In­ter­ac­ti­ve Da­ta Vi­su­a­li­za­ti­on (Mas­ter, in Eng­lish)

Lectures, Assignments and Project. 6 ECTS. For Focus Areas “Data Science” and “Intelligence and Data” (for older examination regulations: Module III.4.1)

Dates (look out for possible changes in dates and times and rooms - these are out of my responsibility and implemented by our administration):

Wednesdays, 11:15-12:45 in F0.530, lectures, starting April 10, 2019. It is mandatory to participate on April 10 for those students who want to finish the course in summer 2019. Everything you will need to know to get a grade in this course will be discussed that morning. 

Thursdays, 16:15 - 18:30 in F1.110, labs and lectures, starting April 11, 2019. We will continue with lectures during the first week, so pick Thursday or Friday and show up.  

Fridays, 8:15 - 10:30 in F0.530, labs and lectures, starting April 12, 2019. We will continue with lectures during the first week. Lectures and labs from Thursday will be repeated.

The objective of this course is to prepare you for various challenges in data visualization:
We will teach you

  • a wealth of visualization techniques, organized by data types and tasks, to look at/practice with/remember for the time you will need them,
  • very basic math that you will need for preprocessing and analyzing data,
  • some in-depth visualization algorithms,
  • knowledge on data characteristics, human perception and design techniques that will help you to map data to expressive and effective visuals.

An important part of this course will be to program some (interactive) techniques yourself. You will not learn how to program in this course, as I am expecting a Computer Science Master student to be able to do that on his/her own.

If you plan to participate in the Master Course “Interactive Data Visualization”, please try out the following self-test. It may take a few minutes or a few hours or a weekend to do so (depending on your level of programming and knowledge of graphics/visualization libraries), but if you do, you will be much better prepared for the assignments of this course.

So, as a self-test, I am challenging you to

  • download the Colorado Elevation Data set:
    http://www.idvbook.com/teaching-aid/data-sets/the-colorado-elevation-data-set/
  • visualize the data set by displaying data on a 400x400 pixel square on your display in a grey scale: black to grey to white (lower values are black to dark grey; higher values are light grey to white.)
  • check yourself if your pictures displays the data correctly: print/plot a few profile lines (e.g. line 100 and line 300) and compare to display. If low data values are correctly displayed as black to dark grey and high data values are correctly displayed as light grey to white, there is a good chance you did well. What is the minimum and the maximum of the data? How do these values correspond to the real elevations of Colorado (do a quick check on the internet). Pick a real max and min of the Colorado area in meters and calculate the scaling between the real values and the values used in the Colorado Elevation Data set. (To pick a "real" max and min, you can approximate values from a map on the internet).
  • Optional:
    • Use a color scale to display the data
    • Draw a 2d coordinate system around the border of the visualization
    • Display a corresponding color scale next to your image display of elevations and mark elevations on the scale
    • advanced: Display contour lines for the elevation data
    • advanced: Draw a surface of the elevation data

There are more data sets you can try to read in on http://www.idvbook.com/teaching-aid/data-sets. The Data Sets are part of the text book we will be using:

M. Ward, G. Grinstein, D. Keim, “Interactive Data Visualization“, CRC Press, AK Peters, 2nd Edition, 2015.

In more detail, the content of the course will be:

  • Data Visualization: Introduction and Definitions
  • Data Foundations
  • User and Task
  • Visualization Techniques for Spatial Data (especially Volume Vis and Flow Vis), Geospatial Data, Time-Oriented Data, Multivariate Data, Trees and Graphs, Text
  • Interaction
  • Mapping from numbers to visuals
  • Evaluating visualization techniques

There will be a limited number of places in the seminar "Advanced Topics in Vis" for participants of "Interactive Data Vis".