A space efficient clustered visualization of large graphs

This paper proposes a new technique for visualizing large graphs of several ten thousands of vertices and edges. To achieve the graph abstraction, a hierarchical clustered graph is extracted from a general large graph based on the community structures which are discovered in the graph. An enclosure geometrical partitioning algorithm is then applied to achieve the space optimization. For graph drawing, we technically use the combination of a spring-embbeder algorithm and circular drawings that archives the goal of optimization of display space and aesthetical niceness. We also discuss an associated interaction mechanism accompanied with the layout solution. Our interaction not only allows users to navigate hierarchically up and down through the entire clustered graph, but also provides a way to navigate multiple clusters concurrently. Animation is also implemented to preserve users' mental maps during the interaction. © 2007 IEEE

A visualization approach for frauds detection in financial market

The traditional solutions to the stock market security are not sufficient in identifying attackers and further attack plans from the analysis of existing events. Therefore, it is difficult for analysts to prevent future unexpected events or frauds by only monitoring the realtime trading information. The event-driven fraud detection in financial market could not help analysts to find attack plans and the further intention of attackers. This paper proposed a new framework of visual analytics for stock market security. The proposed solution consists of two stages: 1) Visual Surveillance of Market Performance, and 2) Behavior-Driven Visual Analysis of Trading Networks. In the first stage, we use a 3D treemap to monitor the realtime stock market performance and to identify a particular stock that produced an unusual trading pattern. We then move to the next stage: social network visualization to conduct behavior-driven visual analysis of suspected pattern. Through the visual analysis of social (or trading) network, analysts may finally identify the attackers (the sources of the fraud), and further attack plans. © 2009 IEEE

Space-efficient visualisation of large hierarchies

University of Technology, Sydney. Faculty of Information Technology.Relational information visualisation concerns viewing relational data, where the underlying data model is a graph. Hierarchical visualisation is one of hot topics in graph visualisation in which the data is organised in a hierarchical structure. As the amount of information, that we want to visualise, becomes larger and the relations become more complex, classical visualisation techniques and hierarchical drawing methods tend to be inadequate.Traditional hierarchical visualisation algorithms are more concerned with the readability of the layouts. They usually do not consider the efficient utilisation of the geometrical plane for the drawings. Therefore, for most hierarchical layouts, a large portion of display space is wasted as background. The aim of this research is to investigate a space-efficient approach to handle the visualisation of large hierarchies in two-dimensional spaces. This thesis introduces a new graph visualisation approach called enclosure+ connection for visualizing large hierarchies. This approach maximises the space utilisation by taking advantages of the traditional enclosure partitioning approach, while it retains the display of a traditional node-link diagram to hopefully provide users a direct perception of relational structures. The main contribution of this thesis is layout and navigation algorithms for visualising large hierarchies. Two layout algorithms, the space-optimised tree and the EncCon tree, have been developed to achieve the space-efficient visualisation. Both algorithms use the enclosure concept to define layout of hierarchies, which ensure the efficient utilisation of display space. Two focus+context navigation and interaction methods have been proposed to cooperate with the visualization of large hierarchies. Several advanced computer graphics approaches, such as graphic distortion and transparency, are used for the development of these navigation methods. Two case studies have been implemented to evaluate the layout algorithms and the associated navigation methods. The first case study is an application of a shared collaborative workspace which aims to provide users with a better assistance for visual manipulation and navigation of knowledge-based information. The second case study is a visual browser for navigating large-scale online product catalogues. Although the case studies have provided some useful evaluation, formal usability studies would be required to justify fully the effectiveness of these layout and navigation methods. Although this task has not carried out in this research, the author has presented his usability study's plan as a future work

Visualization of large citation networks with space-efficient multi-layer optimization

This paper describes a technique for visualizing large citation networks (or bibliography networks) using a space-efficient multi-layer optimization visualization, technique. Our technique first use a fast clustering algorithm to discover community structure in the bibliographic networks. The clustering process partitions an entire network into relevant abstract subgroups so that the visualization, can provide a clearer and less density of display of global view of the complete graph of citations. We next use a new space-efficient visualization algorithm to archive the optimization of graph layout within the limited display space so that our technique can theoretically handle a very large bibliography network with several thousands of elements. Our technique also employs rich graphics to enhance the attributed property of the visualization including publication years and number of citations. Finally, the system provides an interaction technique in cooperating with the layout to allow users to navigate through the citation network. Animation is also implemented to preserve the users' mental maps during the interaction

Enabling effective tree exploration using visual cues

© 2018 Elsevier Ltd This article presents a new interactive visualization for exploring large hierarchical structures by providing visual cues on a node link tree visualization. Our technique provides topological previews of hidden substructures with three types of visual cues including simple cues, tree cues and treemap cues. We demonstrate the visual cues on Degree-of-Interest Tree (DOITree) due to its familiar mapping, its capability of providing multiple focused nodes, and its dynamic rescaling of substructures to fit the available space. We conducted a usability study with 28 participants that measured completion time and accuracy across five different topology search tasks. The simple cues had the fastest completion time across three of the node identification tasks. The treemap cues had the highest rate of correct answers on four of the five tasks, although only reaching statistical significance for two of these. As predicted, user ratings demonstrated a preference for the easy to understand tree cues followed by the simple cue, despite this not consistently reflected in performance results

Advanced Proof Viewing in ProofTool

Sequent calculus is widely used for formalizing proofs. However, due to the proliferation of data, understanding the proofs of even simple mathematical arguments soon becomes impossible. Graphical user interfaces help in this matter, but since they normally utilize Gentzen's original notation, some of the problems persist. In this paper, we introduce a number of criteria for proof visualization which we have found out to be crucial for analyzing proofs. We then evaluate recent developments in tree visualization with regard to these criteria and propose the Sunburst Tree layout as a complement to the traditional tree structure. This layout constructs inferences as concentric circle arcs around the root inference, allowing the user to focus on the proof's structural content. Finally, we describe its integration into ProofTool and explain how it interacts with the Gentzen layout.Comment: In Proceedings UITP 2014, arXiv:1410.785

Highlighting in information visualization: A survey

Highlighting was the basic viewing control mechanism in computer graphics and visualization to guide users' attention in reading diagrams, images, graphs and digital texts. As the rapid growth of theory and practice in information visualization, highlighting has extended its role that acts as not only a viewing control, but also an interaction control and a graphic recommendation mechanism in knowledge visualization and visual analytics. In this work, we attempt to give a formal summarization and classification of the existing highlighting methods and techniques that can be applied in Information Visualization, Visual Analytics and Knowledge Visualization. We propose a new three-layer model of highlighting. We discuss the responsibilities of each layer in the different stage of the visual information processing. © 2010 IEEE

A survey of multiple tree visualisation.

This paper summarises the state-of-the-art in multiple tree visualisations. It discusses the spectrum of current representation techniques used on single trees, pairs of trees and finally multiple trees, in order to identify which representations are best suited to particular tasks and to find gaps in the representation space where opportunities for future multiple tree visualisation research may exist. The application areas from where multiple tree data are derived are enumerated, and the distinct structures that multiple trees make in combination with each other and the effect on subsequent approaches to their visualisation are discussed, along with the basic high-level goals of existing multiple tree visualisations

Explorative Graph Visualization

Netzwerkstrukturen (Graphen) sind heutzutage weit verbreitet. Ihre Untersuchung dient dazu, ein besseres Verständnis ihrer Struktur und der durch sie modellierten realen Aspekte zu gewinnen. Die Exploration solcher Netzwerke wird zumeist mit Visualisierungstechniken unterstützt. Ziel dieser Arbeit ist es, einen Überblick über die Probleme dieser Visualisierungen zu geben und konkrete Lösungsansätze aufzuzeigen. Dabei werden neue Visualisierungstechniken eingeführt, um den Nutzen der geführten Diskussion für die explorative Graphvisualisierung am konkreten Beispiel zu belegen.Network structures (graphs) have become a natural part of everyday life and their analysis helps to gain an understanding of their inherent structure and the real-world aspects thereby expressed. The exploration of graphs is largely supported and driven by visual means. The aim of this thesis is to give a comprehensive view on the problems associated with these visual means and to detail concrete solution approaches for them. Concrete visualization techniques are introduced to underline the value of this comprehensive discussion for supporting explorative graph visualization