Research Topics in Big Data

Postgraduate course

ECTS credits: 10
Teaching semesters
Course code: INFO319A
Number of semesters: 1
Teaching language: English
Resources: Schedule

Select course description for semester

Objectives and Content

The course provides the theoretical and technical foundations for managing and rapidly exploiting big data sets, such as data from public sources, social media/crowdsourcing, and the Internet. It covers general theories and technologies for big data, including sourcing, analysis, curation, processing, use, and evaluation. The course focuses on the exploitation of big data in a selected domain, for example media content production. It gives the academic background for supervised research on uses of big data in that domain. The course involves development work using selected technologies and standards for big data. Examples of research and research methods in the area will also be presented and discussed.

Learning Outcomes

Knowledge

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 how big data can be exploited in the selected domain
know about current research and industry trends in big data in the selected domain
know the relevant research methods for the area

Skills

Upon completion of the course the candidate shall be able to

use central technologies and tools for managing and using big data
exploit big data in the selected domain
prepare and evaluate uses of big data in practice

ECTS Credits

10 ECTS

Level of Study

Master level

Semester of Instruction

Irregular (not taught every year)

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

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

Examn in tree parts:

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 exam assignment will be given in the language of instruction in the course.The exam answer must be submitted in the same language as the exam assignment.

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.

Students with valid absence as defined in the UiB regulations § 5-5 can apply for an extended submission deadline to eksamen.infomedia@uib.no. The application must be submitted before the deadline for submission has expired.

Reading List

The reading list will be ready before 1 July for the autumn semester and 1 December for the spring semester.

Course Evaluation

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

Examination Support Material

Writtenexam: Dictionary preapproved by the Faculty

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 Coordinator

The Programme Committee is responsible for the content, structure and quality of the study programme and courses.