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 necessary.

None

After completing the course, the student should have the following overall learning outcomes defined in terms of knowledge, skills and general competence:

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. The following coursework requirements must have been approved in order for the student to take the exam:

1. Group presentation: Students have to demonstrate analytical and critical skills by analyzing a data driven and visualized web product. The presentation should last about 5 minutes not including Q&A.
   1. Aim: That the student via its own and others presentations gets a broad overview over various web based data visualization.
2. Individual assignment: Datamap. Students have to demonstrate the skills needed to make a data driven map.
   1. Aim: The student must make a map based on structured geographical data souce.
3. Project plan for final exam assignment. The plan should be at least 5 pages in length including images, sketches etc. The written part should be 700-1000 words.
   1. Aim: The students must as a group produce a plan for the exam project to get an assesment wether the project is appropriate and feasible.

All required coursework must be completed and approved by the given deadline in order for the student to take the exam. If one or more coursework requirements have not been approved, the student will be given the opportunity to submit an improved version one time by the given deadline.

The exam consists of two parts. 

Part 1 is a group or individual project made by groups of 1-3 students. The work must include a written article with at least 2 graphics elements based on structured datasets. At least one element must use the technology d3.js. The other element can be made with any tools we have used in class. All members of the group will get the same grade grade for part 1.

Part 2 is a individual written reflection paper where the student should demonstrate the learning outcomes for the project and the course. The paper should be about 2000 words in length. The assessment of the reflection paper can result in the student’s final grade being adjusted one step up or one step down. Font and font size: Arial/Calibri 12 points. Line spacing: 1.5.

The student must pass all parts of the exam to get an overall pass. 

All aids are permitted, as long as the rules for source referencing are complied with.

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. The grades set by an external sensor sould form the basis for asessing the level of the assignments in relation to grades. Internal sensors must take into account the external sensors assessment during sensoring.

Gaute Heggen