Update code_and_data_management.md

Author: marcobarilari

doc/code_and_data_management.md

@@ -3,6 +3,7 @@
 ## Version control
 
 In the lab we (try) to stick to version control for code with git/github and data with datalad and gin. Somewhere else is already mentioned but repetita iuvant so 
+
 1. Install git on your computer 
 2. Create a GITHUB account and ask to be added to the lab organization [https://github.com/cpp-lln-lab]
 3. Make sure you have your SSH key for GITHUB following this tutorial 
@@ -15,6 +16,7 @@ In the lab we (try) to stick to version control for code with git/github and dat
 
 ## Data management
 for MRI data the lab is moving towards using the BIDS data structure
+
 * bids starter kit
 * bids specification
 
@@ -29,18 +31,21 @@ Data:
 
 [GIN organization](https://gin.g-node.org/cpp-lln-lab) for source, raw, and preprocessed data for conversion control and sharing
 
-Dataset summary that puts together all the bidsified raw and derivatives repos of the lab and summarize metadata in a table from the GIN repo above: 
+Dataset summary that puts together all the bidsified raw and derivatives repos of the lab and summarizes metadata in a table from the GIN repo above: 
+
 - [website](https://cpp-lln-lab.github.io/Datasets/)
 - [Githuba repo CPP_Datasets](https://github.com/cpp-lln-lab/CPP_Datasets)
 
 Datalad superdataset to grab all the repo together (these are submodules in the [Githuba repo CPP_Datasets](https://github.com/cpp-lln-lab/CPP_Datasets):
- - https://github.com/cpp-lln-lab/cpp-lln-lab_derivatives 
- - https://github.com/cpp-lln-lab/cpp-lln-lab_source
+
+- https://github.com/cpp-lln-lab/cpp-lln-lab_derivatives 
+- https://github.com/cpp-lln-lab/cpp-lln-lab_source
 
 Guidelines to maintain the CPP dataset https://github.com/cpp-lln-lab/dataset_maintenance
 
 
 Tools:
+
 - https://github.com/cpp-lln-lab/template_datalad_bids-raw
 - https://github.com/cpp-lln-lab/CPP_dcm2Bids
 - https://github.com/cpp-lln-lab/letswave_bids_import
@@ -67,6 +72,7 @@ cooked step by step for MacOS users:
 
 
 Short guidelines:
+
 - not suitable for an “online” usage (eg running analyses within the folder), it is a cloud service so reading and writing is as fast as your internet connection
 - Long term storage
 - Please, be organized. Imagine that another person in the future will open that folder and make sense of the content in less than 2 minutes