Graph layout for applications in compiler construction

We address graph visualization from the viewpoint of compiler construction. Most data structures in compilers are large, dense graphs such as annotated control flow graph, syntax trees, dependency graphs. Our main focus is the animation and interactive exploration of these graphs. Fast layout heuristics and powerful browsing methods are needed. We give a survey of layout heuristics for general directed and undirected graphs and present the browsing facilities that help to manage large structured graph

A proposal from the point of view of information visualization and human computer interaction for the visualization of distributed system load

In this article we show how the design of interfaces for the visualization of distributed system load can benefit from the combination of concepts and techniques from Information Visualization and Human Computer Interaction (HCI). Every distributed systems administrator must handle a high volume of information and the exploration and analysis of this data set has become increasingly difficult. We propose how to visualize the parameters involved in the load of a distributed system to obtain an effective visualization tool in order to reduce the user cognitive workload and help the user make the right decisions in a productive way.Facultad de Informátic

Graph layout for applications in compiler construction

We address graph visualization from the viewpoint of compiler construction. Most data structures in compilers are large, dense graphs such as annotated control flow graph, syntax trees, dependency graphs. Our main focus is the animation and interactive exploration of these graphs. Fast layout heuristics and powerful browsing methods are needed. We give a survey of layout heuristics for general directed and undirected graphs and present the browsing facilities that help to manage large structured graph

A Pattern Approach to Examine the Design Space of Spatiotemporal Visualization

Pattern language has been widely used in the development of visualization systems. This dissertation applies a pattern language approach to explore the design space of spatiotemporal visualization. The study provides a framework for both designers and novices to communicate, develop, evaluate, and share spatiotemporal visualization design on an abstract level. The touchstone of the work is a pattern language consisting of fifteen design patterns and four categories. In order to validate the design patterns, the researcher created two visualization systems with this framework in mind. The first system displayed the daily routine of human beings via a polygon-based visualization. The second system showed the spatiotemporal patterns of co-occurring hashtags with a spiral map, sunburst diagram, and small multiples. The evaluation results demonstrated the effectiveness of the proposed design patterns to guide design thinking and create novel visualization practices

Large Graph Analysis in the GMine System

Current applications have produced graphs on the order of hundreds of thousands of nodes and millions of edges. To take advantage of such graphs, one must be able to find patterns, outliers and communities. These tasks are better performed in an interactive environment, where human expertise can guide the process. For large graphs, though, there are some challenges: the excessive processing requirements are prohibitive, and drawing hundred-thousand nodes results in cluttered images hard to comprehend. To cope with these problems, we propose an innovative framework suited for any kind of tree-like graph visual design. GMine integrates (a) a representation for graphs organized as hierarchies of partitions - the concepts of SuperGraph and Graph-Tree; and (b) a graph summarization methodology - CEPS. Our graph representation deals with the problem of tracing the connection aspects of a graph hierarchy with sub linear complexity, allowing one to grasp the neighborhood of a single node or of a group of nodes in a single click. As a proof of concept, the visual environment of GMine is instantiated as a system in which large graphs can be investigated globally and locally

Distributed system load visualization

In this article we show how the interface design for the visualization of distributed system load can benefit from the combination of concepts and techniques from Information Visualization and Human Computer Interaction (HCI). The use of visual representations and interactions to accelerate the insight into complex data is what distinguishes visual analytic software form other types of analytical tools. Visual representations translate data into a visible form that highlights important data features, including commonalities and anomalies. These visual representations helps the users to quickly perceive salient aspects of their data. Every distributed systems administrator must handle a high volume of information and the exploration and analysis of this data is becoming increasingly difficult. We propose an entirely novel approach to visualize the parameters involved in the system load for a distributed system to obtain an effective visualization tool in order to reduce the user cognitive workload and help the user to make the right decisions in a productive way.IV Workshop de Computación Gráfica, Imágenes y Visualización (WCGIV)Red de Universidades con Carreras en Informática (RedUNCI

An integrated visual framework for the human-Web interface

© 2002 IEEE. The design of Web sites has been largely ad hoc, with little concern about the effectiveness of navigation and maintenance. This paper presents a general framework with a human-Web interface that supports Web design through visual programming and reverse Web engineering through visualization. The paper describes the framework in the context of a Web tool, known as HWIT which has been developed for a pilot study

Information visualization for DNA microarray data analysis: A critical review

Graphical representation may provide effective means of making sense of the complexity and sheer volume of data produced by DNA microarray experiments that monitor the expression patterns of thousands of genes simultaneously. The ability to use ldquoabstractrdquo graphical representation to draw attention to areas of interest, and more in-depth visualizations to answer focused questions, would enable biologists to move from a large amount of data to particular records they are interested in, and therefore, gain deeper insights in understanding the microarray experiment results. This paper starts by providing some background knowledge of microarray experiments, and then, explains how graphical representation can be applied in general to this problem domain, followed by exploring the role of visualization in gene expression data analysis. Having set the problem scene, the paper then examines various multivariate data visualization techniques that have been applied to microarray data analysis. These techniques are critically reviewed so that the strengths and weaknesses of each technique can be tabulated. Finally, several key problem areas as well as possible solutions to them are discussed as being a source for future work