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Information Visualization and Visual Analytics
Typ: International Master in Computer Science - Studienprofil VC
Semester: WS 2014/2015
Umfang: 3V+1Ü
Studiengang: Master Informatik, Master Softwaretechnik, Diplom Informatik, Diplom Softwaretechnik
Dozent: Dr. Steffen Koch
Beschreibung:

The lecture ‚Information Visualization and Visual Analytics’ offers an introduction into both visualization fields. It covers Information Visualization (InfoVis) models and techniques for visualizing quantitative data, relational information, and multivariate data as well as corresponding interaction approaches. The syllabus further includes Visual Analytics (VA) techniques and methodologies for dealing with complex analytic tasks as they occur, e.g., in Big Data contexts. The lecture is complemented with examples of current research problems in both fields and additionally touches on domain-specific characteristics of visualization disciplines such as geographical visualization, visualization of biological data, social media analysis, text analysis, etc.

Infos and updates:

- last lectures will be held on 11.2. and 12.2. (see below)


Lecture dates

15. October 2013 14:00 - 15:30 (0.463):

Lecture - Organisational issues

Lecture - Introduction (release of first assignment)

16. October 2013 14:00 - 15:30 (0.463):

Lecture - Introduction (continued)

22./23.10.

Lecture - Perception and Attention

29./30.10.

Lecture - Graphs and Networks

5./6.11.

Lecture - Slides on Trees and Hierarchies will follow...

19./20.11.

Lecture - Trees & Hierarchies (Dr. Michael Burch)

26./27.11.

Lecture - Slides on Visualization of Multivariate Data will follow...

3./4.12.

Lecture - Visualization of Multivariate Data

10./11.12.

Lecture - Visualizing Time Series Data

17./18.12.2014/7.1.2015

Lecture - Interaction

8.1.2015

Lecture - Visual Analytics, Models and Concepts

14./15.1.2015

Lecture -

21.1.2015

Lecture - Geovisualization (Robert Krüger, Dennis Thom)

22.1.2015

Lecture - Visualizing Biological Data (Corinna Vehlow)

28.1.2015

Lecture - Software Visualization (Dr. Fabian Beck)

29.1.2015

Lecture - cancelled

4.2.2015

Lecture - Text Visualization (Florian Heimerl)

5.2.2015

Lecture - Document Visualization (Harald Bosch)

11.2.2015

Lecture - Eyetracking, Evaluation (Tanja Blascheck, Kuno Kurzhals, Michael Raschke)

12.2.2015

Lecture - Wrap Up

 


Exercise dates

23. October 2013 14:45 – 15:30 (0.463): 

Assignment 1 will be discussed (Corinna Vehlow)

30. October 2013 14:45 – 15:30 (0.108):

Assignment 2 will be discussed (Robert Krueger)
Data sets for the programming part: matrix100.csv, matrix2000.csv
Note for exercise 1: in addition to the requirements for the executables (.exe and .jar), we accept python programs running under python version 3.4.2.

06. November 2013 14:45 – 15:30 (0.108): 

Assignment 3 will be discussed

20. November 2014 14:45 – 15:30 (0.108):

Assignment 4 will be discussed

27. November 2014 14:45 – 15:30 (0.108):

Assignment 5 will be discussed
Data set: aufgabe5_1_all.csv
Note: submission is until 24.11.2014, 8:00 am

4. December 2014 14:45 – 15:30 (0.108):

Assignment 6 will be discussed
Data set: exercise6_1.csv GameOfThronesTree.png
Note: submission is until 01.12.2014, 8:00 am

11. December 2014 14:45 – 15:30 (0.108):

Assignment 7 will be discussed

18. December 2014 14:45 – 15:30 (0.108):

Assignment 8 will be discussed
Data set: cars.txt

15. January 2015 14:45 – 15:30 (0.108):

Assignment 09 will be discussed
Data set: composers.xml

22. January 2015 14:45 – 15:30 (0.108):

Assignment 10 will be discussed
29. January 2015 14:45 – 15:30 (0.108):

Assignment 11 will be discussed
Data set: migration_europe.bgraph
Additional material: map_europe.png


05. February 2015 14:45 – 15:30 (0.108):

Assignment 12 (last assignment) will be discussed

 

 


Bilder:
Internet-Seite:
Termine: Mittwoch, 14:00 - 15:30 Uhr in 0.463
Donnerstag, 14:00 - 14:45 Uhr in 0.108
Übungen: Donnerstag, 14:45 - 15:30 Uhr in 0.108
Tutor: Markus John M.Sc.
Robert Krüger M.Sc.
Dipl.-Inf. Hansjörg Schmauder
Dipl.-Ing. Corinna Vehlow

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