The specifications described in this section fit into two parts of Card-Norman’s model: the description of the operands in the interaction cycle and the visual mappings step of moving from data abstractions to visual structures. This involves the use of six properties related to the resulting visual marks: colour, size (width or angle) and
size (height or radius), connecting path, position (x or theta) and position (y or r), layout and shape. In addition to the low level description of encodings, the
conditioning variable and composition methods defined in the previous chapter are also used for a complete specification of a visualisation technique.
In the same vein as the operations that were suggested in the previous chapter to manipulate the composition grammar, the following operations should be used to assign and modify the visual mappings:
• Assign a variable or value to a property; • Modify or remove a variable assignment; • Modify the coordinate system, when possible;
5.8
Discussion
There are several points of discussion regarding this component. The first important one is the order in which variables are used to describe the hierarchical levels. The
Kaleidomaps example showed how a different ordering may be used to achieve the same
result. For visual exploration, this is a very important factor as it affects the paths that can be taken when navigating between visualisations. The method described in this chapter to convert a visualisation into the framework’s descriptions assumes a
priority for identifier variables, followed by time, space and lastly other attributes. This
order is justified by the fact that the framework deals with time-oriented visualisations, where spatial, quantitative or qualitative attributes are associated with recorded times. In practical use, this may not always be the case; however, it is a characteristic or limitation of the framework that must be considered when using it.
A second point of discussion is the number of channels that were included in this research. As a result of the survey, in addition to positional variables, three other channels were used: size, path and colour. However, other channels could also be used as discussed by Aigner et al. (2011): thickness of lines, texture, glyphs, text annotations, containment or orientation/angle in cartesian coordinates. Some of these were not included as they did not emerge during the survey, such as orientation/angle. Others, such as thickness of line, could be applied to various aspects of visualisations, such as thickness of the lines in visual marks or in connecting paths. In this case, several other attributes could also be used: for example, dotted or dashed lines. Although the framework is fully compatible with their inclusion in the future, the decision was, at this stage of the thesis to limit the number of attributes in the view component and focus first on a complete framework.
The relationship between layouts, position and size is also open to discussion. The design choice for the component was to allow low level, domain-independent views to be defined. This means that, at the point of computing certain layouts, the data points for each variable have already been transformed as needed. At the same time, there are layouts that use the results of algorithms or calculations as an important step. One example is the MDS algorithm used in Time Curves, which generates 2D positions from a correlation matrix. In the framework, the MDS positions are the data variables that are mapped to the positional channels; the framework does not make a particular distinction between positions produced by the MDS algorithm or geographic coordinates. On the other hand, visualisations such as ThemeDelta are defined by
using an algorithm as a layout; this decision was done with basis on the inputs and outputs of algorithms; in the case of ThemeDelta, the algorithm does not take any special data as input, unlike the correlation matrix used for the MDS.
Another point of discussion is the use of the basic layers with scale and algorithms, in contrast with predefined visualisations. Some visual exploration systems such as Tableau use predefined visualisations such as stacked bar charts and maps, still allowing a degree of reconfiguration. On the other hand, grammars such as Vega-Lite include properties that allow defining a stacked bar chart as an extension of a normal bar chart; the same method works for area and stacked area charts. In yet another extreme are specific design space for families of visualisations, such as the design space by Baudel and Broeskema (2012) for treemaps.
The approach taken in the framework makes the description of views compatible with
transitioning between configurations in the design space of hierarchical time-oriented
visualisations. The argument presented in this thesis is that a flexible approach is more important for researching time-oriented visualisations than a rigid one; this is due to the fact that the primary aim of a design space is to enumerate the universe of
design choices (Schulz et al., 2011), even if some design choices are ineffective for a
range of tasks. The relative independence of each component also allows visualisation researchers and designers to choose which parts of the framework are needed for their applications or experiments.
5.9
Chapter summary
This chapter introduced a decomposed view of visual encodings that addresses two secondary questions, what are the interactive visualisation methods used for temporal
data? and how can hierarchical composition techniques be combined with the surveyed visualisations? The specifications of encodings as layers is presented as a component of
the framework that addresses the primary research question. The combination of this component with the composition component presented in the previous section allows the specification and reconfiguration of hierarchical visualisation techniques. Although there are temporal aspects in the definition of the compositions and encodings through the use of temporal variables, the aspects of time that characterise the exploration of time-oriented data are yet to be addressed. The next chapter addresses the third
secondary question and completes the framework by extending the reconfiguration of visualisation to time-based transformations.
Transformation: interactions
This chapter introduces the remaining component of the framework, the Transformation component, which contains the conceptual transformations of the temporal domain that enable the interactive visual exploration. While previous chapters were concerned with the parts of the framework that connect time-oriented visualisation with hierarchical and composite visualisations, this chapter aims at answering the third secondary question — what are the temporal interactions that facilitate exploring temporal data
in hierarchical visualisations? As described in chapter 3, the transformations are
designed based on a combination of analysis of the interactions in time-oriented data visualisations and the use of conceptual models of temporal data. This chapter details the process that leads to the different categories of transformations and their application as functions with distinct parameters.
6.1
Addressing the research questions
This chapter addresses primarily the third secondary question. The aim of this chapter is to introduce conceptual transformations of the time domain that can be applied to the other components, enabling the use of multiple perspectives for temporal data exploration. In order to do that, the chapter relates the existing literature of time-oriented data visualisation with concepts of temporal data. The description of the transformations and their interactions with the other components, besides being presented as a contribution and answer to research question, also addresses the gap identified in chapter 2, where it was identified that current models and frameworks
for time-oriented data visualisation fail to include the time domain in the interactions supported by these models.