91265 - Knowledge Engineering

Course Unit Page

Academic Year 2020/2021

Learning outcomes

At the end of the course, the student knows some (semi-)automated methods for joint interpretation of data and content as sources of knowledge. The student masters the basics of knowledge extraction, engineering, and linking, making data suitable to machine querying and automated reasoning, typically on decentralized platforms such as the Web.

Course contents

Knowledge graphs and ontologies

Ontology design patterns

Extreme Design

OWL, RDF, SPARQL

Knowledge Acquisition

Applied reasoning

Readings/Bibliography

Notes and slides provided by the teacher.

Hitzler, P., Gangemi, A., & Janowicz, K. (2016). Ontology Engineering with Ontology Design Patterns. Amsterdam: IOS Press.

P.A. Bonatti, S. Decker, A. Polleres, V. Presutti, Knowledge graphs: new directions for knowledge representation on the Semantic Web (dagstuhl seminar 18371). Dagstuhl Rep. 8(9), 29–111 (2019)

Teaching methods

Lectures and self-assessment quizzes.

Assessment methods

Written exam or project.

Teaching tools

Slides and tools for self-assessment.

Office hours

See the website of Valentina Presutti

See the website of Andrea Giovanni Nuzzolese