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.

The field of information retrieval has traditionally focused on textbases consisting of titles and abstracts. As a consequence, many underlying assumptions must be altered for retrieval from full-length text collections. This paper argues for making use of text structure when retrieving from full text documents, and presents a visualization paradigm, called TileBars, that demonstrates the usefulness of explicit term distribution information in Boolean-type queries. TileBars simultaneously and compactly indicate relative document length, query term frequency, and query term distribution. The patterns in a column of TileBars can be quickly scanned and deciphered, aiding users in making judgments about the potential relevance of the retrieved documents. KEYWORDS: Information retrieval, Full-length text, Visualization. INTRODUCTION Information access systems have traditionally focused on retrieval of documents consisting of titles and abstracts. As a consequence, the underlying assumpt...

In the last several years, large multi-dimensional databases have become common in a variety of applications such as data warehousing and scientific computing. Analysis and exploration tasks place significant demands on the interfaces to these databases. Because of the size of the data sets, dense graphical representations are more effective for exploration than spreadsheets and charts. Furthermore, because of the exploratory nature of the analysis, it must be possible for the analysts to change visualizations rapidly as they pursue a cycle involving first hypothesis and then experimentation.

We discuss external and internal graphical and linguistic representational systems. We argue that a cognitive theory of peoples' reasoning performance must account for (a) the logical equivalence of inferences expressed in graphical and linguistic form; and (b) the implementational differences that affect facility of inference. Our theory proposes that graphical representations limit abstraction and thereby aid processibility. We discuss the ideas of specificity and abstraction, and their cognitive relevance. Empirical support comes from tasks involving (i) the manipulation of external graphics; and (ii) no external graphics. For (i), we take Euler's Circles, provide a novel computational reconstruction, show how it captures abstractions, and contrast it with earlier construals, and with Mental Models' representations. We demonstrate equivalence of the graphical Euler system, and the non-graphical Mental Models system. For (ii), we discuss text comprehension, and the mental ...

A bewildering variety of devices for communication from humans to computers now exists on the market. In order to make sense of this variety, and to aid in the design of new input devices, we propose a framework for describing and analyzing input devices. Following Mackinlay’s semantic analysis of the design space for graphical presentations, our goal is to provide tools for the generation and test of input device designs. The descriptive tools we have created allow us to describe the semantics of a device and measure its expressiveness. Using these tools, we have built a taxonomy of input devices that goes beyond earlier taxonomies of Buxton & Baecker and Foley, Wallace, & Chan. In this paper, we build on these descriptive tools, and proceed to the use of human performance theories and data for evaluation of the efleciiveness of points in this design space. We focus on two figures of merit, footprint and bandwidth, to illustrate this evaluation. The result is the systematic integration of methods for both generating and testing the design space of input devices.

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this paper, we describe the approach to visual display and manipulation of databases that we have been investigating at the University of Toronto for the past few years. We present an overview and retrospective of the G

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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.

We introduce a system that helps users construct interactive visualizations with constant information density. This work is an extension of the DataSplash database visualization environment. DataSplash is a direct manipulation system in which users can construct and navigate visualizations. Objects' appearances change as users zoom closer to or further away from the visualization. Users specify graphically the point at which these changes occur. Our experience with DataSplash indicates that users find it difficult to construct visualizations that display an appropriate amount of detail. In this paper, we introduce an extension to DataSplash based on the Principle of Constant Information Density. This extension gives users feedback about the density of visualizations as they create them. We also introduce an extension that suggests improvements to existing visualizations. We have performed an informal study of user navigation in applications with and without constant information density. We suggest that designers take density into account when designing applications to avoid biasing user navigation in unexpected ways.