This paper presents visualization and layout schemes developed for a novel circular user interface designed for a round, tabletop display. Since all the displayed items are in a polar coordinate system, many interface and visualization schemes must be revisited to account for this new layout of UI elements. We first discuss the direct implications of such a circular interface on document orientation. Then we describe two types of fisheye deformation of the circular layout and explain how to use them in a multiperson collaborative interface. These two schemes provide a general layout framework for circular interfaces. We have also designed a new visualization technique derived from the particularities of the circular layout we have highlighted. In this technique the user control the layout of the elements of a hierarchical tree. Our approach is not to automatically compute the most effective position of the nodes and leaves of a tree but to provide the user rich interaction possibilities to easily and quickly produce a layout comparable to the hyperbolic view developed at Xerox PARC. Finally, we discuss future work and possible visualization techniques based on different information structures.

Software products are often released with missing functionality, errors, or incompatibilities that may result in failures in the field, inferior performances, or, more generally, user dissatisfaction. In previous work, we presented the Gamma technology, which facilitates remote analysis and measurement of deployed software and allows for gathering programexecution data from the field. When monitoring a high number of deployed instances of a software product, however, a large amount of data is collected. Such raw data are useless in the absence of a suitable data-mining and visualization technique that supports exploration and understanding of the data. In this paper, we present a new technique for collecting, storing, and visualizing program-execution data gathered from deployed instances of a software product. We also present a prototype toolset, Gammatella, that implements the technique. We show how the visualization capabilities of Gammatella allows for effectively investigating several kinds of execution-related information in an interactive fashion.

We investigate the use of elastic hierarchies for representing trees, where a single graphical depiction uses a hybrid mixture, or "interleaving", of more basic forms at different nodes of the tree. In particular, we explore combinations of node-link and Treemap forms, to combine the space-efficiency of Treemaps with the structural clarity of node-link diagrams. A taxonomy is developed to characterize the design space of such hybrid combinations. A software prototype is described, which we used to explore various techniques for visualizing, browsing and interacting with elastic hierarchies, such as side-by-side overview and detail views, highlighting and rubber banding across views, visualization of multiple foci, and smooth animations across transitions. The paper concludes with a discussion of the characteristics of elastic hierarchies and suggestions for research on their properties and uses.

Never before in history has data been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data has become increasingly difficult. Information visualization and visual data mining can help to deal with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data mining process. There are a large number of information visualization techniques that have been developed over the last two decades to support the exploration of large data sets. In this star report, we provide an overview of information visualization and visual data mining techniques, and illustrate them using a few examples.

Abstract — Information visualisation is about gaining insight into data through a visual representation. This data is often multivariate and increasingly, the datasets are very large. To help us explore all this data, numerous visualisation applications, both commercial and research prototypes, have been designed using a variety of techniques and algorithms. Whether they are dedicated to geo-spatial data or skewed hierarchical data, most of the visualisations need to adopt strategies for dealing with overcrowded displays, brought about by too much data to fit in too small a display space. This paper analyses a large number of these clutter reduction methods, classifying them both in terms of how they deal with clutter reduction and more importantly, in terms of the benefits and losses. The aim of the resulting taxonomy is to act as a guide to match techniques to problems where different criteria may have different importance, and more importantly as a means to critique and hence develop existing and new techniques.

We propose an approach for complex software analysis based on visualization. Our work is motivated by the fact that in spite of years of research and practice, software development and maintenance are still time and resource consuming, and high-risk activities. The most important reason in our opinion is the complexity of many phenomena related to software, such as its evolution and its reliability. In fact, there is very little theory explaining them. Today, we have a unique opportunity to empirically study these phenomena, thanks to large sets of software data available through open-source programs and open repositories. Automatic analysis techniques, such as statistics and machine learning, are usually limited when studying phenomena with unknown or poorlyunderstood influence factors. We claim that hybrid techniques that combine automatic analysis with human expertise through visualization are excellent alternatives to them. In this paper, we propose a visualization framework that supports quality analysis of large-scale software systems. We circumvent the problem of size by exploiting perception capabilities of the human visual system. Categories and Subject Descriptors D.2.8 [Software Engineering]: Metrics—complexity measures, product metrics; D.1.5 [Programming Techniques]:

We investigate techniques for visualizing time series data and evaluate their effect in value comparison tasks. We compare line charts with horizon graphs — a space-efficient time series visualization technique — across a range of chart sizes, measuring the speed and accuracy of subjects’ estimates of value differences between charts. We identify transition points at which reducing the chart height results in significantly differing drops in estimation accuracy across the compared chart types, and we find optimal positions in the speed-accuracy tradeoff curve at which viewers performed quickly without attendant drops in accuracy. Based on these results, we propose approaches for increasing data density that optimize graphical perception. Author Keywords Visualization, graphical perception, time series, line charts,

As more and more information is available on the Internet, search engines and bookmark tools become very popular. However, most search tools are based on character-level matching without any semantic analysis, and users have to manually organize their bookmarks or favorite collections without any convenient tool to help them identify the subjects of the Web pages. In this paper, we introduce an interactive tool that automatically analyzes, categorizes, and visualizes the semantic relationships of web pages in personal bookmark or favorites collections based on their semantic similarity. Sophisticated data analysis methods are applied to retrieve and analyze the full text of the Web pages. The Web pages are clustered hierarchically based on their semantic similarities . A utility measure is recursively applied to determine the best partitions that are visualized by what we call the Semantic Treemap. Various interaction methods such as scrolling, zooming, expanding, selecting, searching, filtering etc. are provided to facilitate viewing and querying for information. Furthermore, the hierarchical organization as well as the semantic similarities among Web pages can be exported and visualized in a collaborative 3D environment, allowing a group of people to compare and share each other's bookmarks.

This report is broken down into four main sections, firstly giving the primary aims of the proposed research, followed by a review of background reading of present Information Visualisation (IV) techniques, which are categorised using an existing framework. This is followed by a description of the general visualisation problem we are concerned with plus a description of the specific area where such a visualisation could be of benefit. We then discuss the visualisation techniques that address situations that have the greatest similarity to our own problem, and explain why they still lack suitability for our purposes. Then, two prototypes that are under development are described, and the report finishes with a breakdown of proposed future work

Event sequence analysis is an important task in many domains: medical researchers study the patterns of transfers within the hospital for quality control; transportation experts study accident response logs to identify best practices. In most cases they deal with more than thousands of records. While previous research has focused on searching and browsing, overview tasks are often overlooked. We introduce a novel interactive visual overview of event sequences called LifeFlow. LifeFlow scales to any number of records, summarizes all possible sequences, and highlights the temporal spacing of the events within sequences. We conducted two case studies with healthcare and transportation domain experts to illustrate the usefulness of LifeFlow. We also conducted a user study with ten participants which confirmed that after 15 minutes of training novice users were able to rapidly answer questions about the prevalence and temporal characteristics of sequences, find anomalies, and gain significant insight from the data.