so we must ensure we have the right version. You can check your Quarto version in the Terminal with the command: `quarto --version`. We should be good with that for this workshop, but if you are using a lab computer later on, you may need to update Quarto. See: [release versions of Quarto](https://quarto.org/docs/download/release.html)
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Quarto uses a template command that can be called in the terminal to create an article in any of these formats. Suppose you want to use the Elsevier template. In Rstudio, in the terminal (if not showing, select `Tools > Terminal > New`), type `quarto use template quarto-journals/elsevier`. Then, follow the steps below:
Copy file name to clipboardExpand all lines: episodes/10-biblio-crossref.md
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## Why Cite?
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Correctly citing and attributing publications is key to academic writing. Older versions of RStudio require [Pandoc's citation syntax](https://pandoc.org/MANUAL.html#citation-syntax) to render bibliographies correctly. We won't be covering this approach extensively in this workshop since the new visual editor has made this process much more simple. You can refer to our [previous workshop on R Markdown](https://ucsbcarpentry.github.io/R-markdown/06-citations-bib/index.html) pre-visual editor for more information.
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Correctly citing and attributing publications is key to academic writing. Older versions of RStudio require [Pandoc's citation syntax](https://pandoc.org/MANUAL.html#citation-syntax) to render bibliographies correctly. We won't be covering this approach extensively in this workshop since the new visual editor has made this process much simpler. You can refer to our [previous workshop on R Markdown](https://ucsbcarpentry.github.io/R-markdown/06-citations-bib/index.html) pre-visual editor for more information.
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The new visual editor has made citations and cross-referencing much easier, by offering different options for referencing various types of sources. Before getting into these different features, let's first learn how you can call the citation window dialog on Rstudio and how to navigate these different options.
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A file with the BIB file extension is a BibTeX Bibliographical Database file. It's a specially formatted text file that lists references pertaining to a particular source of information. They're normally seen only with the .`bib` file extension but might instead use `.bibitex`. BibTeX files might hold references for things like research papers, articles, books, etc. The file often includes an author's name, year, title, page number, and other related content. Each item can be edited, in case there is any metadata incorrect or missing.
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Most citation and reference management tools such as Refworks, Endnote, Mendeley and Zotero, as well as some search engines (e.g., Google Scholar), most scientific databases, and our UCSB library catalog allow us to export citations aa[.bib or BibteX files](https://en.wikipedia.org/wiki/BibTeX). These files are used to describe and process lists of references, mostly in conjunction with LaTeX documents. Each .bib file has a citation key or ID preceded by an `@`, which uniquely identifies each item. Citation keys can be customized, as we will learn in a bit, but be advised that your manuscript will render citations correctly only if you have the cited item corresponding to its exact key.
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Most citation and reference management tools such as Refworks, Endnote, Mendeley and Zotero, as well as some search engines (e.g., Google Scholar), most scientific databases, and our UCSB library catalog allow us to export citations as[.bib or BibteX files](https://en.wikipedia.org/wiki/BibTeX). These files are used to describe and process lists of references, mostly in conjunction with LaTeX documents. Each .bib file has a citation key or ID preceded by an `@`, which uniquely identifies each item. Citation keys can be customized, as we will learn in a bit, but be advised that your manuscript will render citations correctly only if you have the cited item corresponding to its exact key.
Copy file name to clipboardExpand all lines: episodes/14-publishing-your-project.md
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This list is expected to grow rapidly with new contributions submitted to the [Quarto Journal Templates Repository](https://github.com/quarto-journals). You may also create your own templates following [these guidelines](https://quarto.org/docs/journals/templates.html).
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Journal templates require features of Quarto version 1.2, so we must ensure we have the right version. You can check your Quarto version in the Terminal with the command: `quarto --version`. We should be good with that for this workshop, but if you are using a lab computer later on, you may need to update Quarto. See: [pre-release versions of Quarto](https://quarto.org/docs/download/prerelease.html)
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Journal templates require features of Quarto version 1.2, so we must ensure we have the right version. You can check your Quarto version in the Terminal with the command: `quarto --version`. We should be good with that for this workshop, but if you are using a lab computer later on, you may need to update Quarto. See: [release versions of Quarto](https://quarto.org/docs/download/release.html)
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Quarto uses a template command that can be called in the terminal to create an article in any of these formats. Suppose you want to use the Elsevier template. In Rstudio, in the terminal (if not showing, select `Tools > Terminal > New`), type `quarto use template quarto-journals/elsevier`. Then, follow the steps below:
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