ISKM56 Data Visualization

Faculty of Arts
Autumn 2022
Extent and Intensity
0/2/0. 5 credit(s). Type of Completion: k (colloquium).
Teacher(s)
Mgr. Tomáš Marek (lecturer)
Mgr. Marek Lang, Ph.D. (assistant)
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
Thu 10:00–11:40 C11
Prerequisites (in Czech)
Tento předmět z nové akreditace nahrazuje B předmět s kódem VIKMB37. Pokud máte absolvován předmět VIKMB37, ISKM56 si nezapisujte.
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 30 student(s).
Current registration and enrolment status: enrolled: 7/30, only registered: 0/30, only registered with preference (fields directly associated with the programme): 0/30
fields of study / plans the course is directly associated with
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.
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
  • 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
  • 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
  • Jonathan Gray, Lucy Chambers, Liliana Bounegru. The Data Journalism Handbook. How Journalists Can Use Data to Improve the News. O'Reilly Media, c2012.
  • Scott Murray. Interactive Data Visualization for the Web. O’Reilly Media, c2013. ISBN: 978-1-449-33973-9
  • CAIRO, Alberto. The functional art: an introduction to information graphics and visualization. San Francisco: Peachpit Press, 2012, 363 pages. ISBN 03-218-3473-9
  • FEW, Stephen. Now you see it: simple visualization techniques for quantitative analysis. Oakland: Analytics Press, c2009, xi, 327 s. ISBN 978-097-0601-988.
  • MONMONIER, Mark S. How to lie with maps. 2nd ed. Chicago: University of Chicago Press, c1996, xiii, 207 p. ISBN 02-265-3421-9
  • 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.
  • Jeffrey Stanton. An Introduction to Data Science. Syracuse University, c2012.
  • Paul Bradshaw. Scraping for Journalists. Leanpub, c2013.
  • 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 (in Czech)
Závěrečné kolokvium a průběžné úkoly.
Language of instruction
Czech
Further Comments
Study Materials
The course is also listed under the following terms Autumn 2019, Autumn 2020, Autumn 2021, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2022, recent)
  • Permalink: https://is.muni.cz/course/phil/autumn2022/ISKM56