Federated Data Management Portal

This repository contains the code for the Federated Data Management Portal, a web application that allows users to inspect data from multiple sources in a single interface. The application has a Vantage6 integration that is automatically enabled when the application is started. This integration will hereafter periodically repeat the task after a set interval (given the application is kept running).

The portal is built using Dash and Vantage6.
The provided implementation has a large dependency on the collaboration descriptives algorithm, please refer to its respective repository for more information (https://github.com/STRONGAYA/triplestore-collaboration-descriptives).

Prequisites

• When using the triplestore-collaboration-descriptives algorithm (default)

  • Vantage6 server and collaboration with nodes running on version 4.x.x
  • Distributed data in RDF-triple format (produced using the Triplifier tool e.g. through https://github.com/MaastrichtU-CDS/Flyover)
  • Annotated data using the SIO's has-attribute relation (http://semanticscience.org/resource/SIO_000008)
  • GraphDB instances running and accessible on distributed data stations
  • JSON file containing the expected schema (see example_data/schema.json for an example)
  • Credentials to send a task to the Vantage6 server

• In development mode

  • Python 3.10 environment with libraries in requirements.txt installed
  • Access to example data in example_data/ or alternative data in the same format

Running the application

In Docker

The application can be run in a Docker container using the provided docker-compose.yml and Dockerfile. However, the application uses Docker secrets to store Vantage6 server credentials, and for that reason we strongly recommend to use the provided shell script start.sh to run the application as the necessary secrets will then be prompted.
This will appear as follows:

bash start.sh

# These example credentials can be found in `example_data/demo_network_config.json`

# "Please enter the username of the service account:"
# org_1-admin

# "Please enter the password of the service account:"
# password

# "Please enter the server URL:"
# http://host.docker.internal

# "Please enter the server port:"
# 5000

# "Please enter the server API path:"
# /api

# "Please enter the collaboration id:"
# 1

# "Please enter the path to the private key in case encryption is enabled for this collaboration:"
# (leave blank if unencrypted)

# "Please enter the id of the aggregating organisation:"
# 1

# "Please enter the path to the schema JSON file:"
# example_data/schema.json

The application should now be running and available on http://localhost:8050.

You can stop and remove the set Docker secrets using the provided shell script stop_and_clean.sh.
Which can be run as follows:

bash stop_and_clean.sh

In Python

The application can also be run directly in Python. For this it is necessary to have a Python 3.10 environment with the libraries in requirements.txt installed.
This can be achieved as follows:

python3 -m venv fdmp_env

source fdmp_env/bin/activate

pip install -r requirements.txt

You can then start the application using the following command:

python main.py

On startup, the application will prompt for any available Vantage6 server credentials and a schema JSON file.
This will appear as follows:

# "Please provide the path to the Vantage6 configuration JSON file or press enter to use mock data."
# example_data/demo_network_config.json

# "Please provide the path to the global schema JSON file."
# example_data/schema.json

The application should now be running and available on http://localhost:8050.

Example data

The application comes with example data in the example_data/ directory. This data consists of the following:

• demo_network_config.json: Example Vantage6 server credentials that can directly be used with Vantage6's developer network (you can set this up through v6 dev create-demo-network and v6 dev start-demo-network respectively)
• mockresult.json: This file contains mock data retrieved through a task using the described Vantage6 algorithm and Vantage6 developer network. The annotated data shown in this example was created using the example data in https://github.com/MaastrichtU-CDS/Flyover.
• schema.json: This file contains the expected schema of the data that is to be shown in the application. This schema was extracted from the example data in https://github.com/MaastrichtU-CDS/Flyover.