OVERVIEW

The Semantic Web and Linked Data technologies are the fulcrum of this teaching: starting from XML and RDF up to the conceptual representations in OWL. These technologies, and the associated methodologies, will be used in the design and implementation of "smart" user interfaces, which exploit ontologies and open and linked data.
Finally, software tools and use cases will be presented to compare Semantic Web and Machine Learning in the management of datasets and complex systems.

AIMS AND CONTENT

LEARNING OUTCOMES

In this course, you will learn the fundamentals of Semantic Web technologies. You will learn how to collect information form linked data and metadata to represent knowledge an build knowledge bases, and how to access and benefit from semantic web technologies applied to smart applications in a H2020 perspective.

AIMS AND LEARNING OUTCOMES

At the end of the course the student will acquire skills and competencies related to design and implementation of “smart” apps and services based on semantic technologies.

TEACHING METHODS

Lectures (online and/or face-to-face) and thematic seminars will be provided during the fall semester. Online activities will be delivered through UniGe digital platforms to permit a continuous assessment of students' competencies.

SYLLABUS/CONTENT

1. Introduction to Semantic Web as Web of Data: XML-based technologies, pros&cons, software tools for open and linked data interchange.
2. Semantic Languages for description, annotation, query and knowledge representation: RDF, RDF-S, SPARQL, OWL.
3. Ontologies and metadata for the Semantic Web: annotation of digital resources through standard metadata (Dublin Core, Linked Data), ontology design for semantic search engines and reasoners.
4. Design and implementation of smart applications and semantic web services.
5. Deep Learning and Semantic Web with large dataset.
6. Linked Data Programming and Semantic Knowledge Mining

RECOMMENDED READING/BIBLIOGRAPHY

• Liyang Yu, A Developer's Guide to the Semantic Web, 2nd Edition, Springer, 2014
• M. Horridge, Protégé OWL Tutorial, v. 1.3, 2011, freely available at http://owl.cs.manchester.ac.uk/publications/talks-and-tutorials/protg-owl-tutorial/ 

TEACHERS AND EXAM BOARD

Exam Board

GIANNI VIARDO VERCELLI (President)

ANTONIO BOCCALATTE

GIOVANNI ADORNI (President Substitute)

LESSONS

LESSONS START

https://courses.unige.it/11160/p/students-timetable

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Oral presentation of the assigned final project and evaluation of intermediate online activities.

ASSESSMENT METHODS

The exam grading is based on the mean average between scores of continuous evaluation of online activities carried out during the semester (50%) and the oral presentation of the assigned final project on course topics (50%).

Exam schedule