Data Visualization (II) (ILV)

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Course numberM2.08760.11.181
Course codeVISU2
Curriculum2021
Semester of degree program Semester 3
Mode of delivery Presence- and Telecourse
SPPW3,5
ECTS credits5,0
Language of instruction English

Acquisition of knowledge and skills to create advanced interactive and dynamic visualizations of modern sensor data.

Consolidation of lecture "Data Visualization (I)" and introduction to advanced techniques in information visualization. In the context of the paradigm "Visual Analytics" the lecture will cover advanced techniques in scientific visualization and geovisualization. Especially the interactive, dynamic mapping of sensor data. Subtopics will be:

  • 2D and 3D scalar fields: Choropleths, heatmaps, height fields, isocontours
  • 2D and 3D Vector fields: Streamlines, derived fields, Isocontours, Direct volume rendering, Point based rendering
  • High-dimensional data: Principal Component Analysis, Multidimensional Scaling, Isomap
  • Large dynamic graph visualization
  • Big data visualization
  • Reasoning and Storytelling
Advanced techniques for geovisualization like generalization of spatial data will be introduce and how multiscale visualizations in the context of satellite imagery, media that contain visuospatial information (e.g., street level imagery, 3D models, videos, animations, etc.), and maps could be created and linked to classical visualizations like plots, charts, and other types of graphics.
In small projects the students will work with modern tools which allow creating interactive visual displays fairly quickly and without a very steep learning curve (e.g., GeoVISTA Studio, Google Maps, Scribble Maps, Mapbox, Carto, Tableau, Gephi, etc.), and there are fully flexible software development environments and scripting languages for visual programming (e.g., Processing, Python, D3.js, Leaflet, WebGL, etc.) of dynamic applications.

Lecture script as provided in the course (required)
Colin Ware, Information Visualization: Perception for Design, Morgan Kaufmann, 4th edition, 2020, ISBN-13: 978-0128128756
Gennady Andrienko, Natalia Andrienko, Peter Bak, Daniel Keim, Stefan Wrobel, Visual Analytics of Movement, Springer, 2013, ISBN-13: 978-3642375828
Cole Nussbaumer Knaflic, Storytelling with Data: A Data Visualization Guide for Business Professionals, Wiley, 2015, ISBN-13: 978-1119002253
Martin Falk, Sebastian Grottel, Michael Krone, Guido Reina, Interactive GPU-based Visualization of Large Dynamic Particle Data, Morgan & Claypool Publishers, 2016, ISBN-13: 978-162705285

Integrated course - teaching & discussion, demonstration, practical examples, guest lectures by specialists, project work and presentations

Immanent examination character: presentation, assignment reports