Level of Study
Objectives and Content
The course introduces students to information technologies that not only store and manipulate data, but also explicitly represent the meaning of the data. Students will become familiar with the theoretical background as well as popular technologies and resources in use today. The aim is to give students a thorough understanding of the way information can be represented to enable interoperability and prepares for reasoning over data sets, especially data on the web. The theoretical studies will be supplemented with practical exercises in information modeling and retrieval.
A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
- knows the basic concepts for representing the semantics of data.
- knows the basic concepts for retrieving semantically-enriched data.
- knows the standards for semantic technologies, for example RDF and SPARQL.
- can design meaningful information representations.
- can add meaningful data to existing web resources
- can retrieve data from semantically-enriched data sets.
Required Previous Knowledge
Recommended Previous Knowledge
Access to the Course
Teaching and learning methods
12-16 two-hour lectures, 10-16 two-hour seminars
Compulsory Assignments and Attendance
Mandatory participation: Attendance at mandatory labs (at least 80%).
Forms of Assessment
3 hours written exam (60%)
1 assignment, group (40% )
Letter grade (A-F).
The course is evaluated by students every three years, and by the responsible lecturer each year.
Department of Information Science and Media Studies
For written exams, please note that the start time may change from 09:00 to 15:00 or vice versa until 14 days prior to the exam. The exam location will be published 14 days prior to the exam.
Type of assessment: Written exam and group assignment (New exam)
- Withdrawal deadline
Exam part: Written exam
- Examination system
- Digital exam