The goal of the research described in this paper is to develop an application-independent presentation tool that automatically designs effective graphical presentations (such as bar charts, scatter plots, and connected graphs) of relational information. Two problems are raised by this goal: The codifi-cation of graphic design criteria in a form that can be used by the presentation tool, and the generation of a wide variety of designs so that the presentation tool can accommodate a wide variety of information. The approach described in this paper is based on the view that graphical presentations are sentences of graphical languages. The graphic design issues are codified as expressiveness and effectiveness criteria for graphical languages. Expressiveness criteria determine whether a graphical language can express the desired information. Effectiveness criteria determine whether a graphical language exploits the capabilities of the output medium and the human visual system. A wide variety of designs can be systematically generated by using a composition algebra that composes a small set of primitive graphical languages. Artificial intelligence techniques are used to implement a prototype presentation tool called APT (A Presentation Tool), which is based on the composition algebra and the graphic design criteria.

We present a study of complex visualization usage by expert meteorological forecasters. We performed a protocol analysis and examined the types of visualizations they examined. We present evidence for how experts are able to make use of complex visualizations. Our #ndings suggest that users of complex visualizations create qualitativemental models from which they can then generate quantitative information. In order to build their qualitative mental models, forecasters integrated information across multiple visualizations and extracted primarily qualitative information from visualizations in a goal-directed manner. We discuss both theoretical and practical implications of this study. Introduction Everywhere you look, newspapers and banners declare this the #Information Age." Scientists, engineers, and weather forecasters #just to name a few# examine extremely large amounts of data on a daily basis. The visualizations that they examine have so much data that it is obvious that...

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Understanding perception is critical to effective visualization design. With its low cost and scalability, crowdsourcing presents an attractive option for evaluating the large design space of visualizations; however, it first requires validation. In this paper, we assess the viability of Amazon’s Mechanical Turk as a platform for graphical perception experiments. We replicate previous studies of spatial encoding and luminance contrast and compare our results. We also conduct new experiments on rectangular area perception (as in treemaps or cartograms) and on chart size and gridline spacing. Our results demonstrate that crowdsourced perception experiments are viable and contribute new insights for visualization design. Lastly, we report cost and performance data from our experiments and distill recommendations for the design of crowdsourced studies. ACM Classification: H5.2 [Information interfaces and presentation]:

We introduce a network visualization technique that supports an analytical method applied in the social sciences. Policy network analysis is an approach to study policy making structures, processes, and outcomes, thereby concentrating on relations between policy actors. An important operational concept for the analysis of policy networks is the notion of centrality, i.e., the distinction of actors according to their importance in a relational structure. We integrate this measure in a layout model for networks by mapping structural to geometric centrality. Thus, centrality values and network data can be presented simultaneously and explored interactively.

Graphics and text have to be well integrated in order to achieve their full potential. A picture shows but a text describes. In a statistical re- port, graphics show the data that is analyzed in the text. This paper describes a system, called PostGraphe, which generates a report integrating graphics and text from a single set of writer's intentions. The system is given the data in tabular form as might be found in a spreadsheet; also input is a declaration of the types of values in the columns of the table. The user chooses the inten- tions to be conveyed in the graphics (e.g. compare two variables, show the evolution of a set of variables ...) and the system generates a report in LATEX with the appropriate PostScript graphic files.

Examining data using graphical tools, such as histograms, quantile plots, scatterplots and the like, is a necessary part of any serious analysis effort. With the advent of inexpensive graphics-capable desktop computing, such tools are generally available. But the use of computers enables more than simply reproducing static plots on a display; it allows users to interact with plots, changing parameters, querying, zooming and linking plots together so that interesting features of one plot can be seen in the light of the others. In this paper we discuss the core features of interactive graphics, investigate how familiar plots can be made interactive and show examples of interactive graphics for general and specific data analysis.

We report an investigation into the processes involved in a common graph reading task using two types of Cartesian graph. We describe an experiment and eye movement study, the results of which show that optimal scan paths assumed in the task analysis approximate the detailed sequences of saccades made by individuals. The research demonstrates the computational inequivalence of two sets of informationally equivalent graphs and illustrates how the computational advantages of a representation outweigh factors such as user unfamiliarity. We describe two models using the ACT rational perceptual motor (ACT-R/PM) cognitive architecture, that replicate the pattern of observed response latencies and the complex scan paths revealed by the eye movement study. Finally, we outline three guidelines for designers of visual displays: Designers should (a) consider how different quantities are encoded within any chosen representational format (b) consider the full range of alternative varieties of a given task, and (c) balance the cost of familiarization with the computational advantages of less familiar representations. Actual or potential applications of this research include informing the design and selection of appropriate visual displays and illustrating the practice and utility of task analysis, eye tracking, and cognitive modeling for understanding interactive tasks with external representations.

A method of statistical graphics consists of two parts: a selection of statistical information to be displayed and a selection of a visual display method to encode the information. Some display methods lead to efficient, accurate visual decoding of encoded information, and others lead to inefficient, inaccurate decoding. It is onlythrough rigorous studies of visual decoding that informed judgments can be made about how to chose display methods. A model has been developed to provide a framework for the study of visual decoding. The model consists of three parts: (1) a two-way classification of information on displays --- quantitative-scale, quantitative-physical, categoricalscale, and categorical-physical; (2) a division of the visual processing of graphical displays into pattern perception and table look-up; (3) a specification of visual operations that are employed to carry out pattern perception and table look-up. Display methods are assessed bystudying the visual operations to which...

this article because I think this is an area rich with statistical applications. There is a great opportunity here! Within Bell Laboratories, I [Mark] have seen several Internet-, or more broadly network-related projects spring up. The second Internet-related article comes from Wolfgang Hardle, Sigbert Klinke and Steve Marron. It is about the use of Internet-enabled applications for the teaching of statistics. These authors establish criteria for effective web-based teaching and propose an approach (using XploRe) to meet these challenges. This article contrasts nicely with an earlier piece by Deborah Nolan and Duncan Temple Lang on the use of multimedia for statistics education (this Newsletter, Volume 9, Number 1). It is interesting to compare these approaches both in terms of the technology and the underlying pedagogy. Wolfgang, Sigbert and Steve offer us several well-presented examples of how the connection between Java and XploRe has produced a rich environment for teaching. With this issue of the Newsletter, we are pleased to introduce Graham Wills as a regular contributor. In his first column, Graham reviews some basics of linked data views. His involvement in the development of several such applications gives him a great perspective to comment on this type of interactivity. Please join us in welcoming Graham to the Newsletter staff! Other items of interest in this edition include the latest column by Andreas Buja, Editor of the Journal of Computational and Graphical Statistics (JCGS). Andreas has a lot of great news to report about JCGS: Submissions are up and the journal is growing! Dan Carr and Ru Sun discuss an alternative to standard Trellis displays, involving layering and perceptual grouping. For the latest in Section news, turn to page 33 where you will re...