UnivIS
Information system of Friedrich-Alexander-University Erlangen-Nuremberg © Config eG 
FAU Logo
  Collection/class schedule    module collection Home  |  Legal Matters  |  Contact  |  Help    
search:      semester:   
ACHTUNG: seit 15.06.2022 werden Lecture list nur noch über Campo verwaltet. Diese Daten in UnivIS sind nicht mehr auf aktuellem Stand!
 
 Layout
 
printable version

 
 
Computational Engineering (Rechnergestütztes Ingenieurwesen) (Master of Science) >>

  Visualization (Vis(A))

Lecturer
Prof. Dr.-Ing. Tobias Günther

Details
Vorlesung
Präsenz
2 cred.h, ECTS studies, ECTS credits: 2,5
nur Fachstudium, Sprache Englisch
Time and place: Mon 10:15 - 11:45, H4

Fields of study
WF INF-BA-V-GD ab 3 (ECTS-Credits: 5)
WF CE-BA-TW ab 3 (ECTS-Credits: 5)
WF CE-MA-INF 1 (ECTS-Credits: 5)
WF INF-MA ab 1 (ECTS-Credits: 5)

Contents
An old English adage says "a picture is worth a 1,000 words", meaning that complex ideas are often easier to convey visually. This lecture is about the craft of creating informative images from data. Starting from the basics of the human visual perception, we will learn how visualizations are designed for explorative, communicative or confirmative purposes. We will see how data can be classified, allowing us to develop algorithms that apply to a wide range of application domains.
The lecture covers the following topics:
  • data abstraction (data types, data set types, attribute types),

  • perception and mapping (marks and channels, effectiveness, pre- attentive vision, color maps),

  • task abstraction and validation (actions and targets),

  • information visualization tools (HTML, CSS, JavaScript, React, D3),

  • information visualization methods (tabular data, networks, trees),

  • scientific visualization methods (volume rendering and particle visualization),

  • scientific visualization tools (VTK, ParaView),

  • view manipulation (navigation, selection, multiple views),

  • data reduction (filtering, agreggation, focus and context),

  • lies in visualization (human biases and rules of thumb),

  • applications (deep learning, medical visualization, optimization)

The lecture is accompanied by voluntary exercises. Theoretical exercises concentrate on the classification of data and the design and analysis of visualizations, while programming exercises using web-based technologies give examples of their implementation.
(automatisch geplant, erwartete Hörerzahl original: 50, fixe Veranstaltung: nein)

Recommended literature
Visualization Analysis and Design, Tamara Munzner, 2014.

ECTS information:
Credits: 2,5

Literature
Visualization Analysis and Design, Tamara Munzner, 2014.

Additional information
Keywords: Visualization
Expected participants: 50, Maximale Teilnehmerzahl: 50

Assigned lectures
UE ([präsenz]):Tutorials to Visualization
Lecturers: Prof. Dr.-Ing. Tobias Günther, Xingze Tian, M. Sc.
Time and place: Mon, Thu 14:15 - 15:45, EE 0.135

Verwendung in folgenden UnivIS-Modulen
Startsemester WS 2022/2023:
Visualization (Vis)

Department: Chair of Computer Science 9 (Computer Graphics)
UnivIS is a product of Config eG, Buckenhof