15 ECTS (50% of a bi-mester)
Level of Study
Irregular (not taught every year)
Objectives and Content
The course provides the theoretical and technical foundations for managing and rapidly leveraging big data sets, for example originating from public sources, social media/crowdsourcing, and the Internet/Cloud of Things. It covers general theories and technologies for big data, including sourcing, curation, processing, use, and evaluation. The course focusses particularly on the application of big data for emergency management. It reviews theory and practice of emergency management and how emergency management can leverage big data. It gives the academic background for supervised research on the possible roles of big data for emergency management. The course involves development work using selected technologies and standards for big data and for emergency management. 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:
Upon completion of the course the candidate shall
- understand central concepts, standards, and technologies for big data
- know about current research and industry trends in big data
- understand central concepts and standards in emergency management
- understand how big data can be leveraged in emergency situations
- know about current research and industry trends in big data for emergency management
- know the relevant research methods for the area
Upon completion of the course the candidate shall be able to
- use central technologies and tools for managing and using big data
- use central technologies and tools for emergency management
- leverage big data in emergency situations
- prepare and evaluate uses of big data in emergency situations
Required Previous Knowledge
European (three-year) Bachelor's degree in information science or similar degree in ICT, covering basic programming skills.
Access to the Course
Master in Information Science or similar ICT background. Students in their last year of a 4 year Bachelor's programme can be admitted after application.
Teaching and learning methods
Lectures, and work with assignments, presentations and discussions. Parts of the course may be taught at a distance.
Compulsory Assignments and Attendance
Participation at 80% of course seminars is mandatory. When teaching is distributed across institutions, students in other institutions may participate online from their institution.
Compulsory requirements are only valid the semester they are approved.
Forms of Assessment
- Portfolio (55%)
- An individual, theoretical essay with thoughtful research and discussion of an assigned topic
- Practical assignment in groups
- Oral presentations of essay and group assignment (15%)
- Written exam (3 hours) (30%)
The grading system has a descending scale from A to E for passes and F for fail.
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.
All courses are evaluated according to UiB's system for quality assurance of education.
Department of Information Science and Media Studies
Telephone 55 58 90 00
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. Autumn 2020 written exams will be arranged either at home or on campus. Please see course information on MittUiB.
Type of assessment: Portfolio, oral presentation and written exam
- Withdrawal deadline
Exam part: Portfolio
- Examination system
- Digital exam
Exam part: Oral presentation
- Exam period
Exam part: Written examination
- 01.12.2020, 09:00
- 3 hours
- Examination system
- Digital exam