adding parts from UNFCCC repo and automatically created DataLad README, DataLad sibling description, merge instructions.

README.md

@@ -1,6 +1,6 @@
 # Global CO2 from Cement Production Dataset
 
-This repository downloads the Andrew dataset on global CO2 emissions from cement production from Zenodo.
+This repository downloads the Andrew dataset on global CO2 emissions from cement production from [Zenodo](https://zenodo.org/records/10008931).
 
 ## Description
 
@@ -9,7 +9,17 @@ The downloaded dataset can then be converted into CSV (.csv file extension) or N
 The data management tool [DataLad](http://docs.datalad.org/en/stable/) is used to version control the data sets.
 Commands to run the scripts are executed via the pydoit package.
 
-### Installation
+## DataLad datasets and how to use them  
+  
+This repository is a [DataLad](https://www.datalad.org/) dataset. It provides  
+fine-grained data access down to the level of individual files, and allows for  
+tracking future updates. In order to use this repository for data retrieval,  
+[DataLad](https://www.datalad.org/) is required. It is a free and open source  
+command line tool, available for all major operating systems, and builds up on  
+Git and [git-annex](https://git-annex.branchable.com/) to allow sharing,  
+synchronizing, and version controlling collections of large files.  
+
+## Installation
 
 - Install datalad according to the [DataLad handbook](https://handbook.datalad.org/en/latest/intro/installation.html). It is recommended to install globally. 
 - DataLad is based on Git. [Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) needs to be installed to run DataLad. 
@@ -18,39 +28,63 @@ Commands to run the scripts are executed via the pydoit package.
 
 ## Getting Started
 
-### 1. Clone the repository
+### Clone the repository
 
-Download the repository using the following command.
+A DataLad dataset can be `cloned` by running  
 ```
 datalad clone
 ```
 Do not use **git clone** to download the repository! This way DataLad will not have the necessary
-information to run the program.
+information to run the program. Once a dataset is cloned, it is a light-weight directory on your local machine.  
+At this point, it contains only small metadata and information on the identity  
+of the files in the dataset, but not actual *content* of the (sometimes large)  
+data files.  
+
 
-### 2. Easy Access
-Users who simply want to download the dataset have the option to access both the
-original and extracted files with the following command.
+### Easy Access
+Users who simply want to retrieve the dataset have the option to access both the
+original and extracted files with
 ```
 dataland get <filename>
 ```
-For example, the CSV file for the 2023/09/13 release can be downloaded with:
+This command will trigger a download of the files, directories, or subdatasets  
+you have specified.
+
+For example, the CSV file for the 2023/09/13 release can be downloaded with
 ```
 datalad get extracted_data/v230913/Robbie_Andrew_Cement_Production_CO2_230913.csv 
 ```
+### Stay up-to-date  
+  
+DataLad datasets can be updated. The command `datalad update` will *fetch*  
+updates and store them on a different branch (by default  
+`remotes/origin/master`). Running  
+  
+```  
+datalad update --merge  
+```  
+  
+will *pull* available updates and integrate them in one go.  
+  
+### Find out what has been done  
+  
+DataLad datasets contain their history in the ``git log``.  By running ``git  
+log`` (or a tool that displays Git history) in the dataset or on specific  
+files, you can find out what has been done to the dataset or to individual  
+files by whom, and when.
 
+## Executing the program
 
-### 3. Executing the program
-
-#### 3.1 Set up the virtual environment with doit
+#### Set up the virtual environment with doit
 ```
 doit setup_env
 ```
-#### <a name="download"></a> 3.2 Download the version from the command line.
+#### <a name="download"></a>Download the version from the command line.
 This will download all files from Zenodo as they are.
 ```
 doit download_version --version <YYMMDD>
 ```
-#### <a name="convert"></a> 3.3 Convert the data sets into CSV and NetCDF files.
+#### <a name="convert"></a>Convert the data sets into CSV and NetCDF files.
 ```
 doit read_version --version <YYMMDD>
 ```
@@ -58,7 +92,7 @@ doit read_version --version <YYMMDD>
 ## <a name="newversion"></a> How to add a new version
 
 
-1. To add a new version go to **versions.py** in the **src** directory and create a new value in the
+To add a new version go to **versions.py** in the **src** directory and create a new value in the
 dictionary. Fill all the required information similar to the previous entries.
 For example, the value _v230913_ in the _versions_ dictionary describes the 13-Sep-2023 release.
 ````python
@@ -84,8 +118,7 @@ versions = {
     },
 }
 ````
-
-2. Then run the two commands as described in [3.2] and [3.3].
+Then run the two commands `read_version` and `download_version` as described in **Executing the program**. 
 
 ## Help
 Show all doit commands
@@ -103,7 +136,7 @@ Get help on a specific command
 doit help <command>
 ```
 
-## For developers
+## Contributing
 ### Repository structure
 - **.datalad/** contains config file for datalad
 - **downloaded_data/** contains original data from Zenodo.
@@ -124,15 +157,15 @@ doit help <command>
 - **setup.cfg** requirements
 - **setup.py** installs python packages
 
-### Make sure to connect with your siblings
+### Make sure to correctly set up the DataLad siblings
 Git repositories can configure clones of a dataset as _remotes_ in order to fetch, pull, or push from and to them. A `datalad sibling` is the equivalent of a git clone that is configured as a remote. 
 
-**Query information** about about all known siblings with: 
+**Query information** about about all known siblings with
 ```
 datalad siblings
 ```
 
-**Add a sibling** to allow pushing to github:
+**Add a sibling** to allow pushing to github
 ```
 datalad siblings add --dataset . --name <name> --url git@github.com:JGuetschow/Global_CO2_from_cement_production.git
 ```
@@ -144,79 +177,24 @@ datalad push --to <name>
 
 ```
 
-### instructions for merge requests
-# About this dataset
-
-## General information
-
-This is a DataLad dataset (id: 24f90b12-e4a9-4e2c-995d-a54ed4cd49c7).
-
-## DataLad datasets and how to use them
-
-This repository is a [DataLad](https://www.datalad.org/) dataset. It provides
-fine-grained data access down to the level of individual files, and allows for
-tracking future updates. In order to use this repository for data retrieval,
-[DataLad](https://www.datalad.org/) is required. It is a free and open source
-command line tool, available for all major operating systems, and builds up on
-Git and [git-annex](https://git-annex.branchable.com/) to allow sharing,
-synchronizing, and version controlling collections of large files.
-
-More information on how to install DataLad and [how to install](http://handbook.datalad.org/en/latest/intro/installation.html)
-it can be found in the [DataLad Handbook](https://handbook.datalad.org/en/latest/index.html).
-
-### Get the dataset
-
-A DataLad dataset can be `cloned` by running
-
-```
-datalad clone <url>
-```
-
-Once a dataset is cloned, it is a light-weight directory on your local machine.
-At this point, it contains only small metadata and information on the identity
-of the files in the dataset, but not actual *content* of the (sometimes large)
-data files.
-
-### Retrieve dataset content
-
-After cloning a dataset, you can retrieve file contents by running
-
-```
-datalad get <path/to/directory/or/file>
-```
-
-This command will trigger a download of the files, directories, or subdatasets
-you have specified.
-
-DataLad datasets can contain other datasets, so called *subdatasets*.  If you
-clone the top-level dataset, subdatasets do not yet contain metadata and
-information on the identity of files, but appear to be empty directories. In
-order to retrieve file availability metadata in subdatasets, run
-
-```
-datalad get -n <path/to/subdataset>
-```
-
-Afterwards, you can browse the retrieved metadata to find out about subdataset
-contents, and retrieve individual files with `datalad get`.  If you use
-`datalad get <path/to/subdataset>`, all contents of the subdataset will be
-downloaded at once.
+### Issues
+There always issues open regarding coding, some of them easy to resolve, some harder.
 
-### Stay up-to-date
+### Your ideas
+Contributing is ouf course not limited to the categories above. I you have ideas for improvements just open an issue or a discussion page to discuss you idea with the community.
 
-DataLad datasets can be updated. The command `datalad update` will *fetch*
-updates and store them on a different branch (by default
-`remotes/origin/master`). Running
+### Technical HowTo for contributors
+As we have a datalad repository using github and gin the process of contributing code and data is a bit different from 
+pure git repositories. As the data is only stored on gin, the gin repository is the source to start 
+from. As gin currently has a problem with forks (the annexed data is not 
+forked) we have to use branches for development and, thus, to contribute you
+first need to contact the maintainers to get write access to the repository.
+You have to clone the repository using ssh to be able to push to it. 
+For that you first need to store your public ssh key on the gin server 
+(settings -> SSH Keys). 
 
-```
-datalad update --merge
-```
-
-will *pull* available updates and integrate them in one go.
-
-### Find out what has been done
-
-DataLad datasets contain their history in the ``git log``.  By running ``git
-log`` (or a tool that displays Git history) in the dataset or on specific
-files, you can find out what has been done to the dataset or to individual
-files by whom, and when.
+### Instructions for merge requests
+Once you have everything set up you can create a new branch branch and work there. 
+When you're done create a pull request to integrate your work into the main 
+branch. This should be done first github to allow for discussions and review. Afterwards the changes 
+can be implemented on gin.