Data Translation Pipeline

This repository contains one way to translate CSV-liked data into Knowledge Graph.

1. Manual scripting with owlready2 (OWL format)

   This is used to provide the demo.

   Instantiating ontology class instances using owlready2 based on the CSV data. Then save the knowledge graph using dict, following the owlready2 syntax. This provides a high flexibility and efficiency, without requiring the developer to be proficient with owlready2. owlready2 is used for validation of fields and namespaces.

Installation

run conda env create -f PyPipeline.yml

running

1. update config file ``example-translation/src/config.yml`
2. update global variables in example-translation/src/main.py
3. run conda activate PyPipeline
4. run python example-translation/src/main.py