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Semantic Technologies in Practice


Status Archive
School Computer and Information Science (CIS)
Division HCS
Owner Eva Blomqvist

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Course plan

No of lectures

Part I - self study (corresponding to about 5 lectures) and 4 homework exercises
Part II - approximately 10h lectures + 15h exercises
Part III - individual (practical) course project

Recommended for

PhD students in Computer Science, Informatics and Cognitive Science

The course was last given

New course

(Part of Part I, and potentially some lecture will be similar to the course in Enterprise Knowledge Management given in 2009 at Jönköping University.)


This course aims to introduce some of the basics of the Semantic Web, e.g. ontologies and their representation, as well as to show what those ontologies (or knowledge bases) can be used for in practical applications. In particular we focus on applications in content management and decision support, e.g. in security applications. After the course the students should be able to build an application ontology, understand and reuse existing ontologies, and apply some semantic technologies in a simple application. Theoretically the students should have an overview of semantic technologies in use today, e.g. for content management and decision support in different fields.
Part I:

  • The student should have an overview of the Semantic Web, its main technologies and languages, as well as the general state of the art

  • The student should be able to use RDF, OWL and SPARQL for modelling simple knowledge domains and retrieving knowledge from a knowledge base

  • The student should be able to use some basic ontology engineering environment

Part II:

  • The student should be able to choose an appropriate technology, tool or API for performing some specific task solved by semantic technologies

  • The student should be able to assess the potential and limits of semantic technologies, e.g. from the Semantic Web, for different use cases

  • The student should be able to perform some simple reengineering of other formalisms into RDF and OWL, e.g. to produce linked data

  • The student should be aware of how semantic technologies are used in advanced research and business use cases today, e.g. for applications in security, information logistics etc.

Part III:

  • The student should be able to apply one specific semantic technology to a chosen use case, potentially related to his or her research


Part I: Some basic knowledge of modelling, e.g. UML, ER, and basic logics (undergraduate).

Part II (for skipping Part I): Basic knowledge of Semantic Web languages (RDF, OWL, SPARQL) and basic ontology engineering, e.g. through courses such as Ontologies and ontology engineering or self-study.

Part III: Part II + basic programming knowledge.


The course is divided into three parts:
I) Foundations of the Semantic Web and Ontology Engineering
II) Applications of Semantic Technologies
III) Student Project

Part I is an optional self-study module, intended for those students who are not familiar with the Semantic Web and ontologies. Students will become familiar with basic techniques and the standards of the field, and gain some practical experience in ontology modelling. Examination consists of a set of individual take-home exercises. This part can be done during summer 2012 or in August-September, but all exercises should be handed in before the start of Part II.

Part II is the core part of the course (mandatory if taking the course) and consists of a set of lectures/seminars, including guest lectures from leading researchers in the Semantic Web and related fields, as well as practical exercises or mini-projects to explore different aspects of advanced ontology engineering and building or using semantic applications. In principle, each lecture has an associated exercise - leading to a quite hands-on focused course. Examination consists of participation in all lectures/seminars and providing solutions to exercises (if not finished during the session, the students will finish later and hand in the result). Part II will start in mid-September and be completed around the end of October (depending on the availability of invited lecturers).

Part III is an optional student project where the students can pick some technique related to the course topics, e.g. among the topics presented in Part II, and relate it to their own research by applying it to some small practical problem. Examination consists of a demonstration and written report of the project results. Part III can start from the beginning of October and should be finished by mid-December.


Technologies for exposing and exploiting the underlying semantics of information are important for building modern intelligent applications, e.g. for decision support. Technologies for knowledge representation is a cornerstone, but equally important are technologies and methods for acquiring knowledge and utilizing its representation in software systems. With the emergence of the Semantic Web, linked data etc., we have seen a change in how ontologies and semantic applications are developed and used. New representational standards as well as the fact that a large amount of ontologies and data, e.g. linked data, is now available online have changed the way we make use of semantic technologies.

Topics of the course includes:

Part I:
- Overview of the Semantic Web and linked data
- Formats and languages (RDF, OWL, SPARQL etc.)
- Ontology engineering and ontology engineering tools
- Brief introduction to methodologies and Ontology Design Patterns

Part II:
- Reengineering and reuse of knowledge and ontologies
- Publishing and utilizing linked data
- Building semantic applications (existing APIs etc.)
- Making use of legacy data for semantic applications
- Semantic applications in different fields, e.g. semantic CMS, security and surveillance, enterprise applications etc.

Part III:
- Topic selected by the student


No mandatory literature, for suggestions see below.

Part I:
Online tutorials on RDF, OWL and SPARQL.
"Semantic Web for the Working Ontologist" by Hendler & Allemange

Part II:
Literature suggestions given by the lecturers.

Part III:
API documentation and online tutorials


Examiner and lecturer:
Eva Blomqvist, Assistant Professor, IDA/HCS, Linköping Univeristy

Invited lecturers:
Prof. Fabio Ciravegna, OAK group, University of Sheffield
Dr. Valentina Presutti, STLab, ISTC-CNR, Rome
Prof. Kurt Sandkuhl, University of Rostock
Additional lecturers TBD...


Eva Blomqvist


Part I:
Handing in correct solution to the take-home exercises.

Part II:
Attendance at lectures/seminars + correct solutions to exercises.

Part III:
Demonstration and written report of the produced application.


Part I: 3HP
Part II: 4HP
Part III: 3HP


Page responsible: Director of Graduate Studies