dsp-metadata-gui 1.0.2

Python GUI tool to collect metadata for DSP projects.

DSP-METADATA-GUI Metadata Module

The dsp-metadata-gui is a GUI application written in Python for collecting project specific metadata and turn it into RDF.

As part of the dsp-tools, its aim is to enable researchers and project managers who deposit research data on the DSP (DaSCH Service Platform), to add metadata about the project and datasets to the DSP repository. By providing metadata, the project will be searchable on the platform, which is an integral part of the FAIR principles.

The metadata follows the schema defined by the dsp-ontologies.

Install and run

The module provides a command line entry point to run the GUI. The only requirement is Python 3 and PIP installed and ready to use.

The application has only been tested on Python 3.9, but it might work on older versions too.

Note: There have been issues with conda installations. If this is the case, consider using a virtual environment.

Installation via pip

To install the application, run:

pip install dsp-metadata-gui

Or respectively:

pip3 install dsp-metadata-gui

Afterwards, the program can be started by running the command dsp-metadata in your terminal of choice.

Installation from source

Clone this repo and run make make-and-run. If you don't use GNU Make, run the commands specified in the Makefile manually.

This will package the application, install it to your python environment and run the application.

Usage

The Application is divided into two windows:

1. The main window lets you organize a list of projects, for which you can collect metadata. Several actions can be performed with projects, e.g. editing or exporting the project.

2. When editing a project, in the project window, the actual metadata can be added, modified and saved.

To add a project, you will need the project short code, which is assigned to you by the DaSCH Client Service.
A project is always associated with a folder on your local machine. If any files should be included with the metadata import, these files must be within that folder. Once all metadata are added and valid, and the overall DRF graph of the metadata set validates against the ontology, the project can be exported for upload to the DSP.

All data is locally stored in the file ~/DaSCH/config/repos.data. for more detail, see here.

Development

Development Environment

Pipenv

Use pipenv for a seamless development experience.
In order to have both dependencies and dev-dependencies installed from the Pipfile, set up the virtual environment running

pipenv instal --dev

pipenv will manage dependencies as well as a virtual environment. To install packages, use

pipenv install <package-name>

To create requirements.txt, run

pipenv lock -r > requirements.txt

To bring setup.py up to date, run

pipenv run pipenv-setup sync

GNU Make

GNU Make is used to automatize most tasks.
Run make help for info on the available targets.

Note: All make targets - except make run - should be run from within the pipenv shell:
Either by running

pipenv run make <target-name>

or by opening a virtual pipenv shell by running

pipenv shell
make <target-name>
...
exit

Documentation

The documentation is created using mkdocs and mkdocstrings with markdown_include.include. To create the documentation, make sure to install all of these, using pip.

To serve the documentation locally, run make doc. To deploy the documentation to github pages, run make deploy-doc.