AIRC Team

The goal of the research is to design an ontology that validates datasets that are previously translated into knowledge graphs. However, this would involve work on description logic and propositional logic and building a knowledge base. The workflow could go along the lines of 1. Translating a dataset into a knowledge graph that represents dataset characteristics and tells us about the quality of the dataset, 2. Feeding the dataset into the knowledge base (which is the main part of the project) to check against DL/PL rules. 3. Summarizing the results and making suggestions/automatic corrections to the dataset. A part of the work would be to investigate a SHACL-style restriction language to define the rules. This project is funded by SFI Centre for Research Training in Machine Learning.