FSS:POL371 Data Visualization - Course Information

POL371 Data Visualization in Social Sciences

Extent and Intensity

0/2/0. 4 credit(s). Type of Completion: z (credit).

Teacher(s)

Mgr. Jan Boček (lecturer)
Mgr. Matěj Málek (lecturer)
Mgr. Tomáš Marek (lecturer)
doc. Mgr. Michal Pink, Ph.D. (lecturer)
Mgr. Jan Pospíšil (lecturer)

Guaranteed by

prof. PhDr. Stanislav Balík, Ph.D.
Division of Politology – Department of Political Science – Faculty of Social Studies
Contact Person: Mgr. Lucie Pospíšilová
Supplier department: Division of Politology – Department of Political Science – Faculty of Social Studies

Timetable

Fri 3. 3. 9:45–15:00 U41, Fri 24. 3. 9:45–15:00 U41, Fri 7. 4. 9:45–15:00 U41, Fri 5. 5. 9:45–15:00 U41

Course Enrolment Limitations

The course is only offered to the students of the study fields the course is directly associated with.

fields of study / plans the course is directly associated with

• Political Science (programme FSS, B-HE) (2)
• Political Science (programme FSS, B-HS)
• Political Science (programme FSS, B-KS) (2)
• Political Science (programme FSS, B-MS) (2)
• Political Science (programme FSS, B-PL) (4)
• Political Science (programme FSS, B-PS) (2)
• Political Science (programme FSS, B-SO) (2)
• Political Science (programme FSS, B-SP) (2)
• Sociology (programme FSS, B-HE)
• Sociology (programme FSS, B-HS)
• Sociology (programme FSS, B-KS)
• Sociology (programme FSS, B-MS)
• Sociology (programme FSS, B-PL)
• Sociology (programme FSS, B-PS)
• Sociology (programme FSS, B-SO) (2)
• Sociology (programme FSS, B-SP)
• Sociology (programme FSS, B-TV)
• Public Policy and Human Resources (programme FSS, B-PL) (2)

Course objectives

In the first prt of the course students explore theoretical concepts for data visualisation: basic visual perception (how brain perceive colors, symbolsetc.) and principle of effective data visualisaton. Second part of the course is dedicated od problematic visualisation and manipulative graph. Last part of the course is practical, focused on source of the data, data acquring, analyse, maps, and interactive visualisation.

Syllabus

• 1. Introducton in to the course 2. Basic terminology 3. History and evolution of data visualisaton 4. Data and storytelling 5. Acquiring and processing 6. Visual perception, colors, design 7. Efficacy of visualisation 8. Manipulative visualisation 9. Acquiring and data analyse 10. Maps and copypast 11. Geodata 12. Tools for map projection

Literature

required literature
• Jeffrey Stanton. An Introduction to Data Science. Syracuse University, c2012.

Teaching methods

Seminar group

Assessment methods

homework, four time per term

Language of instruction

Czech

Further Comments

Study Materials
The course is taught annually.

• Enrolment Statistics (recent)
  
• Permalink: https://is.muni.cz/course/fss/spring2017/POL371