Applied Computing

Data Visualisations

Data visualisation results from using software functions and techniques to access and select data from large data repositories, and then present that data in graphical form. This can be in the form of graphs and histograms, charts and maps, or spatial relationship diagrams and network diagrams. This type of graphic representation helps the viewer to identify patterns and relationships in vast amounts of data that would not be identifiable in the raw data. Data visualisations can be still (static) or moving, or updated regularly or in real time (dynamic).

→Information visualisation deals more with ideas and concepts.
→Data visualisation offers a graphic representation of complex data sets.

Purposes of data visualisations

There are many purposes for a data visualisation. A successful chart could satisfy many needs by simultaneously:

→educating to develop understanding

→entertaining to amuse and distract or provoke a response

→informing to convey information

→persuading to encourage adoption of a point of view or opinion.

Explanatory

An explanatory data visualisation sets out to explain a point of view. Features of this type of

visualisation are that it is:

→clearly expressed

→simply laid out

→based on known facts.

Exploratory

Exploratory visualisations allow users to select a value or category to explore connections and relationships. An example is shown in Figure below, which is an on-screen interactive visualisation of student progress and results. The relationships between submitted work, progress and grades for the entire class group can be combined onto one screen. The hover tooltip reveals further details on each record. As further records are added, the display is recalculated and updated.

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