README.md

DPROD - Ontology for Data Product Descriptions

This folder contains the Ontology for Data Product Descriptions according to data mesh principles. It is mainly based on the Data Product Descriptor Specification

File Overview

• dprod-ontology.ttl: classes and properties definitions (new terms)
• dprod-shapes.ttl: shacl shapes file for using DPROD to describe data products (data model)

Executing the Ontology Pipeline

Requirements

To execute the ontology pipeline you need:

• Task
• Docker, Podman, or a compatible container engine
• Python 3

Further documentation of the ontology pipeline is available at https://github.com/eccenca/ontology-pipeline-template .

Build Artifacts

The build artifacts are generated in the directory artifacts. In the GitHub Action Workflow the artifacts are attached to a successful build (not integrated to this repository yet).

Building the Documentation and Running RDFUnit Tests

To build documentation for the terms defined in dprod.ttl and run rdfunit-tests you can use the following commands:

task pipeline:validation #run rdfunit tasks

task pipeline:artifacts  #generate documentation

Pipeline Artifacts

• The Ontology Documentation:
  • schema-documentation.html
• The RDFUnit test results:
  • check-rdfunit-auto-results.html
  • check-rdfunit-auto-results.xml
  • check-rdfunit-manual-results.html
  • check-rdfunit-manual-results.xml

TODO for using the pipeline with eccenca CMEM

• 🛠️ Adjust config in cmemc.ini (Find details on documentation.eccenca.com)
• 📡 Make sure to setup a remote for git push
• 🔗 Create a prefixes.ttl
• 📑 Make sure dprod.ttl, dprod.nt, and dprod.nt.graph exist
• 📝 Make sure dprod-sh.ttl, dprod-sh.nt, and dprod-sh.nt.graph exist
• 💾 Commit the newly created files