The final step to address RQ1 and complete the component of the framework is translating the descriptions of the visual encodings into specifiable properties and combine them with the visual composition methods. This is done by decomposing encodings into layers that are described by a conditioning variable, a composition method and a set of visual mappings, including layout and shape. The aim of using the layers is to enable rearrangement of visual encodings based on the use of conditioning variables and the sets of visual mappings. The combination of layers and composition methods describe complete visualisation techniques; from this, common layers can be found among techniques and rearranged with the framework, enabling a navigation of the resulting design space and exploration of different perspectives on datasets.
alternate dimension
point bar spine ellipse
cartesian coordinates
polar cordinates
polygon
Fig. 5.7 Shapes supported in the framework. An attribute is mapped to height and width, respectively, for bars and spines in cartesian coordinates; although the spine shape occupies a larger area, this dimension is not conveying information. The concentric circles in the polar row indicates the radial subdivisions of the available area. The third row represents the use of a variable in a different orientation for polar coordinates. For example, the bar shape is displayed in the second row with a variable assigned to angle, configuring an annular sector, whereas in the third row it is assigned to radius. The same applies for spine: in the second row, the angular spines configure circular sectors, whereas in the third row the concentric circles are space-filling in the radius dimension.
Some decompositions are straightforward to extract based on the publication where the visualisation was described; sometimes, however, the visualisation source does not include details about the construction of the encoding or the original description needs to be adapted. In such cases, the following method is used to decompose encodings from the mappings descriptions into layered specifications:
1. For each variable that is assigned to at least one positional channel, assign one of the layout cases;
2. For each variable assigned to a shape, mark as a conditioning variable and assign a layer number;
3. For each attribute variable listed under another variable type, assign the same layer number. This covers every case of encoding except 2D combinations of two attribute variables, such as some scatterplots;
4. For each variable with layout case n-to-2, assign the same layer number. This covers spiral layouts, in which more than one time variable is used for two positional channels;
5. For every layer after the first, assign a composition method between juxtaposition, superimposition and nesting;
This method results in multi-layered visualisations, where each layer corresponds to a 1D partition of space by identifiers, space or time or a 2D combination of any two variables.
Example Table 5.2 contains an example of applying this method to the Kalei-
domaps (Bale et al., 2007) technique. The technique uses polar coordinates to display
instant time. The space is partitioned along the angular dimension for different identi-
fier variables corresponding to a measurement; each sector is then partitioned based
on a combination of two time variables and coloured based on the value of that mea- surement (attribute). Each non-attribute variable is mapped to at least one positional channel (alternating between angle and radius) – they are assigned a 1-to-1 layout case. As the use of space is space-filling for each variable, they are assigned a spine shape. Following the method described, the non-attributes variables are marked as a conditioning variable and a layer number is assigned to them. The attribute variable is assigned to the last temporal variable as it is used to colour the last layer with a spine. Finally, each layer is composed using nesting. The visualisation is displayed in fig. 5.8;
the first two layers are displayed in the black-and-white figure, reproduced from the source publication.
Mappings:
Variable Layout C S P x/θ y/r Shape Case Cond.
Identifier SCALE ´ ´ ´ ✓ - SPINE 1-to-1 ✓
Time 1 SCALE ´ ´ ´ ✓ - SPINE 1-to-1 ✓
Time 2 SCALE ´ ´ ´ - ✓ SPINE 1-to-1 ✓
Attribute SCALE ✓ ´ ´ - - - - -
Layers:
Layer Conditioning Variable
Comp Method C S P x/θ y/r Layout Shape
1 Identifier ´ ´ ´ - I - SCALE SPINE
2 Time 1 nesting ´ ´ - T1 - SCALE SPINE
3 Time 1 nesting A ´ - T2 - SCALE SPINE
Table 5.2 Description of visual mappings of Kaleidomaps. Abbreviations: Colour, Size,
Path. The double column borders in the layers table indicate the separation between
the framework’s components, as conditioning variable and composition method are part of the composition component. The composition signature for this visualisation is the following: N ((I,L1),N ((T,L2),(T,L3))).
5.4.1
Visual mappings
Considering the method described and including the properties defined by the compo- sition component, each layer contains the following set of properties:
Conditioning variable any variable, or a list of variables for special layout cases
(see below for spiral example);
Composition method juxtaposition, superimposition or nesting; Shape POINT, BAR, SPINE, ELLIPSE or other polygon shapes;
Fig. 5.8 Layers of Kaleidomaps reproduced from Bale et al. (2007). In the original article, the combination of the two temporal variables (middle) is described as a 2D partition; in the framework, separating the two time variables enables different arrangements between layers. The figure on the right is the final visualisation.
Layout SCALE for default transformations, any ALGORITHM which is supported
by the implementation, or other keywords that define a layout, such as SPIRAL. Unless specified, the layout choice affects both positional axes;
Colour and/or Opacity any variable;
Size 1 and Size 2 any variable, assigned to the first (width or angle) and/or second
(height or radius) axis;
Path any variable;
Position 1 and Position 2 any variable, assigned to the first (horizontal or angle)
and/or second (vertical or radius) axis, or a list of variables for special layout cases (see below for spiral example);