Universität Wien
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136013 UE Visualization of humanities data (2022S)

5.00 ECTS (2.00 SWS), SPL 13 - Europäische und Vergleichende Sprach- und Literaturwissenschaft
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 25 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine

The course will be held parallel to the VU Visual and Exploratory Data Analysis (2022S). For course times and venue see:
https://ufind.univie.ac.at/de/course.html?lv=053622&semester=2022S

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Computer-based visualization systems provide visual representations of datasets intended to help people carry out some task more effectively. These datasets can come from very diverse sources, such as scientific experiments, simulations, medical scanners, commercial databases, financial transactions, health records, social networks and the like. In this course we deal with effective visual mappings as well as interaction principles for various data, understand perceptual and cognitive aspects of visual representations and learn how to evaluate visualization systems.

Topics covered will include (but are not limited to):

* Introduction and historical remarks
* Visual design principles and the visualization pipeline
* Design studies
* Data acquisition and representation
* Basic visual mapping concepts (marks + channels)
* Human visual perception + Color
* Visual mappings for tables and multi/high-dimensional data
* Visual mappings for networks, graphs and trees
* Visual mappings and algorithms for 2D+3D scalar, vector, and tensor fields
* Visual mappings for text data
* Principles of multiple coordinated views
* Data interaction principles including Brushing+Linking, Navigation+Zoom , Focus+context
* Principles of Evaluation of visual analysis systems
* some selected advanced topic

Course-specific goals -- students can:
* represent and interact with various data visually
* evaluate visual depictions of data and possible find improved presentations
* assist users in visual data analysis
* use different visual analysis tools, like Tableau

General goals -- students gain:
* insight into a new discipline and extend their scientific horizons
* an appreciation for the interplay of mathematical analysis and user-centered design

Art der Leistungskontrolle und erlaubte Hilfsmittel

handing in of homework, 5x assignments
participation
test

Mindestanforderungen und Beurteilungsmaßstab

There is no formal prerequisite.

The grading scale for the course will be:
1: at least 87.5%
2: at least 75.0%
3: at least 62.5%
4: at least 50.0%

In order to pass the course successfully, you will need to reach a minimum of 50% on all assignments combined, 25% of the points on the last assignment, as well as a minimum of 40% on the test.

Prüfungsstoff

applied exercises and tasks
readings

Literatur

T. Munzner: Visualization Analysis & Design: Abstractions, Principles, and Methods, CRC Press, 2014

various papers as presented on the course page

Zuordnung im Vorlesungsverzeichnis

DH-S II
S-DH Cluster III

Letzte Änderung: Do 04.07.2024 00:13