Information Visualization Of An Agent-Based Financial System Model

This paper considers the application of information visualization techniques to an agent-based model of a financial system. The minority game is a simple agent-based model which can be used to simulate the events in a real-world financial market. To aid understanding of this model, we can apply information visualization techniques. Treemap and sunburst are two such information visualization techniques, which previous research tells us can effectively represent information similar to that generated by the minority game. Another information visualization technique, called logical fisheye-lens, can be used to augment treemap and sunburst, allowing users to magnify areas of interest in these visualizations. In this paper, treemap and sunburst, both with and without fisheye-lens, are applied to the minority game, and their effectiveness is evaluated. This evaluation is carried out through an analysis of users performing various tasks on (simulated) financial market data using the visualization techniques. A subjective questionnaire is also used to measure the users’ impressions of the visualization techniques.Dynamic Models, Minority Game, Visualization

A usability study on the use of multi-context visualization

Graph visualization has been widely used in real-world applications, as it provides better presentation of overall data structure. However, there are navigation problems existing in deep and large relational datasets. To address these challenges, a new technique called multi-context visualization, which provides users with rich contextual information, has been proposed as the solution to the navigation in large scale datasets. This paper evaluates the multi-context visualization by conducting an experiment-based user study. To answer whether the more contextual information positively assist in making more accurate and easier decisions, it aims to evaluate the effectiveness and efficiency of the multi-context visualization, by measuring the user performance. Specifically, this usability test was designed to test if the use of multiple context views can improve navigation problems for deep and large relational data sets. © 2008 IEEE

RICHIE: A Step-by-step Navigation Widget to Enhance Broad Hierarchy Exploration on Handheld Tactile Devices

International audienceExploring large hierarchies is still a challenging task, especially for handheld tactile devices, due to the lack of visualization space and finger's occlusion. In this paper, we propose the RICHIE (Radial In-Cremental HIerarchy Exploration) tool, a new radial widget that allows step-by-step navigation through large hierarchies. We designed it to fit handheld tactile requirements such as target reaching and space optimization. Depth exploration is made by shifting two levels of hierarchy at the same time, for reducing the screen occupation. This widget was implemented in order to adapt a Command and Control (C2) system to mobile tactile devices, as these systems require the on-screen presence of an important unit's hierarchy (the ORder of BATtle). Nevertheless, we are convinced that RICHIE could be used on several systems that require hierarchical data exploration, such as phylogenetic trees or file browsing

Interactive Visualisation of Hierarchical Quantitative Data: An Evaluation

We have compared three common visualisations for hierarchical quantitative data, treemaps, icicle plots and sunburst charts as well as a semicircular variant of sunburst charts we call the sundown chart. In a pilot study, we found that the sunburst chart was least preferred. In a controlled study with 12 participants, we compared treemaps, icicle plots and sundown charts. Treemap was the least preferred and had a slower performance on a basic navigation task and slower performance and accuracy in hierarchy understanding tasks. The icicle plot and sundown chart had similar performance with slight user preference for the icicle plot.Comment: Presented at IEEE VIS 2019 in Vancouver, Canada and included in the VIS 2019 conference proceedings. Improved the image quality in the pape

Data Exploration Interface for Digital Forensics

The fast capacity growth of cheap storage devices presents an ever-growing problem of scale for digital forensic investigations. One aspect of scale problem in the forensic process is the need for new approaches to visually presenting and analyzing large amounts of data. Current generation of tools universally employ three basic GUI components—trees, tables, and viewers—to present all relevant information. This approach is not scalable as increasing the size of the input data leads to a proportional increase in the amount of data presented to the analyst. We present an alternative approach, which leverages data visualization techniques to provide a more intuitive interface to explore the forensic target. We use tree visualization techniques to give the analyst both a high-level view of the file system and an efficient means to drill down into the details. Further, we provide means to search for keywords and filter the data by time period

Data Exploration Interface for Digital Forensics

The fast capacity growth of cheap storage devices presents an ever-growing problem of scale for digital forensic investigations. One aspect of scale problem in the forensic process is the need for new approaches to visually presenting and analyzing large amounts of data. Current generation of tools universally employ three basic GUI components—trees, tables, and viewers—to present all relevant information. This approach is not scalable as increasing the size of the input data leads to a proportional increase in the amount of data presented to the analyst. We present an alternative approach, which leverages data visualization techniques to provide a more intuitive interface to explore the forensic target. We use tree visualization techniques to give the analyst both a high-level view of the file system and an efficient means to drill down into the details. Further, we provide means to search for keywords and filter the data by time period

Space-filling Techniques in Visualizing Output from Computer Based Economic Models

One important factor concerning economic models is that frequently large amounts of data are produced. There is the research issue of how end-users (who may not be researchers or model developers) can be presented with this data so that maximum benefits can be attained from the data production. The usual approach with economic models is a series of tables or data series plots. In this paper we use space-filling information visualization techniques as an aid to user’s understanding of data from an economic model. Based upon evaluation of the effectiveness of existing treemap and sunburst techniques through user experimentation, we introduce two new space-filling visualization techniques. We also describe fisheye-lens techniques applicable to these new visualizations.User Interfaces, Information visualisation, Minority Game

Visualising Bluetooth interactions: combining the Arc Diagram and DocuBurst techniques

Within the Bluetooth mobile space, overwhelmingly large sets of interaction and encounter data can very quickly be accumulated. This presents a challenge to gaining an understanding and overview of the dataset as a whole. In order to overcome this problem, we have designed a visualisation which provides an informative overview of the dataset. The visualisation combines existing Arc Diagram and DocuBurst techniques into a radial space-filling layout capable of conveying a rich understanding of Bluetooth interaction data, and clearly represents social networks and relationships established among encountered devices. The end result enables a user to visually interpret the relative importance of individual devices encountered, the relationships established between them and the usage of Bluetooth 'friendly names' (or device labels) within the data

Context-Preserving Visual Analytics of Multi-Scale Spatial Aggregation.

Spatial datasets (i.e., location-based social media, crime incident reports, and demographic data) often exhibit varied distribution patterns at multiple spatial scales. Examining these patterns across different scales enhances the understanding from global to local perspectives and offers new insights into the nature of various spatial phenomena. Conventional navigation techniques in such multi-scale data-rich spaces are often inefficient, require users to choose between an overview or detailed information, and do not support identifying spatial patterns at varying scales. In this work, we present a context-preserving visual analytics technique that aggregates spatial datasets into hierarchical clusters and visualizes the multi-scale aggregates in a single visual space. We design a boundary distortion algorithm to minimize the visual clutter caused by overlapping aggregates and explore visual encoding strategies including color, transparency, shading, and shapes, in order to illustrate the hierarchical and statistical patterns of the multi-scale aggregates. We also propose a transparency-based technique that maintains a smooth visual transition as the users navigate across adjacent scales. To further support effective semantic exploration in the multi-scale space, we design a set of text-based encoding and layout methods that draw textual labels along the boundary or filled within the aggregates. The text itself not only summarizes the semantics at each scale, but also indicates the spatial coverage of the aggregates and their hierarchical relationships. We demonstrate the effectiveness of the proposed approaches through real-world application examples and user studies

Interactive metagenomic visualization in a Web browser

<p>Abstract</p> <p>Background</p> <p>A critical output of metagenomic studies is the estimation of abundances of taxonomical or functional groups. The inherent uncertainty in assignments to these groups makes it important to consider both their hierarchical contexts and their prediction confidence. The current tools for visualizing metagenomic data, however, omit or distort quantitative hierarchical relationships and lack the facility for displaying secondary variables.</p> <p>Results</p> <p>Here we present Krona, a new visualization tool that allows intuitive exploration of relative abundances and confidences within the complex hierarchies of metagenomic classifications. Krona combines a variant of radial, space-filling displays with parametric coloring and interactive polar-coordinate zooming. The HTML5 and JavaScript implementation enables fully interactive charts that can be explored with any modern Web browser, without the need for installed software or plug-ins. This Web-based architecture also allows each chart to be an independent document, making them easy to share via e-mail or post to a standard Web server. To illustrate Krona's utility, we describe its application to various metagenomic data sets and its compatibility with popular metagenomic analysis tools.</p> <p>Conclusions</p> <p>Krona is both a powerful metagenomic visualization tool and a demonstration of the potential of HTML5 for highly accessible bioinformatic visualizations. Its rich and interactive displays facilitate more informed interpretations of metagenomic analyses, while its implementation as a browser-based application makes it extremely portable and easily adopted into existing analysis packages. Both the Krona rendering code and conversion tools are freely available under a BSD open-source license, and available from: <url>http://krona.sourceforge.net</url>.</p