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Information Visualisation, 2009 13th International Conference

Date 15-17 July 2009

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Displaying Results 1 - 25 of 113
  • [Front cover]

    Page(s): C1
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  • [Title page i]

    Page(s): i
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  • [Title page iii]

    Page(s): iii
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  • [Copyright notice]

    Page(s): iv
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  • Table of contents

    Page(s): v - xi
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  • Preface

    Page(s): xii
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  • Acknowledgments

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  • Organizing and Liaison Program Committee

    Page(s): xiv - xvi
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  • International Committee

    Page(s): xvii
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  • list-reviewer

    Page(s): xviii
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  • Visual Perception of Parallel Coordinate Visualizations

    Page(s): 3 - 9
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2655 KB) |  | HTML iconHTML  

    Parallel coordinates is a visualization technique that provides an unbiased representation of high-dimensional data. The parallel configuration of axes treats data dimensions uniformly and is well suited for exploratory visualization. However, first-time users of parallel coordinate visualizations can find the representation confusing and difficult to understand.We used eye tracking to study how parallel coordinate visualizations are perceived, and compared the results to the optimal visual scan path required to complete the tasks. The results indicate that even first-time users quickly learn how to use parallel coordinate visualizations, pay attention to the correct task-specific areas in the visualization, and become rapidly proficient with it. View full abstract»

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  • VioNeS - Visual Support for the Analysis of the Next Sub-volume Method

    Page(s): 10 - 17
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (803 KB) |  | HTML iconHTML  

    Computational simulation is an established method to gain insight into cellular processes. As the resulting data sets are usually large and complex, visualization can play a significant role in data analysis. In this paper, we focus on the visualization of simulation output from the next sub-volume method, a spatial simulation algorithm. In addition to the spatial context of the simulation output, its heterogeneous data types, multiple variables, and the temporal context make high demands on the visualization. To cope with these challenging characteristics, we systematically explore possible visualization concepts with respect to these characteristics. From these findings, we derive our specific solution to visualize the data from the next sub-volume method, using a framework of multiple coordinated views that emphasize the spatial context of the data. Combining these views with a highly interactive user interface, the user is able to adapt the visualization to his current analysis goals and explore the data in its complexity. View full abstract»

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  • A Framework to Analyze Information Visualization Based on the Functional Data Model

    Page(s): 18 - 24
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1032 KB) |  | HTML iconHTML  

    We propose a framework for analyzing information visualization (infovis) based on the concept of functional dependency (FD). Although functional dependencies express important semantic information of data, they are rarely taken into account by general purpose infovis tools-- a fact that may cause problems in the visualization process. The main idea of our approach is to use the concept of FD for modeling the invariant structures of all three components of information visualization that is data, visual representations, and visual mappings. View full abstract»

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  • Many-to-Many Relational Parallel Coordinates Displays

    Page(s): 25 - 31
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3128 KB) |  | HTML iconHTML  

    An interesting property of the commonly used parallel coordinates display is the distinct overall pattern formed by the totality of lines between adjacent axes. These patterns have a direct correspondence to the type of relationship existing between the variables mapped onto the axes in question as well as a salient visual appearance. Parallel coordinates displays can therefore be used to visually investigate relationships between variables as well as investigating individual objects/lines. The problem with this approach is that, whereas each object is mapped in its entirety in a standard parallel coordinates display, only a small subset of the interrelations between variables is shown as the number of variables increase. To show all possible relations between variables multiple parallel coordinates displays are needed. In turn this means that each variable is duplicated several times, once per extra parallel coordinates display. To a viewer this increases the visual complexity and most probably the mental load. To aid users we have devised a new configuration of the axes in multiple parallel coordinates displays. Through an experiment we have also started to investigate the usability of this new configuration and the results are promising. View full abstract»

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  • HexBoard: Conveying Pairwise Similarity in an Incremental Visualization Space

    Page(s): 32 - 37
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (560 KB) |  | HTML iconHTML  

    We introduce the HexBoard space and visualization tool, that provides an incremental visualization space that conveys pairwise similarity among all neighboring elements from a dynamic data set. It is a significant evolution on our previous work, incBoard, a chess board analogy for displaying (projecting) objects from a dynamic set on a 2D space, considering their similarity in a higher dimensional space. HexBoard relays on hexagons to represent data items: the only regular polygons that provide a regular tessellation of the Euclidean plane and where neighboring elements always share an edge. These edges are then easily manipulated to convey pairwise similarity information, thus overcoming a serious limitation of the previous solution, while preserving all advantages of incBoard (no occlusion, coherent disposition of elements, inherently incremental solution and low computational cost). This paper introduces HexBoard, discusses its potential and illustrates its application with examples. View full abstract»

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  • An Occlusion-Reduced 3D Hierarchical Data Visualization Technique

    Page(s): 38 - 43
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1371 KB) |  | HTML iconHTML  

    Occlusion is an important problem to be solved for readability improvement of 3D visualization techniques. This paper presents an occlusion reduction technique for cityscape-style 3D visualization techniques. The paper first presents an algorithm for occlusion reduction. It generates bounding boxes of 3D objects on the 2D display space, moves them to reduce their overlap, and finally reversely projects their movements onto the 3D space. The paper then presents an application of the algorithm to our own hierarchical data visualization technique, and a music browser based on the technique. The paper also shows several numerical evaluations that denote the effectiveness of the presented technique. View full abstract»

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  • Hierarchical Temporal Patterns and Interactive Aggregated Views for Pixel-Based Visualizations

    Page(s): 44 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (386 KB) |  | HTML iconHTML  

    Many real-world problems involve time-oriented data. Time data is different from other kinds of data--explicitly harnessing the structures of time in visualizations can guide and support userspsila visual analysis processes. State-of-the-art visualizations hardly take advantage of the structures of time to aid users in understanding and exploring the data. To bring more flexibility to the analysis process, we have developed interactive visual methods incorporating the structures of time within a pixel-based visualization called GROOVE (granular overview overlay). GROOVE uses different techniques to visualize time-oriented data by overlaying several time granularities in one visualization and provides interactive operators, which utilize the structures of time in different ways to capture and explore time-oriented data. View full abstract»

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  • BIIGLE Tools – A Web 2.0 Approach for Visual Bioimage Database Mining

    Page(s): 51 - 56
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (840 KB) |  | HTML iconHTML  

    In this paper we want to discuss the usage of Web 2.0 techniques to realize information visualization based exploration and annotation of huge volume, semi-structured data, and in particular high throughput bioimage series. To this end, we developed a toolbox for a graphical representation of different displays in a browser context which can be used for image database exploration in a link & brush fashion. The Web based approach proved to be capable of information visualization tasks and supports collaboration of several users at arbitrary locations. View full abstract»

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  • Spatial Visualisation of Conceptual Data

    Page(s): 57 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (853 KB) |  | HTML iconHTML  

    Numerous data mining methods have been designed to help extract relevant and significant information from large datasets. Computing concept lattices allows clustering data according to their common features and making all relationships between them explicit. However, the size of such lattices increases exponentially with the volume of data and its number of dimensions. This paper proposes to use spatial pixel-oriented and tree-based visualisations of these conceptual structures in order to optimally exploit their expressivity. View full abstract»

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  • Visual Graph Comparison

    Page(s): 62 - 67
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1224 KB) |  | HTML iconHTML  

    Researchers and analysts in many fields are sometimes confronted with the task of comparing and contrasting two similar but different graphs or networks. This paper presents a technique and prototype tool to support the visual comparison of graphs and the interactive reconciliation of candidate graphs into a single reference graph. Given two input graphs and a set of similarities between nodes, the Semantic Graph Visualiser (SGV) computes a merged graph and allows the analyst to visually compare and contrast the two input graphs. In a specific example, given two differing models of essentially the same business process derived from different sources, a process engineer can visually compare them and reconcile them into a single reference model. View full abstract»

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  • Algebraic Guide Generation

    Page(s): 68 - 73
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (299 KB) |  | HTML iconHTML  

    Suitable reference marks are an important part of creating an understandable visualization. The reference marks create the frame in which the data is understood, thereby preserving the context of the data and allowing the transition from data to information to be made. However, reference marks (including legends, axial and point labels) are given insufficient attention in many visualization frameworks. When explicitly present, they often require completely separate specification from the visualization for which they are a reference. This paper presents a framework independent method for deriving reference marks from the data analysis pathway. We also describe how this approach has been implemented in the Stencil library, and how it may be implemented in other libraries. View full abstract»

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  • Probabilistic NeuroScale for Uncertainty Visualisation

    Page(s): 74 - 79
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (231 KB) |  | HTML iconHTML  

    This paper is a study of low dimensional visualisation methods for data visualisation under uncertainty of the input data. It focuses on NeuroScale, the feed-forward neural networks algorithm by trying to make the algorithm able to accommodate the uncertainty. The standard model is shown not to work well under high levels of noise within the data and need to be modified. The modifications of the model are verified by using synthetic data to show their ability to accommodate the noise. View full abstract»

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  • A Visualization and Level-of-Detail Control Technique for Large Scale Time Series Data

    Page(s): 80 - 85
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2609 KB) |  | HTML iconHTML  

    We have various interesting time series data in our daily life, such as weather data (e.g., temperature and air pressure)and stock prices. Polyline chart is one of the most common ways to represent such time series data. We often draw multiple polylines in one space to compare the time variation of multiple values. However, it is often difficult to read the values if the number of polylines gets larger. This paper presents a technique for visualization and level-of-detail control of large number of time series data. The technique generates clusters of time series values,and selects representative values for each cluster, as a preprocessing. The technique then draws the representative values as polylines. It also provides a user interface so that users can interactively select interesting representatives,and explore the time series values which belong to the clusters of the representatives. View full abstract»

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  • Visualising the Query Space of the Image Collection

    Page(s): 86 - 91
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2733 KB) |  | HTML iconHTML  

    In this paper, we propose an information visualisation solution for multimedia retrieval based on semantic concepts defined in an image database. The proposed visualisation approach utilises concept map, Venn diagram and Fisheye distortion to enable effective and efficient visualisation of image database. In addition, the proposed approach enables displaying the local and global views of the collection subset, selected as relevant by the user. The proposed solution is evaluated on Corel 700 dataset with 10 semantic concepts for the following user actions: exploratory browsing, querying and detecting patterns. View full abstract»

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  • A Linking Mechanism to Integrate Components of a Visualization Framework

    Page(s): 92 - 97
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (517 KB) |  | HTML iconHTML  

    Visual analysis and exploration of data has been extensively studied in various fields. As the amount of data increases, we need scalable and efficient visualization tools integrated with cross-discipline elements to explore and overcome the issues exposed by the large data sets. In this paper, we present our dynamic linking mechanism to create a visualization framework (mVis, multi-visualizer for multi-dimensional data) for visual exploration of large relational data sets. It is an extendable, flexible, and easy-to-use environment. The linking mechanism links co-operating components and data-connected interactive visualizers to the framework. It constitutes object-and event-linkers which are identified by their names so that new external components can subscribe to any linker group easily without compiling the framework. View full abstract»

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