Skip to content
This repository has been archived by the owner on Aug 10, 2023. It is now read-only.

A system that supports the creation and validation of mappings and the creation of RDF data from relational data.

License

Notifications You must be signed in to change notification settings

MaastrichtU-CDS/DataFAIRifier

Repository files navigation

DataFAIRifier

The DataFAIRifier is a system that supports the creation and validation of mappings of relational data to ontologies. The system is packaged as a set of Docker images. The frontend of the system is implemented as Jupyter Notebook.

This repository describes the bottom-up DataFAIRifier process, and FAIR (Findable, Accessible, Interoperable, Reusable) data station which will be setup when following the instructions.

Getting started

Prerequisites

To run this DataFAIRifier, you need the following software installed on your computer:

  • Docker Engine
  • Docker Compose

Configuring the infrastructure

The full docker-compose collection of containers is given in docker-compose.yml The most minimalistic infrastructure can be executed by writing a docker-compose file (docker-compose.yml) with the following contents:

version: "2"
services:
  graphdb:
    image: jvsoest/graphdb-free:fairstation
    ports: 
      - "7200:7200"

This will create and run a GraphDB instance on your computer. The GraphDB web interface will be available on http://localhost:7200. If you want to add computation docker containers to this configuration, you can e.g. the O-RAW DICOM Radiomics pipeline:

version: "2"
services:
  graphdb:
    image: jvsoest/graphdb-free:fairstation
    ports: 
      - "7200:7200"
  oraw:
    image: jvsoest/oraw
    volumes:
      - ./dicom_import/:/data/
    links:
      - graphdb:graphdb
    environment:
      - RDF4J_URL=http://graphdb:7200
      - EXCLUDE_STRUCTURE_REGEX="(Patient.*|BODY.*|Body.*|NS.*|Couch.*|Isocenter.*)"

Running the infrastructure.

To run this infrastructure, you can go to the folder where you have this docker-compose.yml stored, and type: docker-compose up This will download the necessary images, and run the container.

The following commands can help you as well:

  • docker-compose up -d: Will start or run docker containers in detached mode, giving you back the command line (and run containers as service in background)
  • docker-compose stop: will stop all running containers
  • docker-compose down: Will stop all containders and remove the active image including data
  • docker logs <container_name>: Will show the console logs for the running container, especially helpful in detached mode

How to query and use GraphDB

Regarding the use of GraphDb, please have a look at the quick start guide

Implementation repositories

Frozen hackathon repositories