FAIR data in marine robotics

For more information check the GitHub pages of this project!

This is a work in progress. At the time of writing, this repository contains several notebooks and python files. Here a short summary of the most important ones:

1. database.ipynb : It shows how to create a light database in JSON format. Such database are used to store the standard names of global variables and the standard attributes of robotic and scientific variables. The products of such notebook are stored in the folder database and are used to fill the NetCDF files with standardized metadata.
2. _netcdfconventions.ipynb: It aims to show how to add and possibly extract descriptive and domain specific metadata from NetCDF files using python. It takes raw data in input and creates FAIR NetCDF and ISO-199115-2 files in output. The notebook interacts with the previously created database and with a configuration file that contains the values given to the global metadata. More information are contained directly in the notebook.
3. _nc_genscript.py: Simple script to generate netcdf files automatically based on the notebook example. It can be used to generate all nc files in once.
4. fairdata folder: It contains our own python modules. Right now the only module present is metadataDB which is the interface towards the JSON databases.
5. interface folder: It contains an interface to fill the global metadata and to generate the netcdf files. More information on the website.

Installation

To download this repository, it is recommended to use git with the command git clone.

For installing all needed packages, the easiest way is to install anaconda to manage the python environments. In the environment folder of this repository, you can find the environment.yml file with all packages used in this repository. Note that the first line of the yml file sets the new environment's name. After the installation, open the anaconda command line, navigate to the environment folder and digit:

$ conda env create -f environment.yml

Then you can switch to the newly created environment using:

$ conda activate <env_name>

Finally, to open the IDE for jupyter run

$ cd .. to go back to the root repo folder

$ jupyter lab