Post date: Jan 29, 2018 12:17:44 PM
Overview of Ontology and Knowledge Graph EngineeringÂ
Ontologies enable formal representation of knowledge in the real world in formats that can be understandable by both humans and machines. A knowledge graph (KG) is a graphical network of data entities (people, places, things, concepts) and the relationships that exist between them. Today, ontologies and knowledge graphs are viable models for representing knowledge that exists in the real world. Ontologies and KG have become the bedrock of many intelligent systems. However, there are several domains where viable knowledge infrastructure like ontologies and KG are lacking, which limits our capacity to deploy AI. The main goal of OntoKGE research is to identify these domains and create viable knowledge infrastructures like ontologies and KG that can stimulate the application and deployment of AI in such domains in the immediate future.
Research Approach: ontology engineering, knowledge graph engineering (Development and Evaluation, Trial use cases)
Participation
Prospective Researchers: Bachelor honours, master's, and doctoral students, postdoctoral fellows, research collaborators.
Skill Requirements: Expertise in programming (Python/Java/C#/JavaScript, Neo4j), software development, open-soure development tools (ontology tools, knowledge graph tools), good communication and writing skills.
For more information on OntoKGE research contact me via my email: wande.daramolaj@up.ac.za