OVERVIEW

The Semantic Web Technologies are the main focus of the course, starting from XML and RDF up to the conceptual representations in OWL; these technologies will be used to design and implement smart user interfaces exploiting ontologies, open and linked data.

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.

TEACHING METHODS

Lectures and seminars will be provided during the fall semester. Online activities will be delivered via Aulaweb to permit a continuous evaluation of students' competences.

SYLLABUS/CONTENT

Synopsis

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: models and software frameworks for semantic projects in OWL-S, SAWSDL and microformats. Semantic wiki technologies.

RECOMMENDED READING/BIBLIOGRAPHY

• Liyang Yu, A Developer's Guide to the Semantic Web, 2nd Edition, Springer, 2014
• G. Vercelli and G. Vivanet, E-learning and Semantic Web, GUP, 2012
• 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)

GIOVANNI ADORNI

LESSONS

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