- Visualization pipeline
- Human perception and laws of form
- Characteristics of data
- Visual coding and its systematization
- Interaction mechanisms
Visualization of univariate data
- Corridors visual mappings
- Discussion of the approaches
- Design guidelines and sources of error
Visualization of multivariate data
- Direct mapping procedures
- Performant implementations
- Linear projections in the visualization
Visualization of graphs
- Design strategies
- Tree representations
- Directed and undirected graphs
Scalar field visualization
- Representation of fields on the computer
- Basic procedures in 2D and 3D
Formal modelling of complex systems (M, 8.0 LP)
|Module Number||Module Name||CP (Effort)|
|INF-90-60-M-7||Formal modelling of complex systems||8.0 CP (240 h)|
|CP, Effort||8.0 CP = 240 h|
|Position of the semester||1 Sem. in WiSe|
|Level|| Master (Advanced)|
|Language||[DE/EN] German or English as required|
|Area of study||[INF-SI] Socioinformatics|
|Reference course of study||[INF-88.B16-SG] M.Sc. Socioinformatics|
|Type/SWS||Course Number||Title||Choice in |
|SL||SL is |
required for exa.
|P||42 h||78 h||
Continuous models of complex systems
|P||42 h||78 h||
- About [INF-19-31-K-5]: Title: "Data Visualization"; Presence-Time: 42 h; Self-Study: 78 h
- About [INF-19-31-K-5]: The study achievement "[U-Schein] proof of successful participation in the exercise classes (ungraded)" must be obtained.
- About [INF-57-51-K-6]: Title: "Continuous models of complex systems"; Presence-Time: 42 h; Self-Study: 78 h
- About [INF-57-51-K-6]: The study achievement "[U-Schein] proof of successful participation in the exercise classes (ungraded)" must be obtained.
Examination achievement PL1
- Form of examination: oral examination (30-45 Min.)
- Examination Frequency: each semester
- Examination number: 65753 ("Continuous models of complex systems")
Evaluation of grades
The grade of the module examination is also the module grade.
- mathematical problem formulation
- Phase space
- Concept of equilibrium, types of equilibria
- Attractors, strange attractors
- Concept of bifurcation
- Analysis of the system properties
- Conditions for the transition to chaotic systems
Competencies / intended learning achievements
Upon successful completion of the module, students will be able to
- to describe and apply models for the analysis of complex systems
- analyse and visualise the simulation results of these complex models
- to explain essential properties of complex phenomena (emergence, bifurcations, chaos) on the basis of a mathematical description of non-linear dynamic systems
- explain conditions for the transition to chaotic systems,
- model different concepts of complex systems,
- to analyse implemented concepts and system characteristics on concrete systems,
- implement basic techniques of data visualisation and apply them to specific problems
- analyse and categorise available techniques in terms of quality, efficiency and suitability for specific data
- select and apply appropriate visualisation techniques based on their functionality for the respective problem
- Alexandru C. Telea: Data Visualization Principles and Practice, AK Peters ltd., 2007.
- Robert Spence: Information Visualization, Addison Wesley, 2000.
- Colin Ware: Information Visualization, Morgan Kaufmann, 2. Edition, 2004.
- Boccara, Nino: Modeling complex systems . Springer Science & Business Media, 2010.
- Gros, Claudius: Complex and Adaptive Dynamical Systems, 2009.
Requirements for attendance of the module (informal)None
- Notice: Some Courses have informal requirements for attendance:
Requirements for attendance of the module (formal)None
References to Module / Module Number [INF-90-60-M-7]
|Course of Study||Section||Choice/Obligation|
|[INF-88.B16-SG] M.Sc. Socioinformatics||[Compulsory Modules] Socioinformatics||[P] Compulsory|