The work described in this thesis encompasses a wide span of domains related to data visualisation, ranging from usability studies, HCI theory and visualisation techniques to interface design and implementation issues. There is, therefore, a variety of work which could be pursued to further advance the knowledge and understanding of issues associated with the problems of visualising large information spaces over the small display screen. The following subsections describe some of the major areas of research which could stem from the current work.
Implementation and Evaluation of the lnfoLens
The iterative design of the lnfoLens described in the previous chapter has provided the necessary groundwork for its full implementation. This implementation would then facilitate a thorough evaluation of the system using a variety of spreadsheets, tables and databases with varying attributes, such as size, data types and data structures. User performance on various tasks may also be compared with other display formats and systems, such as the more conventional tables and displays of databases on the computer.
The functionality of the InfoLens may also be integrated as a key component of a database system, supporting a comprehensive range of operations. At a higher level, the database system establishes a permanent linkage with various files with graphical data to support the InfoLens. At a lower level, data, as they are entered and updated, would be automatically converted in various graphical formats to enable the user to undertake the task at hand; in this context, the user could be the viewer of the data, the administrator or the data entry operator.
Comparison and Evaluation of Distortion-Oriented Presentation Techni ques
The underlying difficulty in the selection of distortion-oriented presentation techniques for a particular application is the apparent visual differences between these types of displays. Whilst the taxonomy and conceptual model of distortion-oriented presentation techniques proposed in this thesis have enriched our understanding of these approaches in presenting large information spaces, there is a great need to gather a body
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of empirical data to compare the strengths and weaknesses of these techniques. This would help to make the selection process for an appropriate presentation technique an easier task. It is important to emphasise that in the comparison of these presentation techniques, system parameters should be carefully chosen so that the magnification factors in the in-focus and out-of-focus regions are as closely matched as possible. In order that a richer picture of the evaluation can be gained, a multi-dimensional evaluation approach (Burger & Apperley, 1 99 1 ) is recommended. The empirical knowledge base so generated would help to strengthen the metrication framework proposed and help identify specific application domains for these techniques.
A deeper understanding of the user interaction with these types of interfaces can also be gained by developing detailed cognitive models to account for and predict user behaviour and performance. The cognitive model on user interaction with map-based user interfaces described in this thesis has identified three key constituents: states, processes and resources. Further observational studies on other types of graphical user interfaces would help to extend this model in a number of ways. First, the model could be extended to cover a wider range of graphical user interfaces. Second, the model could be strengthened to account for the full range of interface experience, from original goal formation to system state evaluation. Third, a more elaborate model could facilitate accurate prediction of user performance of a variety of tasks using these graphical user interfaces.
Extending the E3 Framework
The E3 metrication model described in this thesis has provided a useful framework for the user interface designer to make an objective assessment and comparison of various presentation techniques. This framework suggests the information flow starts from the representation of the data to the user in the performance of a particular task. A formal analysis of this information flow using established information theory would help to identify the existence of any bottlenecks which could potentially impede user performance. Research into the amount of textual information to be displayed on the screen suggests there is an optimum information density (Danchak, 1976; NASA 1980). A formal analysis would help to identify an optimal value for the presentation of graphical data
The robustness and usefulness of the E3 metrication model currently relies much on empirical data which provides the knowledge base for expressiveness and effectiveness. The study of the former is typically carried out by psycho-physicists; the latter by user interface evaluators. Recent work on the development of a cognitive model
CHAPTER 7: CONCLUSIONS AND FURTIIER WORK 143 for the understanding graphical perception (Lohse, 1993) would also contribute to the formation of a more robust and versatile metrication model.
Visual Illusion in Data Visualisation
Recent advances in computer graphics technologies have contributed to the development and applications of many sophisticated data visualisation and interaction techniques� These approaches enable complex multi-dimension data to be presented on the display screen and, increasingly, 3D visualisation is common in the presentation of large data sets. Whilst these techniques provide a powerful means of representing and presenting complex data, it should be emphasised that the main aim of data visualisation is data comprehension, enabling the viewer to perform the task at hand.
These visualisation techniques are potentially powerful, as they allow patterns which are inherent in the data set, but which would otherwise remain obscured, to unveil themselves. However, misuse of these techniques may impede data comprehension, and may even lead to misinterpretation of the data. Visual illusions have been a well researched topic in psychology over the past one hundred years. However, their effects on data visualisation in computer applications have been under-explored. Tufte ( 1983) describes the use of illusion in graphical presentations in terms of the lie factor. There is some research evidence to suggest that users perform less effectively with 3D graphics than conventional 2D graphs (Barfield & Robless, 1989; Carswell, Frankenberger & Berhard, 1991). Much further work is needed to develop a set of practical guidelines for user interface designers and practitioners to identify the potential pitfalls in data visualisation.