Postgraduate course

Research Topics in Model-Based Information Systems

Level of Study

Master level

Teaching semester


Objectives and Content

The course provides the theoretical and technological foundations for developing and evolving model-centered information systems. The course offers a broad spectrum of formal method techniques including graph theory, logic (FOL, Temporal logic), model transformation, reasoning and automatic verification using model checking. This course also gives the academic background for supervised research on model-based information systems.
The course reviews and discusses topical theories, technologies and standards for model-based and model-driven information systems and for suitable models and modelling languages. The course also involves actual development work using selected technologies and standards, and it covers a selection of closely related topics such as designing process models, Internet of Things (IoT) platforms, information systems architectures, privacy and security. 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:


The student

  • understands central concepts in model-based information systems.
  • understands central concepts in information systems modelling.
  • understands how the theories, technologies and standards are used to solve practical problems.
  • know how to specify properties of parallel distributed systems using linear temporal logic and computation tree logic and how to automatically verify such systems.
  • know about topical reseach methods used in the area.


The student

  • can describe and discuss current research and industry trends in model-driven information systems and relevant modelling techniques.
  • can describe and discuss related topics such as information systems architectures, web services/cloud services, semantic interoperability, privacy and security.
  • use the theories, technologies and standards to solve such problems and to justify the choices behind the solution.
  • can describe how to specify properties of a safety critical system and verify such system.

Required Previous Knowledge

Bachelor's degree in information science or equivalent.

Access to the Course

Master 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 is mandatory.

Forms of Assessment

  • Written exam (30%)
  • An individual, theoretical essay with thoughtful research and discussion of an assigned topic (30%)
  • In addition there is a 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 written exam the following semester.

Course Evaluation

INFO310 is evaluated by students every three years and by the department every year.


Department of Information Science and Media Studies


Contact Information


Exam information

  • 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. Candidates must check their room allocation on Studentweb 3 days prior to the exam.

  • Type of assessment: Written exam, essay and group assignment

    • Exam part: Written exam

      26.05.2020, 09:00
      2 hours
      Examination system
      Digital exam
    • Exam part: Essay

      Submission deadline
      14.05.2019, 14:00
    • Exam part: Group assignment

      Submission deadline
      04.05.2019, 14:00