diff --git a/develop/06_pipelines.qmd b/develop/06_pipelines.qmd
index c20fe938..8367b375 100644
--- a/develop/06_pipelines.qmd
+++ b/develop/06_pipelines.qmd
@@ -55,6 +55,7 @@ To maintain clarity and organization in the data analysis process, adopt best pr
 This lesson emphasized the importance of reproducibility in computational research and provided practical techniques for achieving it. Using annotated notebooks, pipeline frameworks, and community-curated pipelines, such as those developed by the nf-core community, enhances reproducibility and readability. 
 
 ### Sources
+- [RDMkit, Elixir Data Management - Data Analysis](https://rdmkit.elixir-europe.org/data_analysis)
 - [Code documentation by Johns Hopkins Sheridan libraries](https://guides.library.jhu.edu/c.php?g=1096705&p=8066729). This link includes best practices for code documentation, style guides, R markdown, Jupyter Notebook, version control, and code repository. 
 - [Guide to reproducible code in ecology and evolution](https://www.britishecologicalsociety.org/wp-content/uploads/2017/12/guide-to-reproducible-code.pdf)
 - [Best practices for Scientific computing](https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1001745)