Semantic Web and Linked Data

Code:

M.EIC047

Acronym:

WSDL

Keywords
Classification	Keyword
OFICIAL	Information Systems

Instance: 2024/2025 - 1S

Active?	Yes
Responsible unit:	Department of Informatics Engineering
Course/CS Responsible:	Master in Informatics and Computing Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
M.EIC	28	Syllabus	2	-	6	39	162

Teaching language

English

Objectives

BACKGROUND

The syllabus of Semantic Web and Linked Data has a strong emphasis on representation and querying languages and their underlying principles, namely logic and inference.

These languages and principles provide a body of knowledge that ranges from the concepts of Semantic Web and Linked Data to their application in describing web resources and in explicit and interoperable representations for data in multiple domains. This content provides support for abstract learning objectives that involve aspects of data modeling, metadata creation, and ontology development. Applied learning objectives also follow the unit's topics, namely those on the use of Semantic Web technologies, interrogation languages, and Linked Data principles.

SPECIFIC OBJECTIVES

1. Describe and define the concepts and technologies associated with the Semantic Web;
2. Analyze and prepare artifacts (e.g., ontologies) for use in Semantic Web solutions;
3. Evaluate the value and applicability of semantic web strategies in various contexts;
4. Identify and apply multiple Semantic Web-related tools and techniques;
5. Analyze the characteristics of data and documents accessible to people and machines;
6. Relate web resources to the metadata that describe and link them;
7. Treat ontologies as providers of description tools;
8. Analyze existing ontologies and create new ontologies;
9. Explore applications that manipulate semantic web information descriptions and develop systematic methods for creating metadata;
10. Experiment with applications that explore Linked Open Data on the Web;
11. Use tools and languages to explore Semantic Web content;
12. Compare semantic web-based services and other approaches to resource description.

Learning outcomes and competences

On completion of this course, the student should be able to:

1. Describe and define the concepts and technologies associated with the Semantic Web;
2. Analyze and prepare artifacts (e.g., ontologies) for use in Semantic Web solutions;
3. Evaluate the value and applicability of semantic web strategies in various contexts;
4. Identify and apply multiple Semantic Web-related tools and techniques;
5. Analyze the characteristics of data and documents accessible to people and machines;
6. Relate web resources to the metadata that describe and link them;
7. Treat ontologies as providers of description tools;
8. Analyze existing ontologies and create new ontologies;
9. Explore applications that manipulate semantic web information descriptions and develop systematic methods for creating metadata;
10. Experiment with applications that explore Linked Open Data on the Web;
11. Use tools and languages to explore Semantic Web content;
12. Compare semantic web-based services and other approaches to resource description.

 

Working method

Presencial

Program

1. The Semantic Web Activity of W3C: Overview of technologies and standards


2. RDF—The Resource Description Framework


3. Metadata with RDF


4. Metadata taxonomies with RDF Schema


5. SPARQL queries


6. The OWL ontology language


7. Logic and Inference


8. The Web of Data


9. Publishing and Consuming Linked Data


10. Semantic Web Applications

Mandatory literature

Antoniou, G., Groth, P., van Harmelen, F., & Hoekstra, R. ; A Semantic Web Primer. , MIT Press; , 2021
Heath, T., Bizer, C; Linked Data: Evolving the Web into a Global Data Space., Synthesis Lectures on the Semantic Web: Theory and Technology, 1:1, 1-136. Morgan & Claypool, 2011

Comments from the literature

Other scientific journals:

International Semantic Web Conference (ISWC),  http://iswc.semanticweb.org/

Journal of Web Semantics, Elsevier, http://www.elsevier.com/wps/find/journaldescription.cws_home/671322/description

Teaching methods and learning activities

The theoretical components of classes are used for topic presentation, with reference to the bibliography, and for running small assignments to stimulate learning. The time dedicated to practical work is used to discuss topics proposed to students, to answer practical exercises on the Semantic Web and to develop the practical work. The practical work is expected to 1) analyze existing applications and make their presentation in class and 2) apply the theoretical concepts in a small project in an area of interest. 

 

Software

Neo4j
Protégé
oXygen

keywords

Physical sciences > Computer science > Informatics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	40,00
Trabalho prático ou de projeto	60,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto	123,00
Frequência das aulas	39,00
Total:	162,00

Eligibility for exams

n/a

Calculation formula of final grade

Distributed assessment with final exam

 

Final Rating = 60% * GradeWork + 40% * GradeExam

 

GradeWork: grades of the practical groupworks.

GradeExam: grade obtained in exam.

Examinations or Special Assignments

There are no special works or tests.

Special assessment (TE, DA, ...)

Students taking exams under special regimes are expected to previously submit the assignments required for this course.

Classification improvement

Students may improve the mark in the course's next edition.

Observations

https://teams.microsoft.com/l/meetup-join/19%3aPCnbkJl3LqoCg5H8jtMalH_c2P8aRa1_oU-ZjGTQgGI1%40thread.tacv2/1634544065210?context=%7b%22Tid%22%3a%22b7821bc8-67cc-447b-b579-82f7854174fc%22%2c%22Oid%22%3a%2230b26af4-bc7f-4dec-9e24-29fd1f94cc02%22%7d