Helen C. Purchase

Which Aesthetic has the Greatest Effect on Human Understanding

In the creation of graph drawing algorithms and systems, designers claim that by producing layouts that optimise certain aesthetic qualities, the graphs are easier to understand. Such aesthetics include maximise symmetry, minimise edge crosses and minimise bends.

Cognitive measurements of graph aesthetics

A large class of diagrams can be informally characterized as node–link diagrams. Typically nodes represent entities, and links represent relationships between them. The discipline of graph drawing is concerned with methods for drawing abstract versions of such diagrams. At the foundation of the discipline are a set of graph aesthetics (rules for graph layout) that, it is assumed, will produce graphs that can be clearly understood. Examples of aesthetics include minimizing edge crossings and minimizing the sum of the lengths of the edges. However, with a few notable exceptions, these aesthetics are taken as axiomatic, and have not been empirically tested. We argue that human pattern perception can tell us much that is relevant to the study of graph aesthetics including providing a more detailed understanding of aesthetics and suggesting new ones. In particular, we find the importance of good continuity (ie keeping multi-edge paths as straight as possible) has been neglected. We introduce a methodology for evaluating the cognitive cost of graph aesthetics and we apply it to the task of finding the shortest paths in spring layout graphs. The results suggest that after the length of the path the two most important factors are continuity and edge crossings, and we provide cognitive cost estimates for these parameters. Another important factor is the number of branches emanating from nodes on the path.

Multidimensional tactons for non-visual information presentation in mobile devices

Tactons are structured vibrotactile messages which can be used for non-visual information presentation when visual displays are limited, unavailable or inappropriate, such as in mobile phones and other mobile devices. Little is yet known about how to design them effectively. Previous studies have investigated the perception of Tactons which encode two dimensions of information using two different vibrotactile parameters (rhythm and roughness) and found recognition rates of around 70. When more dimensions of information are required it may be necessary to extend the parameter-space of these Tactons. Therefore this study investigates recognition rates for Tactons which encode a third dimension of information using spatial location. The results show that identification rate for three-parameter Tactons is just 48, but that this can be increased to 81 by reducing the number of values of one of the parameters. These results will aid designers to select suitable Tactons for use when designing mobile displays.

Validating Graph Drawing Aesthetics

Designers of graph drawing algorithms and systems claim to illuminate application data by producing layouts that optimize measurable aesthetic qualities. Examples of these aesthetics include symmetry (where possible, a symmetrical view of the graph should be displayed), minimize edge crossings (the number of edge crossings in the display should be minimized), and minimize bends (the total number of bends in polyline edges should be minimized). The aim of this paper is to describe our work to validate these claims by performing empirical studies of human understanding of graphs drawn using various layout aesthetics. This work is important since it helps indicate to algorithm and system designers what are the aesthetic qualities most important to aid understanding, and consequently to build more effective systems.

Metrics for graph drawing aesthetics

Graph layout algorithms typically conform to one or more aesthetic criteria (e.g. minimizing the number of bends, maximizing othrogonality). Determining the extent to which a graph drawing conforms to an aesthetic criterion tends to be done informally, and varies between different algorithms. This paper presents formal metrics for measuring the aesthetic presence in a graph drawing for seven common aesthetic criteria, applicable to any graph drawing of anysize. The metrics are useful for determining the aesthetic quality of a given graph drawing, or for defining a cost function for genetic algorithms or simulated annealing programs. The metrics are continous, so that aesthetic quality is not stated as a binary conformance decision (i.e. the drawing either conforms to the aesthetic or not), but can be stated as the extent of aesthetic conformance using a number between 0 and 1. The paper presents the seven metric formulae. The application of these metrics is demonstrated through the aesthetic analysis of example graph drawings produced by common layout algorithms.

Empirical Evaluation of Aesthetics-based Graph Layout

Many automatic graph layout algorithms have been designed and implemented to display relational data in a graphical (usually node-arc) manner. The success of these algorithms is typically measured by their computational efficiency and the extent to which they conform to aesthetic criteria (for example, minimising the number of crossings, maximising symmetry). Little research has been performed on the usability aspects of such algorithms: do they produce graph drawings that make the embodied information easy to use and understand? Is the computational effort expended on conforming to the assumed aesthetic criteria justifiable with respect to better usability? This paper reports on usability studies that were performed to investigate the merit of automatic graph layout algorithms with respect to human use. The paper describes three ways in which this issue has been considered experimentally: first, investigating individual aesthetic criteria in simple, abstract graph structures; second, investigating the results of common automatic graph layout algorithms; and third, investigating individual aesthetic criteria and other relevant secondary notations in Unified Modeling Language class and collaboration diagrams. The results show that the use of only some aesthetics affect usability significantly, and that the semantic domain of the graph drawings affects which aesthetic criteria need to be emphasised.

Animation, Small Multiples, and the Effect of Mental Map Preservation in Dynamic Graphs

In this paper, we present the results of a human-computer interaction experiment that compared the performance of the animation of dynamic graphs to the presentation of small multiples and the effect that mental map preservation had on the two conditions. Questions used in the experiment were selected to test both local and global properties of graph evolution over time. The data sets used in this experiment were derived from standard benchmark data sets of the information visualization community. We found that small multiples gave significantly faster performance than animation overall and for each of our five graph comprehension tasks. In addition, small multiples had significantly more errors than animation for the tasks of determining sets of nodes or edges added to the graph during the same timeslice, although a positive time-error correlation coefficient suggests that, in this case, faster responses did not lead to more errors. This result suggests that, for these two tasks, animation is preferable if accuracy is more important than speed. Preserving the mental map under either the animation or the small multiples condition had little influence in terms of error rate and response time.

Effective information visualisation: a study of graph drawing aesthetics and algorithms

Abstract Information visualisation systems which generate diagrams representing discrete relational information must consider potential users if they are to be effective. Many algorithms which render an abstract graph structure as a diagram are valued for their conformance to aesthetic criteria (e.g. reducing the number of edge crossings, maximising symmetry), or for computational efficiency. They are not usually judged on their ability to produce diagrams that maximise human performance. This paper presents the results of experiments investigating the relative worth (from an HCI point of view) of graph drawing aesthetics and algorithms using a single graph. The results indicate that while some individual aesthetics affect human performance, it is difficult to say that one algorithm is ‘better’ than another from a relational understanding point of view. Designers of automatic layout algorithms, and the systems which embody such algorithms, can benefit from this study and this human-centred approach, by adapting their methods to focus on user concerns, rather than computational ones.

PeerWise: students sharing their multiple choice questions

PeerWise is a system in which students create multiple choice questions and answer those created by their peers. In this paper, we report on some quantitative results which suggest that students who use PeerWise actively perform better in final examinations than students who are not active. We note a significant correlation between performance in written (not just multiple choice) questions and PeerWise activity, suggesting that active use of the system may contribute to deep (and not just drill-and-practise) learning.

An experimental study of the basis for graph drawing algorithms

Designers of graph drawing algorithms and systems claim to illuminate application data by producing layouts that optimise measurable aesthetic qualities. Examples of these aesthetics include symmetry (where possible, a symmetrical view of the graph should be displayed), minimise arc crossing(the number of arc crossings in the display should be minimised), and minimise bends (the total number of bends in polyline arcs should be minimised). The aim of this paper is to describe our work to validate these claims by performing empirical studies of human understanding of graphs drawn using various layout aesthetics. This work is important since it helps indicate to algorithm and system designers what are the aesthetic qualities most important to aid understanding, and consequently to build more effective systems.