Objectives and outcomes
Students are taught the possibilities and importance of data visualisation. They are ready to use
visualisation for the purpose of presenting arbitrary data, for the purpose of data analysis and visual data
mining with the aim of synthesising new knowledge. They are able to use the R language, JavaScript and
alternative open-source solutions for visualisation purposes.
Lectures
Visual data mining. Examples of visual data mining. Outliers, patterns, trends. Basics of creating
presentation graphics using R, a standard and a powerful tool for various visualisation applications.
Visualisation with JavaScript. Other open-source solutions. Detailed and complete code
examples for line and column graphics, for population pyramids, Lorenz curves, box plots, scatter plots,
time series, radial polygons, Gantt charts, heat maps, bump mapping, mosaic and balloon graphics,
cartograms, chord diagrams, as well as a series of different types of thematic graphics which can be
created using R’s basic graphic system. Social network visualisation. Social network parameters. Gephi
– open-source software.
Practical classes
In R and other tools, students visualise the obtained data, as well as the data they scrape themselves.
They compare the results and assess their usability.