INF132 Applied ontology and knowledge representation

This course covers semantic technology with a focus on its practical use for modern explainable AI methods, where learning by deduction and induction are combined. The exploration of this field is based on a critical discussion of common practices and recommendations for good practice (FAIR principles, and going beyond the FAIR principles). Knowledge graph technology and methods for designing and aligning semantic artefacts, such as ontologies, are introduced and connected to their logical-mathematical foundations. Dedicated logical formalisms for use in a knowledge-driven AI context, e.g., description logic and logic programming (such as answer set programming), are presented and compared.

The teaching is done in English and is completely digitalized. The course can be completed without being physically present at NMBU.

The participants develop the ability to

• assess requirements and evaluate/improve processes in data managment in accordance with established recommendations for good practice;
• characterize the semantics of data in knowledge-based systems through formal logic;
• specify metadata and communicate information following the formalism based on RDF/OWL.