Universität Wien

052215 VU Visualisation and Visual Data Analysis (2020W)

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

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

The lectures of this course will be held online via Collaborate on Moodle: https://moodle.univie.ac.at/mod/lti/view.php?id=5823944

  • Thursday 01.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 06.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 08.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 13.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 15.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 20.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 22.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 27.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 29.10. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 03.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 05.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 10.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 12.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 17.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 19.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 24.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 26.11. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 01.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 03.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 10.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 15.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 17.12. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 07.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 12.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 14.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 19.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 21.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Tuesday 26.01. 13:15 - 14:45 Hörsaal 3, Währinger Straße 29 3.OG
  • Thursday 28.01. 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 , 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

Assessment and permitted materials

handing in of homework, 6x assignments, 56%
2 tests, 40%
participation 4%

Minimum requirements and assessment criteria

A mandatory prerequisite for this class is the successful completion of either Foundations of Computer Graphics (05-2200) or Foundations of 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 as well as a minimum of 50% on the tests combined.

Examination topics

applied exercises and tasks
readings

Reading list

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

various papers as presented on the course page

Association in the course directory

Module: VIS VMI

Last modified: Th 08.09.2022 00:15