Student Pages
Postgraduate course

Research Topics in Semantic Information Systems

  • ECTS credits15
  • Teaching semesterAutumn
  • Course codeINFO320
  • Number of semesters1
  • LanguageEnglish
  • Resources

Main content

ECTS Credits


Level of Study


Teaching semester


Objectives and Content

The course provides the theoretical and technological foundations for developing and evolving information systems that are driven by semantic models, such as ontologies and vocabularies and that leverage big open data sets. The course also gives the academic background for supervised research on information systems that are based on semantic models. The course reviews and discusses topical theories, technologies and standards for information systems that are based on or driven by knowledge graphs and ontologies. The course also involves actual development work using selected technologies and standards, and it covers a selection of closely related topics such as big open data, semantic Internet of Things (IoT), semantic social media, semantic web services and workflows, and semantic interoperability. Examples of research and research methods in the area will also be presented and discussed.

Learning Outcomes

A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge: The student

  • understands central concepts in semantic information systems
  • understands central concepts of knowledge graphs and ontologies
  • understands how the theories, technologies and standards are used to solve practical problems
  • know about topical research methods used in the area

Skills: The student

  • can describe and discuss current research and industry trends in semantic information systems and relevant semantic modelling techniques
  • can describe and discuss a selection of related topics such as big open data, semantic Internet of Things (IoT), semantic social media, semantic web services and workflows, and semantic interoperability
  • can use the theories, technologies and standards to solve real problems and to justify the choices behind the solution

Required Previous Knowledge

Bachelor's degree in information science or equivalent.

Access to the Course

Master's Programme in Information Science. Other master students may apply for admission.

Teaching and learning methods

Lectures, and work with assignments, presentations and discussions.

Compulsory Assignments and Attendance

  • Participation at 80% of course seminars. 
  • Plenary presentations of individual essay and group assignment.

Forms of Assessment

Exam in three parts:

  • Written exam, 3 hours (30%)
  • Individual, theoretical essay with thoughtful research and discussion of an assigned topic (30%)
  • Practical assignment in groups (40%)

Grading Scale

The grading system has a descending scale from A to E for passes and F for fail.

Assessment Semester

Assessment in teaching semester. Only students who have a valid document of absence will be entitled to take a new exam the following semester.

Reading List

The reading list will be published on June 1st  / December 1st

Course Evaluation

All courses are evaluated according to UiB's system for quality assurance of education.

Programme Committee

The Information Science Programme Committee is responsible for the professional content and structure of the study program and for the quality of the study program and all courses there.

Course Administrator

Department of Information Science and Media Studies at the Faculty of Social Sciences has the administrative responsibility for the course and the study programme. 


Student adviser: Studierettleiar@ifi.uib.no

Tlf 55 58 41 17