Universität Wien

052215 VU Visualisation and Visual Data Analysis (2016W)

6.00 ECTS (4.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work

URL http://vda.univie.ac.at/Teaching/Vis/16w/
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 50 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 04.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 06.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 11.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 13.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 18.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 20.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 25.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 27.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 03.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 08.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 10.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 15.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 17.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 22.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 24.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 29.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 01.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 06.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 13.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 15.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 10.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 12.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 17.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 19.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 24.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 26.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 31.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG

Information

Aims, contents and method of the course

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 , F$
* Principles of Evaluation of visual analysis systems
* some selected advanced topic

Assessment and permitted materials

active participation in class and online
handing in of homework
project completion and presentation
final presentation

Minimum requirements and assessment criteria

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

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

Examination topics

applied exercises and tasks
accomplishing a team project
in-class presentations

Reading list

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

Association in the course directory

Last modified: Mo 07.09.2020 15:30