| Professor |
Prof. Dr. Andreas Kerren
|
| Time & Place |
Compare here!
In general, the lectures will take place online via Zoom.
|
| Teaching Period |
I (2020-08-31 till 2020-10-30)
|
| Assessment |
Assignments AND oral examinations. Oral examinations will take place via Zoom in week 44.
|
| Prerequisites |
90 credits in Computer Science (including a degree project at Bachelor level). English B/English 6 or the equivalent.
|
| Credits |
5 ECTS
|
| Topic |
Basics in Information Visualization
Information Visualization (InfoVis) covers the development of tools for better understanding
and analyses of abstract information using the human visual system. Abstract information
can normally not be transferred into the physical world. This course gives you an overview
of the most important techniques of this research area including fundamentals. Covered
topics are among others: visual perception, interaction techniques (e.g., level of detail,
navigation, focus and context, ...), and visualization techniques for multi-dimensional data sets (tables).
The course Advanced Information Visualization and Applications extends this course with visualization techniques and systems for special data sets.
|
| Schedule |
Preliminary Schedule:
| # |
Date |
Topic |
Slides |
| 1 |
2020 09 01 |
Introduction and Motivation |
|
| 2 |
2020 09 08 |
Perception Theory I |
|
| 3 |
2020 09 15 |
Perception Theory II |
↑
|
| 4 |
2020 09 22 |
InfoVis Basics (Reference and Design Models) |
|
| 5 |
2020 09 23 |
InfoVis Basics (Data/Task Abstractions) |
↑
|
| 6 |
2020 09 29 |
Interaction I (Dynamic Queries) |
|
| 7 |
2020 10 06 |
Interaction II (Zoom&Pan, Overview&Detail) |
↑
|
| 8 |
2020 10 13 |
Interaction III (Focus&Context) |
↑
|
| 9 |
2020 10 20 |
1D, 2D, 3D, and Multidimensional Data |
|
|
| Materials |
Learning Environment:
Visualization Tools and Libraries:
- D3 (JavaScript)
- Vega (JavaScript; based on D3)
- Vega-Lite (JavaScript; based on D3 and Vega)
- plotly.js (JavaScript; based on D3)
- nivo (JavaScript; based on D3 and React)
- Victory (JavaScript; based on D3 and React)
- Chart.js (JavaScript)
- vis.js (JavaScript)
- Highcharts (JavaScript)
- Google Charts (JavaScript)
- Rickshaw (Temporal data; JavaScript; based on D3)
- Leaflet (Geospatial data (maps); JavaScript)
- Sigma (Graph/network data; JavaScript)
- Bokeh (Python; generates a web-based visualization)
- Dash (Python or R; generates a web-based visualization using plotly.js)
- plotly.py (Python; generates a web-based visualization using plotly.js)
- Altair (Python; generates a web-based visualization using Vega and Vega-Lite)
- mpld3 (Python; generates a web-based visualization using D3)
- Shiny (R; generates a web-based visualization)
- Shiny Dashboard (R; generates a web-based visualization using Shiny)
- Tableau (Visualization environment, Dashboards)
- QlikView (Visualization environment, Dashboards)
- Power BI (Visualization environment, Dashboards)
- Visualize Free (Online, Dashboards)
- Keshif Online (Online, Dashboards)
- yFiles (Several platforms)
- Gephi (The Open Graph Viz Platform; Java)
- Processing (Environment for graphics programming; several platforms)
- Improvise (Java)
- JFreeChart (Java)
- ggplot2 (R)
- Chaco (Python)
- Matplotlib (Python)
No longer in active development (not recommended for assignments):
Interesting URLs:
|
| Assignments |
Assignments consist of theoretical and practical exercises. They will be supervised by
Angelos Chatzimparmpas.
Assignments:
- Assignment 1 (Deadline: 2020-09-07, Presentation: 2020-09-08, 15:00-16:45, online via Zoom)
- Assignment 2 (Deadline: 2020-09-21, Presentation: 2020-09-22, 15:00-16:45, online via Zoom)
- Assignment 3 (Deadline: 2020-10-05, Presentation: 2020-10-06, 15:00-16:45, online via Zoom)
- Assignment 4 (Deadline: 2020-10-26, Presentation: 2020-10-27, 13:00-14:45, online via Zoom)
|
| Open Theses |
We permanently offer interesting topics for Bachelor's and Master's Theses that are related to Information Visualization and Software Visualization.
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