Universität Wien

052215 VU Visualisation and Visual Data Analysis (2024W)

6.00 ECTS (4.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Prüfungsimmanente Lehrveranstaltung

URL http://vda.univie.ac.at/Teaching/Vis/
Moodle

An/Abmeldung

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

Details

max. 50 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Dienstag 01.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 03.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 08.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 10.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 15.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 17.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 22.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 24.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 29.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 31.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 05.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 07.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 12.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 14.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 19.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 21.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
    Seminarraum 3, Währinger Straße 29 1.UG
  • Dienstag 26.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 28.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 03.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 05.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 10.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 12.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Dienstag 17.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 16.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
    Seminarraum 4, Währinger Straße 29 1.UG
  • Dienstag 21.01. 11:30 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Donnerstag 23.01. 11:30 - 14:45 Seminarraum 2, Währinger Straße 29 1.UG

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
* 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
* use D3 to create interactive web-visualization environments

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
* experience working in a team

Art der Leistungskontrolle und erlaubte Hilfsmittel

5 homework assignments
2 tests
participation
presentation

Mindestanforderungen und Beurteilungsmaßstab

A mandatory prerequisite for this class is the successful completion of either Foundations of Computer Graphics (05-2200) or Foundations or Data Analysis (05-2300).

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 tests combined. Additionally, you need to get 50% of the score on the presentation for the last assignment.

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

Module: VIS VMI

Letzte Änderung: Mo 20.01.2025 15:05