Azanzi Jiomekong

Dr. Azanzi Jiomekong is a researcher and lecturer in Computer Science at the University of Yaounde I in Cameroon. He holds a Ph.D in the integration of semantic in software, with the application to epidemiological surveillance. His research interests include empirical studies in software engineering, Model-Driven Engineering, Semantic Web and Knowledge Engineering with the application to the health domain. He has published in software engineering, knowledge engineering and Model Driven Architecture. His research allows him to develop a wealth of experience in Knowledge Management. During his research, he has participated in several national and international research projects such as the EPICAM project (https://github.com/UMMISCO/EPICAM); The “Management and Access of Biomedical knowledge through Ontology network (MABO) project”. Currently, he is working on the curation of Open Research Knowledge Graph. In the latter work, he is comparing papers related to ontology learning.

Enterprise Knowledge Graphs (EKGs) are increasingly becoming important in the Artificial Intelligence (AI) world. Based on ontologies and taxonomies, it is a great technology for data integration and analytic, semantic search and question answering, and many other AI applications. It’s frequently used to organize scientific data, organize data in companies and organizations, avoid data silos, furnish a common view of data to all stakeholders involved in a task, infer non hidden information from existing ones using the reasoning mechanism, etc. Our aim in this tutorial is to familiarize our audience with the complete development and integration of EKG.

Tutorial outline:

• Knowledge graphs
• Ontology construction
• From ontologies to knowledge graphs
• Integration of KG in real-world application
• Knowledge Graph automatic curation