FF:ISKM56 Data Visualization - Course Information

ISKM56 Data Visualization

Extent and Intensity

0/2/0. 5 credit(s). Type of Completion: k (colloquium).
In-person direct teaching

Teacher(s)

Mgr. Tomáš Marek (lecturer)

Guaranteed by

PhDr. Petr Škyřík, Ph.D.
Department of Information and Library Studies – Faculty of Arts
Contact Person: Mgr. Alice Lukavská
Supplier department: Department of Information and Library Studies – Faculty of Arts

Timetable

Wed 10:00–11:40 K32, except Mon 18. 11. to Sun 24. 11.

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 33/20, only registered: 7/20, only registered with preference (fields directly associated with the programme): 7/20

fields of study / plans the course is directly associated with

there are 14 fields of study the course is directly associated with, display

Course objectives

Student will be able to design effective and meaningful visualization, use basic tools to visualize them, evaluate and discuss a graphical representation of the data in terms of their effectiveness in different contexts. On the theoretical level, students will be familiar with the basis of visual perception, design and aesthetics in visualization.

Learning outcomes

Upon completion of the course the student will be able to:
- evaluate and critically view data visualizations;
- design effective visualization solutions;
- use basic visualization tools;
- reflect on the role of data visualization in communication.

Syllabus

• Introduction
• Dataviz history
• Manipulative data visualization
• Cognition
• Effectivity od dataviz
• Data journalism
• Tools to visualize data
• Data visualization interpretation
• Maps and networks

Literature

recommended literature
• Jonathan Gray, Lucy Chambers, Liliana Bounegru. The Data Journalism Handbook. How Journalists Can Use Data to Improve the News. O'Reilly Media, c2012.
• Paul Bradshaw. Scraping for Journalists. Leanpub, c2013.
• Jeffrey Stanton. An Introduction to Data Science. Syracuse University, c2012.
• FEW, Stephen. Now you see it: simple visualization techniques for quantitative analysis. Oakland: Analytics Press, c2009, xi, 327 s. ISBN 978-097-0601-988.
• WONG, Dona M. The Wall Street journal guide to information graphics: the dos and don'ts of presenting data, facts, and figures. 1st ed. New York: W.W. Norton, c2010, 157 p. ISBN 03-930-7295-9.
• CAIRO, Alberto. The functional art: an introduction to information graphics and visualization. San Francisco: Peachpit Press, 2012, 363 pages. ISBN 03-218-3473-9
• Scott Murray. Interactive Data Visualization for the Web. O’Reilly Media, c2013. ISBN: 978-1-449-33973-9
• Fond Otakara Motejla. Příručka datové žurnalistiky. Nadace Open Society Fund Praha, c2013, ISBN 978-80-87725-10-8. Dostupná z www.osf.cz/publikace/prirucka-datove-zurnalistiky
• MONMONIER, Mark S. How to lie with maps. 2nd ed. Chicago: University of Chicago Press, c1996, xiii, 207 p. ISBN 02-265-3421-9
• YAU, Nathan. Visualize this: the FlowingData guide to design, visualization, and statistics. Indianapolis, Ind.: Wiley Pub., c2011, xxvi, 358 p. ISBN 11-181-4025-7
• YAU, Nathan. Data points : visualization that means something. Indianapolis: Wiley, 2013, xiii, 300. ISBN 9781118462195. info
• TUFTE, Edward R. The visual display of quantitative information. 2nd ed. Cheshire: Graphics Press, 2001, 197 s. ISBN 0-9613921-4-2. info
• HUFF, Darrell. How to lie with statistics. Illustrated by Irving Geis. New York: Norton, 1993, 142 p. ISBN 0393310728. info

Teaching methods

Seminars, lectures and discussion.

Assessment methods

The course ends with a final colloquium in small groups of students. During the semester, continuous assignments are given to be completed.

Language of instruction

Czech

Further Comments

Study Materials

• Enrolment Statistics (recent)
  
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