052215 VU Visualisation and Visual Data Analysis (2018W)

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

Prüfungsimmanente Lehrveranstaltung

URL http://vda.univie.ac.at/Teaching/Vis/18w/

Moodle

An/Abmeldung

Anmeldung von Sa 08.09.2018 09:00 bis So 23.09.2018 23:59
Abmeldung bis So 14.10.2018 23:59

Details

max. 50 Teilnehmer*innen

Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

    
    Dienstag
    02.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    04.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    09.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    11.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    16.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    18.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    23.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    25.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    30.10.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    06.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    08.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    13.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    15.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    20.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    22.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    27.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    29.11.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    04.12.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    06.12.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    11.12.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    13.12.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    08.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    10.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    15.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    17.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    22.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    24.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Dienstag
    29.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG
    
    Donnerstag
    31.01.
    13:15 - 14:45
    Hörsaal 3, Währinger Straße 29 3.OG

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

handing in of homework, 5x assignments, 70%
final examination, 30%

Mindestanforderungen und Beurteilungsmaßstab

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).

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 40.0%

In order to pass the course successfully, you will need to reach a minimum of 20% on each individual assignment as well as a minimum of 50% on the final exam.

Prüfungsstoff

applied exercises and tasks
accomplishing a team project
in-class presentations
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 07.09.2020 15:30