Learning outcomes
After completing this course successfully, the students are capable of:

• Explaining the principles of Linked Data, comparing and applying the main standards of the Semantic Web stack
• Explaining, comparing and applying data format standards for Semantic Web applications (RDF serializations) 
• Designing and evaluating semantic models by following an ontology engineering methodology for a specific application domain
• Creating Linked Data dataset(s) from scratch and storing in a triplestore
• Reusing existing dataset(s), both from an available triplestore and by converting (“triplifying”) existing non-Linked Data datasets 
• Developing and evaluating a Semantic Web application that is capable of querying different datasets for data analytics

Course format

The following activities have been planned in this course:

• Lectures that address methods, techniques and typical problems related to Linked Data. These lectures are given in the form of a discussion forum, which means that you must prepare yourself by reading the material before the lecture. During some lectures you will be asked to do some simple exercises with software tools, so you are expected to bring your laptop to the lectures. Sheets will be made available in the Course material section after each lecture.
• Practical sessions that have been designed to motivate the students to practise with the techniques discussed during the lectures.
• Project to be performed by groups of two students. Students can subscribe to the project through this site. In the project, students have to submit three deliverables (report and code) and each student gives a presentation.
• Final exam consists of questions on the subjects discussed during the lectures and the practical sessions.

Course contents
This course focuses on Semantic Web (SW) standards, Linked Data principles, and tools.

The Semantic Web (SW) is an extension of the World Wide Web to make Internet data machine-readable in a way that can be consumed and understood by machines. This is supported by standards that are set by the World Wide Web Consortium (W3C), which are organized in the SW stack.

Linked Data (LD) are structured data interlinked with other data built upon the SW stack, enabling applications to share information in a way that can be automatically ‘understood’ by computers. Part of the vision of LD is to enable the Internet to behave as a “global database”, so technologies that use the SW standards have a high potential to facilitate web data to be processed ('understood') by machines. For example, triplestores can support the conversion and storage of the original data into knowledge graphs that are useful for Artificial Intelligence (AI) systems.

This is a project-based course offering conventional lectures and hands-on sessions (exercises and a project) as main learning activities. During the course, students apply the acquired knowledge in the practical (lab) sessions, and in the project, which covers the development of a SW application, including:

• Task 0: analyzing a case
• Task 1: creating a LD dataset through the ‘triplification’ of an existing dataset
• Task 2: engineering an ontology, and using it to represent a LD dataset
• Task 3: linking the LD datsets for integrated query analysis.

Main topics

• Web of data, Linked Data (LD), and Linking Open Data (LOD)
• Semantic Web (SW) standards
  • Knowledge representation language and vocabularies: W3C RDF, RDF schema, PROV, DCAT
  • Logics: OWL Lite, OWL DL
  • LD serializations: RDF/XML, Turtle (TTL), JSON-LD
  • Query and validation languages: SPARQL, SHACL
• Popular semantic resources: vocabularies, standards, and indexes (Linked Open Vocabularies)
• SW applications: AI, data analytics, reasoning, knowledge graphs

Course schedule

Weekly plan

Previous knowledge and complementary materials

It is recommended that students follow the course on Service-oriented Architecture with Web services (192652150) before or during this course. Materials of this course are available in the Canvas page of last year's edition, please subscribe as student to access the materials. 

Although this is not a formal prerequisite for this course, the students should know how to program and deploy web services following the RESTful architecture, and manipulate data with XML/XML schema, JSON/JSON schema, and in relational databases, including query languages as SQL.