Information visualizations must allow users to browse information spaces and focus quickly on items of interest. Being able to see some representation of the entire information space provides an initial gestalt overview and gives context to support browsing and search tasks. However, the limited number of pixels on the screen constrain the information bandwidth and make it difficult to completely display large information spaces. The Information Mural is a two-dimensional, reduced representation of an entire information space that fits entirely within a display window or screen. The mural creates a miniature version of the information space using visual attributes such as grayscale shading, intensity, color, and pixel size, along with anti-aliased compression techniques. Information Murals can be used as stand-alone visualizations or in global navigational views. We have built several prototypes to demonstrate the use of Information Murals in visualization applications; subject matter ...

Structural comparison of large trees is a difficult task that is only partially supported by current visualization techniques, which are mainly designed for browsing. We present TreeJuxtaposer, a system designed to support the comparison task for large trees of several hundred thousand nodes. We introduce the idea of “guaranteed visibility”, where highlighted areas are treated as landmarks that must remain visually apparent at all times. We propose a new methodology for detailed structural comparison between two trees and provide a new nearly-linear algorithm for computing the best corresponding node from one tree to another. In addition, we present a new rectilinear Focus+Context technique for navigation that is well suited to the dynamic linking of side-by-side views while guaranteeing landmark visibility and constant frame rates. These three contributions result in a system delivering a fluid exploration experience that scales both in the size of the dataset and the number of pixels in the display. We have based the design decisions for our system on the needs of a target audience of biologists who must understand the structural details of many phylogenetic, or evolutionary, trees. Our tool is also useful in many other application domains where tree comparison is needed, ranging from network management to call graph optimization to genealogy.

Multiple coordinated visualizations enable users to rapidly explore complex information. However, users often need unforeseen combinations of coordinated visualizations that are appropriate for their data. Snap-Together Visualization enables data users to rapidly and dynamically mix and match visualizations and coordinations to construct custom exploration interfaces without programming. Snap's conceptual model is based on the relational database model. Users load relations into visualizations then coordinate them based on the relational joins between them. Users can create different types of coordinations such as: brushing, drill down, overview and detail view, and synchronized scrolling. Visualization developers can make their independent visualizations snap-able with a simple API. Evaluation of Snap revealed benefits, cognitive issues, and usability concerns. Data savvy users were very capable and thrilled to rapidly construct powerful coordinated visualizations. A snapped overview...

Visualization of high-dimensional, large data sets, resulting from computational simulation, is one of the most challenging fields in scientific viualization. When visualization aims at supporting the analysis of such data sets, feature-based approches are very useful to reduce the amount of data which is shown at each instance of time and guide the user to the most interesting areas of the data. When using feature-based visualization, one of the most difficult questions is how to extract or specify the features. This is mostly done (semi-)automatic up to now. Especially when interactive analysis of the data is the main goal of the visualization, tools supporting interactive specification of features are needed. In this paper we present a framework for flexible and interactive specification of high-dimensional and/or complex features in simulation data. The framework makes use of multiple, linked views from information as well as scientific visualization and is based on a simple and compact feature definition language (FDL). It allows the definition of one or several features, which can be complex and/or hierarchically described by brushing multiple dimensions (using non-binary and composite brushes). The result of the specification is linked to all views, thereby a focus+context style of visualization in 3D is realized. To demonstrate the usage of the specification, as well as the linked tools, applications from flow simulation in the automotive industry are presented. 1.

Visage is a prototype user interface environment for exploring and analyzing information. It represents an approach to coordinating multiple visualizations, analysis and presentation tools in data-intensive domains. Visage is based on an Information-centric approach to user interface design which strives to eliminate impediments to direct user access to information objects across applications and visualizations. Visage consists of a set of data manipulation operations, an intelligent system for generating a wide variety of data visualizations (SAGE) and a briefing tool that supports the conversion of visual displays used during exploration into interactive presentation slides. This paper presents the user interface components and styles of interaction central to Visage's information-centric approach. Keywords: Visualization, exploratory data analysis, graphics, user interface environment, human-computer interaction 1. Introduction There has been a great deal of research recently on ...

This paper is aimed at the exploratory visualization of networks where there is a strength or weight associated with each link, and makes use of any hierarchy present on the nodes to aid the investigation of large networks. It describes a method of placing nodes on the plane that gives meaning to their relative positions. The paper discusses how linking and interaction principles aid the user in the exploration. Two examples are given; one of electronic mail communication over eight months within a department, another concerned with changes to a large section of a computer program. I. THE PROBLEM It has almost become a clichŽ to start a paper with the observation that the amount of data in the world is growing rapidly, and that current efforts to extract useful information from data lag far behind the ability to create data. However the clichŽ is true, and no less so in the field of network analysis and visualization than in any other. In many areas, scientists are realizing that the tools they have been using are limited in utility when applied to large, information-rich networks. Not only are networks of interest large in terms of size (as measured by number of nodes or links between nodes), but also in terms of the data collected for each node or link. The ability to examine statistics on the nodes and relate them to the network is of crucial importance. Examples of areas in which the analysis of large networks is important include: i. Trade flows. The concern in this area is monitoring imports and exports of various products at several levels; international, interstate and local. Besides examining many types of trade goods, there is also strong interest in spotting temporal patterns. ii. Communication networks. This is an important and wide category, covering not only telecommunication networks, but also electronic mail (email), financial transaction, ATM/bank data transferal and other data distribution networks.

We describe a system, called GPL, that implements a language for quantitative graphics. The structure of this system differs from existing statistical graphics, visualization, and mapping systems. Instead of treating a graphics display as a viewer for underlying data, GPL treats data as an accessory to viewing a graph. GPL is based on the mathematical definition of the graph of a function and uses that definition to organize data linked to the graph. To be published in Journal of Computational and Graphical Statistics. GPL has been renamed nViZn

Information has become interactive. Information visualization is the design and creation of interactive graphic depictions of information by combining principles in the disciplines of graphic design, cognitive science, and interactive computer graphics. As the volume and complexity of the data increases, users require more powerful visualization tools that allow them to more effectively explore large abstract datasets. This

In this paper, we develop an approach to the process of constructing knowledge through structured exploration of large spatiotemporal data sets. We begin by introducing our problem context and defining both Geographic Visualization (GVis) and Knowledge Discovery in Databases (KDD), the source domains for methods being integrated. Next, we review and compare recent GVis and KDD developments and consider the potential for their integration, emphasizing that an iterative process with user interaction is a central focus for uncovering interesting and meaningful patterns through each. We then introduce an approach to design of an integrated GVis-KDD environment directed to exploration and discovery in the context of spatiotemporal environmental data. The approach emphasizes a matching of GVis and KDD meta-operations. Following description of the GVis and KDD methods that are linked in our prototype system, we present a demonstration of the prototype applied to a typical spatiotemporal datas...

This paper presents the Snap user interface and basic conceptual model and then reports on two studies on constructing and operating coordinated visualizations