Research Topics in Model-Based Information Systems
Level of Study
Objectives and Content
The course provides the theoretical and technological foundations for developing and evolving model-centered information systems, in particular 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 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 big open data, semantic Internet of Things (IoT), semantic social media, semantic web services and workflows, semantic interoperability, information systems architectures, privacy and security. Semantic support for rapidly leveraging big open data sets in emergency situations is a possible application area. Examples of research and research methods in the area will also be presented and discussed.
A student who has completed the course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge: The candidate
- understands central concepts in model-based information systems.
- understands central concepts in information systems modelling, including ontologies and vocabularies.
- understands how the theories, technologies and standards are used to solve practical problems.
- know about topical reseach methods used in the area
Skills: The candidate
- 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
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%)
The grading system has a descending scale from A to E for passes and F for fail.
INFO310 is evaluated by students every three years and by the department every year.
Department of Information Science and Media Studies