move viz to earlier

content/workflow-management.md

@@ -194,7 +194,23 @@ Steps:
 - 8: Probably only the two lines containing "shell".
 ```
 ````
+## Visualizing the workflow
 
+We can visualize the directed acyclic graph (DAG) of our current Snakefile
+using the `--dag` option, which will output the DAG in `dot` language.
+
+**Note**: This requires the [Graphviz software](https://www.graphviz.org/),
+which can be installed by `conda install graphviz`. 
+
+```console
+$ snakemake -j 1 --dag | dot -Tpng > dag.png
+```
+Rules that have yet to be completed are indicated with solid outlines, while already completed rules are indicated with dashed outlines.
+
+```{figure} img/snakemake_dag.png
+:alt: Snakemake DAG
+:width: 100%
+```
 
 ## Why [Snakemake](https://snakemake.readthedocs.io/)?
 
@@ -209,6 +225,8 @@ Steps:
 - If several workflow steps are independent of each other, and you have multiple cores available, Snakemake can run them in parallel.
 - Nice functionality for archiving the workflow, see: [the official documentation](https://snakemake.readthedocs.io/en/stable/snakefiles/deployment.html#sustainable-and-reproducible-archiving)
 
+Tools like Snakemake help us with **reproducibility** by supporting us with **automation**, **scalability** and **portability** of our workflows.
+
 
 ## Similar tools
 
@@ -220,20 +238,4 @@ Steps:
 - [Book on building reproducible analytical pipelines with R](https://raps-with-r.dev/)
 
 
-## Visualizing the workflow
-
-We can visualize the directed acyclic graph (DAG) of our current Snakefile
-using the `--dag` option, which will output the DAG in `dot` language.
-
-**Note**: This requires the [Graphviz software](https://www.graphviz.org/),
-which can be installed by `conda install graphviz`. 
-
-```console
-$ snakemake -j 1 --dag | dot -Tpng > dag.png
-```
-Rules that have yet to be completed are indicated with solid outlines, while already completed rules are indicated with dashed outlines.
 
-```{figure} img/snakemake_dag.png
-:alt: Snakemake DAG
-:width: 100%
-```