envidat-converter 0.1.0

Converters for EnviDat metadata

EnviDat Converters

This project features converters made for EnviDat metadata.

• EnviDat to JSON-LD
• EnviDat to DataCite XML
• EnviDat to RIS
• EnviDat to DIF
• EnviDat to ISO 19139
• EnviDat to BIBTEX
• EnviDat to DCAT-AP It also offers a way to download EnviDat metadata.

So how do I use it?

All you need to do is install the package.

Clone the repository in a folder of your choosing. Then install it. Easy!

We recommend using a virtual environment as described here, but in theory you can also just run the last command.

# Create virtual environment:
python -m venv <virtual-environment-name>

# Activate virtual environment (depends on your OS)
# Linux/MacOS
source <virtual-environment-name>\bin\activate
# Windows
<virtual-environment-name>\Scripts\activate.bat

# Install the package.
pip install .

If you have set this up before and come back to the project at a different time, the only step you need to do is activate the virtual environment.

Once this project is on PyPi, I will add the according instructions here.

Command Line Usage

Command Line Usage

Open your favourite terminal. So far, you have two main functionalities:

• Getting the metadata directly from EnviDat
• Converting that metadata to a format of your choosing

Both have the option to either just print the output or save it as a file.

EnviDat metadata

To show or download the metadata, use the following command:

(python) envidat-converter get-data <query>

Query is your search term. It can be a DOI, a dataset name or a dataset ID.

Optional:

To download the dataset, use the --download flag. This will save the file in your current directory.

If you want to specify the path, you can do that with the --outputdir flag.

Examples:

(python) envidat-converter get-data labes

... will print the dataset with the name "labes" in your terminal.

(python) envidat-converter get-data "10.16904/envidat.228" --download --outputdir ".\foldername"

... will save the dataset with the DOI 10.16904/envidat.228 in a new folder called "foldername".

Convert metadata

So far you can convert to the following formats:

• Datacite (XML)
• Json LD in the style of Zenodo (JSON)

To use the converter, use:

(python) envidat_converter.py convert <query> --converter <converter>

Let's break that down:

• query: query is your search term. It can be a DOI, a dataset name or a dataset ID.
• converter: this can currently be "datacite", "jsonld", "bibtex", "dif", "ris", "iso", or "dcatap"

Optional:

To download the dataset, use the --download flag. This will save the file in your current directory.

If you want to specify the path, you can do that with the --outputdir flag.

Examples:

(python) envidat-converter convert labes --converter datacite

... will print the dataset with the name "labes" in the datacite format in your terminal.

(python) envidat-converter convert "10.16904/envidat.228" --converter jsonld --download --outputdir ".\foldername"

... will save the dataset with the DOI 10.16904/envidat.228 in a new folder called "foldername".

API usage

API usage

Make sure you have uvicorn installed. Then it's as simple as running

uvicorn converters.main:app --port 8080

It should load up under http://localhost:8080/. Note that you can always change the port number to whatever fits your needs.

The docs should open up and help you use the API.

• To convert metadata, use the convert-metadata endpoint. You can use IDs, package names, or DOIs as query.
• To simply get the EnviDat metadata, use the get-data endpoint. You can use IDs, package names, or DOIs as query.

Addtional information

This repository was tested against Python Versions 3.8, 3.9, 3.10, 3.11, 3.12, 3.13. Version 3.8 and 3.9 did not work due to dependency issues.

config.ini

If you are not just handling production data but, for example, have a local database that you want to test, you can add the environment to config.ini. There is no need to restart or reinstall after making changes.