diff --git a/module4/ressources/resources_refs.org b/module4/ressources/resources_refs.org
index d5aeceeb5343148b0aab3940e1c9ad09ea42bbe6..9795f7ebdc71828236d817e77d662194b14948e0 100644
--- a/module4/ressources/resources_refs.org
+++ b/module4/ressources/resources_refs.org
@@ -41,8 +41,10 @@ careful about stability. We (the authors of this MOOC) believe that open
 source (which allows to inspect how computation is done and to
 identify both mistakes and sources of non-reproducibility) is more
 important than the rock solid stability of SAS, which is proprietary
-software. Yet, if you really need to stay with SAS, you should know that SAS
-can be used within Jupyter using the [[https://sassoftware.github.io/saspy/][Python SASPy]] and the
+software.
+
+Yet, if you really need to stay with SAS, you should know that SAS can be used 
+within Jupyter using the [[https://sassoftware.github.io/saspy/][Python SASPy]] and the
 [[https://sassoftware.github.io/sas_kernel/][Python SASKernel]] packages (step by step explanations about this are given
 [[https://app-learninglab.inria.fr/gitlab/85bc36e0a8096c618fbd5993d1cca191/mooc-rr/blob/master/documents/tuto_jupyter_windows/tuto_jupyter_windows.md#53-le-package-python-saspy-permet-dex%C3%A9cuter-du-code-sas-dans-un-notebook-python][here]]). Using such literate programming approach allied with systematic
 version and environment control will always help. Similar solutions exist for many languages ([[https://github.com/jupyter/jupyter/wiki/Jupyter-kernels][list of Jupyter kernels]]).
@@ -72,9 +74,9 @@ Hinsen on Active Papers]] (http://www.activepapers.org/).
 Ensuring software is properly archived, i.e, is safely stored so that
 it can be accessed in a perennial way, can be quite tricky. If you
 have never seen [[https://github.com/alegrand/RR_webinars/blob/master/5_archiving_software_and_data/index.org][Roberto Di Cosmo presenting the Software Heritage
-project]], this is a must see. https://www.softwareheritage.org/
+project]], this is a must see. [[https://www.softwareheritage.org/][https://www.softwareheritage.org/]]
 
-For regular data, we highly recommend using https://www.zenodo.org/
+For regular data, we highly recommend using [[https://www.zenodo.org/][https://www.zenodo.org/]]
 whenever the data is not sensitive.
 * Workflows
 In the video sequences, we mentioned workflow managers (original application domain in parenthesis):