MOKV3500 Data visualization Course description

In this course students learn how to create data driven, interactive content for web and mobile using free open source web technology. The course includes cartography, statistics, source criticism, applied mathematics, programming and visualization. The course is suited for web journalism and other kinds of web content creation.

The course does not require previous experience with programming, but participants should have an interest for data and programming. Using your own laptop and having administrative rights to this laptop is highly recommended.

No pre requirements, but we want to inform that the course has progression provisions as described in the general part of the program plan.

Knowledge

The student knows:

• cartography
• correct use of different types of graphs
• How to search public databases
• data sources and source criticism
• basic statistical methods

Skills:

The student can:

• Find and refine data while maintaining the integrity of the dataset
• Use mathematics and programming to visualize data
• Produce user-friendly interactive maps and charts to communicate a message efficiently

General skills:

The student can

• Analyze data from various sources
• Produce digital stories for multiple platforms
• Analyze works within the field
• Communicate fact based and quantitative sources in a visual form.

This course has a high degree of project based activities. The course is organized as weekly seminars with practical challenges. Students will have readings and exercises to do between classes. Work will be performed individually, in groups and students will be required to have a presentation.

The course has three required assignments consisting of one individual assignment, one group presentation and one final assignment to be done individually or in groups.

1. Individual assignment: Datamap. Students have to demonstrate the skills needed to make a data driven map.
2. Group presentation: Students have to demonstrate analytical and critical skills by analyzing a data driven and visualized web product.
3. Project plan for final exam assignment.

The assignments will be marked as pass or fail by the teacher and all assignments must be completed before the student can take the exam.

Students who don't get their assignments approved on their first attempt can hand in a revised version once.

The exam is a final assignment based on assignment 3. The exam assignment requires completion of a data driven visualized product done individually or by groups of normally up to 3 students. Students have to demonstrate concept development, relevant use of data sources, refining data, visualizing data, interactivity and user-friendly design. All students must also submit an individual paper describing the process of the final project. This paper might result in an adjusted grade for the student.

All utilitites allowed as long as rules for source reference are followed.

Graded scale A-F.

The exam assignment is assessed per group by two sensors. For at least 25 percent of assignments one sensor must be external.

Gaute Heggen