R Markdown Introduced in the R Module

The UNIGIS optional module “Automated Data Processing with R” was now complemented with new learning materials on R Markdown. These module materials teach how to set up the system in RStudio and how to create and synchronize your first R Markdown documents with GitHub.

Many of the methods covered in the R module are intended to make workflows less time consuming and more efficient. With R Markdown, you can execute tasks such as raw data cleaning, data wrangling, statistical and spatial analysis, output rendering, and text writing in a single document. These processes are displayed in a notebook format, which allows for an interactive and independent execution of code chunks, with outputs visible right beneath inputs.

The integration of GitHub in the workflow leverages the full advantages of R Markdown to make the collaboration within teams easier and more transparent.  For instance, separate jobs such as writing a chapter or creating a map can be executed synchronously on different workplaces and can later be merged into interactive (e.g. HTML) or static (e.g. PDF) reports.

The same procedures come in handy when writing a master-thesis. For instance, you might use QGIS or other GIS software to perform geoprocessing operations with results stored in different file formats. Once you have established a link between files and an R Markdown document, you can play around with different settings in the geoprocessing model. Updated outputs are then rendered on-the-fly in the R Markdown document and in the respective file derivatives (HTML, PDF, etc.).

To get started with R Markdown you can turn to the R module materials which are freely provided under the creative commons license.