# 1.4.2. Presentation of Thematic Data

As you have seen in chapter Thematic Map Types there are two different thematic map types: qualitative and quantitative.

Qualitative maps contain, as the name indicates, qualitative features. Qualitative feature describe types, kinds or properties of spatial data. They are of a nominal scaling whereas the ordering of data is based on equality or inequality between groups. Thus rivers can be distinguished from roads, deserts from forests, etc. Qualitative data can be visualised by point, line or area symbols, whereas points are normally represented by point symbols, lines by line symbols and areas by area symbols. (Asche et al. 2002) Symbolisation for qualitative maps (Asche et al. 2002)

Quantitative maps contain quantitative attributes which relate to the values, magnitudes or intensities of numerical data which are expressed in a numerical form e.g. the number of inhabitants of individual settlements (Asche et al. 2002). Quantitative data can either be absolute (e.g. inhabitants of a commune) or relative (e.g. population density of a commune). The decision on how to visualise quantitative data, depends on several aspects as you can see in the following illustration: From data to a thematic map (Hurni et al. 2005)

First of all we have to decide whether to visualise one attribute, such as inhabitants of a commune, or several attributes, such as inhabitants of a commune subdivided into male and female. If we visualise only one attribute we have to find out whether the attribute is relative or absolute.
The following paragraphs explain in a few words the representation types that may be used to visualise the data.

#### Continuous Representation of Data Amounts

 Criteria for this representation type: Representation of integer, positive and negative numbers, including zero Representation of decimal numbers Maps with continuous representation of data amounts portray correct data relations, because each measured value is visualised.

There exist several methods to visualise a continuous representation of data amounts. Three of them are presented next:

Method Example

Choropleth Map
The exact object values are visualised (e.g. colored or shaded) directly in the map. Even little value differences are visible.

• The exact value can be read out of the map
• Exact placing to its correct location

• Difficulty to compare the values with the naked eye
• Impossible to design value overlapping Exact values are visualised in the map (Allen et al. 2001)

Proportional Symbol
A symbol is defined whose area size is directly proportional to the value dimension.

• Slower growing of the symbol dimension by increasing value.
• Exact placing to its correct location

• Poor accuracy of value estimation
• Difficulty to design symbol overlapping One symbol is defined whose size is variable (Allen et al. 2001)

Repeated Symbol
One unit is defined with whom all other values can be represented. The repetition of the unit makes the dimension of the values visible.

• Quick and easy overview
• Countability of the represented values

• Difficult to show a wide value range
• The impression of over-simplification One unit is defined to visualise all values (Institut für Länderkunde 2000)

As you can see in the presented maps, there may occur a few problems using the continuous representation of data amounts in screen maps because this representation type needs a lot of space.

#### Representation with Intervals

 Criteria for this representation type: Representation of integer, positive and negative numbers, including zero Representation of decimal numbers Classification of data values (building intervals) Classification of data leads to a loss of detail because the exact numercial data relations are not visible anymore. (The theory of how to classify data is explained in the next chapter.)

The representation with intervals can be used for relative and absolute attributes:

Attribute Type Representation Type Example

Relative

Choropleth Map

• Phenomenon is spread evenly and continuously over the area
• Density change occurs at boundaries

• Boundaries may suggest that densities change abruptly at the lines
• Densities are not uniform throughout any statistical unit Interactive choropleth map (Schnabel 2008)

Absolute

Graduated range of geometric / pictorial symbols or characters

• Avoids overcrowding
• Number of symbols can be adjusted to cover a certain value range
• Small symbols can mark large values

• Symbols do not express exact values Representation with geometric symbols, reproduced with the permission of swisstopo (JD072706) Representation with pictorial symbols, reproduced with the permission of swisstopo (JD072706) Representation with characters, reproduced with the permission of swisstopo (JD072706)

Absolute

Flow Chart (for directional topics)

• Show movements and transportations and their direction
• Start and end point of the movements are important and not their location

• Need quite a lof of space

#### Representation with Diagrams

There is a huge amount of diagram types than can be used for the visualisation of thematic data. We will only introduce the most popular ones. If you want to get familiar with other diagram types have a look at the pdf file "Diagram Types" (in german).

The most important diagrams within the field of cartography are the following:

(Divided) Wing Chart Advantages:
• absolute totals depicted by wing area
• null sets can be represented easily
• estimation and measuring is generally less accurate

(Divided) Bar Chart Advantages:
• quick and easy overview of the represented value percentages
• null sets can be represented easily
• estimation and measuring is generally less accurate

Area Chart Advantages:
• space-saving and great centring
• absolute totals depicted by quadrat area
• representation of individual component values by quadrat segments
• takes up a lot of space when showing large values

Pie Chart Advantages:
• space-saving and great centring
• absolute totals depicted by circle area
• representation of individual component values by circle segments
• representation of component percentages by segment angles