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Evaluating Knowledge Graph Storage and Inference Efficiency in a Document Based Database built on Domain Knowledge Derivation

This repository contains the culmination of research and development conducted in the field of knowledge graph creation, storage, and inference within MongoDB. The work herein explores the possibilities of leveraging NoSQL databases for sophisticated ontology management traditionally handled by graph-based databases.

📖 Contents

  • Ontology Creation: Initial scripts and resources used for manual and automated ontology creation in Protege, including RDF format in Ontologies folder.
  • Data Models: Three distinct models for storing ontology in MongoDB, showcasing RDF to JSON mapping, JSON-LD conversion via Apache Jena, and a segmented document approach.
  • Query Mappings: Demonstrations of mapping SPARQL queries to MongoDB queries across different data models, with performance and complexity evaluation file present under performance_test.
  • Evaluation: Assessment of the structure of models along with hardware resource test to view the contribution of machine's efficiency.

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