The manner of external representation (or presentation) could affect our way of working with the internal representation (mentally) and our understanding of the information [1
], e.g. in cockpit information displays for aviation [2
], but few results on graphical external representation can be generalised [3
One problem affecting all websites is that there is no reliable, general and abstract method for predicting the effect of presentation rhetorics and modality on understanding of the information. To improve knowledge communication, we should investigate how sensitive people might be to differences in the way we construct our websites. It would be useful to conduct experiments quickly to compare different models of interpretation of information of a specific domain in particular cases. There may be certain styles of presentation or navigation that are generally demanded by users and can either hinder or support users' ability to interpret the information.
Tabular and graphical representations are common in constructing visual arguments [4
] and presenting relational data (especially quantitative data) [5
]. Visualisation of aviation accident events generally use causal trees to represent the causal relations but there are few empirical studies on both preference and perception of causality visualisation. Specifically, we investigate users' preferences for information visualisation styles and their perception of causality as required by aviation accident reporting. As the Web is one of the main channels for publishing information of aviation accidents, it is desirable to know about how people would prefer the causal relations in accident events to be presented in a website and how they perceive this causality. The user preference data are useful in the design and re-design of websites. To elicit preferences from people, we provide multiple designs for selection and study the rationale of their design decisions. Automated website synthesis saves time and effort in building websites for such designs. Few models and theories are available to address computational website design. However, if we view websites as a form of information visualisation, we can borrow some findings from automated diagram design [6
] to serve as our experiment hypotheses. Some systems for automated diagram design have incorporated text to enhance user understanding of graphical visualisation [7
]. This kind of multimodal visualisation should be applicable to website design. Expressiveness and effectiveness of graphical languages as proposed by Mackinlay [8
] have been influential to diagram visualisation models, including source information characteristics [9
], user-defined task specification [10
], and user-defined layout preferences [7
] for automated diagram design.
In general, we would like to see if people would prefer different representations to display the same information. In particular, this study aims to elicit preferences of designers (and users) about visualisation patterns, particularly the preferences for tables and trees in visualising causality information. In this case, we select trees and tables as the options for selection by users. Tree representations are commonly used to graphically represent causality in printed documents. The causal relations are normally represented by arrows or lines connecting causes and effects.
If people do prefer a representation, it would be interesting to see what rationale or criteria contribute to their preferences. We categorised common rationale/criteria mentioned in website design textbooks [11
• easy to learn: the users do not need much time and effort to understand how it works;
• more visual: the users can understand through graphical illustrations;
• more informative: the users can know more details;
• more scalable: fewer changes are needed to handle more massive information;
• more features represented: less characteristics (important information) are left out;
• more suggestive: the users can understand without much guessing; and
• more flexible: suitable for use in different situations.
As these seven rationales may not cover all possible rationales that are crucial to any particular preference, the experiment participants were asked (unprompted) for their rationale before seeing these seven rationales and then they were asked (prompted) to identify if any of these rationales were similar to their own rationales. They were also asked if any of their rationales was not covered by these seven rationales.
Software designs should reduce users' cognitive load [13
]. We hypothesise that participants prefer one design to other designs partially because the preferred design suits their cognitive abilities. If this is true, the cognitive abilities of the participants should be related to their preferences. The relationships among preferences of trees or tables, the cognitive test results of the participants, and rationale for their preferences were studied in this experiment. As it is impossible to test numerous cognitive factors in a single experiment, the participants were only tested on cognitive styles/abilities of visualisation and analogy-making, which we guessed were related to visual representations.
The main objectives of this experiment are as follows:
• To see if there is any different preference for tables or trees in representing the given information;
• To see if different preferences are based on different priority in criteria/rationale;
• To see if the preferences are related to the cognitive test results; and
• To see if the importance ratings of design criteria/rationale are related to cognitive test results.