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Information Visualisation (IV), 2013 17th International Conference

Date 16-18 July 2013

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Displaying Results 1 - 25 of 103
  • [Front cover]

    Publication Year: 2013 , Page(s): C4
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  • [Title page i]

    Publication Year: 2013 , Page(s): i
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  • [Title page iii]

    Publication Year: 2013 , Page(s): iii
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  • [Copyright notice]

    Publication Year: 2013 , Page(s): iv
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  • Table of contents

    Publication Year: 2013 , Page(s): v - xiii
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  • Preface

    Publication Year: 2013 , Page(s): xiv
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  • Acknowledgments

    Publication Year: 2013 , Page(s): xv
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  • Organizing Committee

    Publication Year: 2013 , Page(s): xvi - xx
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  • Program Committee

    Publication Year: 2013 , Page(s): xxi - xxii
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  • Reviewers

    Publication Year: 2013 , Page(s): xxiii - xxiv
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  • Keynotes

    Publication Year: 2013 , Page(s): xxv - xxx
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (457 KB)  

    These keynote speeches discuss the following: Machine Analysis of Facial Behaviour; Visual Analysis of Financial Data; Geovisual Analytics with integrated Storytelling Applied to Business Intelligence; Smart Cities, Real-Time Data, Augmented Reality and the Internet of Things: Towards the Geography of Everything; Automatic Generation of Visualization Like Human's Ones. View full abstract»

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  • D-Art Gallery

    Publication Year: 2013 , Page(s): xxxi - xxxii
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  • A Visual Analytics Tool for System Logs Adopting Variable Recommendation and Feature-Based Filtering

    Publication Year: 2013 , Page(s): 1 - 10
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1932 KB) |  | HTML iconHTML  

    Analysis and monitoring of system logs such as transaction logs and access logs is important for various objectives including trend discovery, update effort determination, and malicious behavior monitoring. However, it is not always an easy task because these logs may be massive, consisting of millions of records containing tens of variables, and therefore it may be difficult or time-consuming to discover significant knowledge. This paper presents a visual analytics tool which enables us to effectively observe system logs. The tool recommends variables that can reveal interesting discoveries and provides feature-based filtering that selects meaningful items from the visualization results. This paper also presents the result of experiments for non-professional users. View full abstract»

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  • Matching Application Requirements with Dynamic Graph Visualization Profiles

    Publication Year: 2013 , Page(s): 11 - 18
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1009 KB) |  | HTML iconHTML  

    Mapping a dynamic graph dataset to an inappropriate visualization leads to a degradation of visualization performance at some task. To tap the full potential of existing dynamic graph visualization techniques, we propose a methodology for matching application requirements with dynamic graph visualization profiles. We target at supporting experts choosing the right visualization technique. Our methodology describes both the application requirements and the visualization techniques as profiles covering important aesthetic criteria for visualizing dynamic graphs. Characteristics of the graph and task are used to derive the application profile. The probably most appropriate visualization technique is the one whose profile matches best the required application profile. We compile exemplary visualization profiles for representatives of dynamic graph visualization approaches and demonstrate the methodology in a case study. View full abstract»

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  • Multivariate Network Exploration with JauntyNets

    Publication Year: 2013 , Page(s): 19 - 27
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1423 KB) |  | HTML iconHTML  

    The amount of data produced in the world every day implies a huge challenge in understanding and extracting knowledge from it. Much of this data is of relational nature, such as social networks, metabolic pathways, or links between software components. Traditionally, those networks are represented as node-link diagrams or matrix representations. They help us to understand the structure (topology) of the relational data. However in many real world data sets, additional (often multidimensional) attributes are attached to the network elements. One challenge is to show these attributes in context of the underlying network topology in order to support the user in further analyses. In this paper, we present a novel approach that extends traditional force-based graph layouts to create an attribute-driven layout. In addition, our prototype implementation supports interactive exploration by introducing clustering and multidimensional scaling into the analysis process. View full abstract»

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  • Edge Bundling by Rapidly-Exploring Random Trees

    Publication Year: 2013 , Page(s): 28 - 35
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1440 KB) |  | HTML iconHTML  

    We introduce a technique for bundling edges in graphs where a hierarchical organization of the vertices is not available. Instead of applying time-complex force-directed edge bundling, we adopt the concept of Rapidly-Exploring Random Trees (RRTs). We use RRTs for fast computation of a hierarchical space organization that is independent of the spatial structure of the graph layout. Due to this independency, edge bundling can be applied to any graph layout and even allows us to define spatial obstacles through which no bundles may lead. Furthermore, when adding or removing graph nodes and edges on-the-fly, the bundling structure remains stable, which cannot be guaranteed for force-directed bundling. The main benefit of RRT bundling is its high efficiency, supporting interactive exploration. We rely on the low runtime complexity for a new interaction technique for visual clutter reduction in node-link diagrams that we refer to as the RRT edge bundling lens. View full abstract»

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  • Force-Directed Parallel Coordinates

    Publication Year: 2013 , Page(s): 36 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1493 KB) |  | HTML iconHTML  

    Parallel coordinates are a well-known and valuable technique for the analysis and visualization of high dimensional data sets. However, while Inselberg emphasizes that the strength of parallel coordinates as a methodology is rooted in exploration and interactivity, the set of interaction techniques is currently limited. Axes can be re-ordered and brushing (simple, angular or multi-dimensional) can be performed. In this paper, we propose a force-directed algorithm and related interaction techniques to support the exploration of parallel coordinate plots through a physical metaphor. Our parallel-coordinates visualization offers novel user interaction beyond the standard techniques by allowing the user to rotate the axis according to forcedirected polylines. The new interaction provides the user with a more immersive experience for data exploration that results in greater intuition of the data, especially in cases where many polylines overlap. We demonstrate our approach, then present the results of a qualitative evaluation of the system. View full abstract»

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  • Prefix Tag Clouds

    Publication Year: 2013 , Page(s): 45 - 50
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (713 KB) |  | HTML iconHTML  

    Tag clouds are a popular way to visually represent word frequencies. However, one major limitation is that they do not relate different word forms but treat every form as an individual tag. This results not only in a non-efficient use of screen space but, in particular, leaves the viewer with no indication whether there are other forms of a word or not. To overcome this limitation, we introduce prefix tag clouds: a visualization technique that uses a prefix tree to group different word forms and visualizes the sub trees as tag cloud. The grouping is emphasized by color, while the relative frequencies of the word forms are indicated by font size. A circular tag cloud layout supports the quick identification of the most frequent words and word forms. We show the usefulness of the approach for a large dataset of paper titles from the computer science bibliography DBLP. View full abstract»

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  • Radial Layered Matrix Visualization of Dynamic Graphs

    Publication Year: 2013 , Page(s): 51 - 58
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1203 KB) |  | HTML iconHTML  

    We propose a novel radial layered matrix visualization for dynamic directed weighted graphs in which the vertices can also be hierarchically organized. Edges are represented as color-coded arcs within the radial diagram. Their positions are defined by polar coordinates instead of Cartesian coordinates as in traditional adjacency matrix representations: the angular position of an edge within an annulus is given by the angle bisector of the two related vertices, the radial position depends linearly on the angular distance between these vertices. The exploration of time-varying relational data is facilitated by aligning graph patterns radially. Furthermore, our approach incorporates several interaction techniques to explore dynamic patterns such as trends and countertrends. The usefulness is illustrated by two case studies analyzing large dynamic call graphs acquired from open source software projects. View full abstract»

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  • Arrangement of Low-Dimensional Parallel Coordinate Plots for High-Dimensional Data Visualization

    Publication Year: 2013 , Page(s): 59 - 65
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (653 KB) |  | HTML iconHTML  

    Multidimensional data visualization is an important research topic that has been receiving increasing attention. Several techniques that use parallel coordinate plots have been proposed to represent all dimensions of data in a single display space. In addition, several other techniques that apply scatter plot matrices have been proposed to represent multidimensional data as a collection of low-dimensional data visualization spaces. Typically, when using the latter approach it is easier to understand relations among particular dimensions, but it is often difficult to observe relations between dimensions separated into different visualization spaces. This paper presents a framework for displaying an arrangement of low-dimensional data visualization spaces that are generated from high-dimensional datasets. Our proposed technique first divides the dimensions of the input datasets into groups of lower dimensions based on their correlations or other relationships. If the groups of lower dimensions can be visualized in independent rectangular spaces, our technique packs the set of low-dimensional data visualizations into a single display space. Because our technique places relevant low-dimensions closer together in the display space, it is easier to visually compare relevant sets of low-dimensional data visualizations. In this paper, we describe in detail how we implement our framework using parallel coordinate plots, and present several results demonstrating its effectiveness. View full abstract»

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  • A Matrix-Based Visualization for Exploring Dynamic Compound Digraphs

    Publication Year: 2013 , Page(s): 66 - 73
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1035 KB) |  | HTML iconHTML  

    We introduce a matrix-based visualization technique for exploring time-varying directed and weighted graphs. Two overview representations are shown: one for the time-aggregated relations with attached quantitative weighted attributes and one for the results of an automatic dynamic pattern identification algorithm, i.e., relations accompanied by categorical attributes. Apart from a dynamic edge pattern categorization, our tool can also compute graph-specific properties---such as shortest paths or the existence of cliques---and highlight their evolution over time. The visualization method is complemented by interaction techniques that allow the user to navigate, explore, and browse the data, based on the Visual Information Seeking Mantra---overview first, zoom and filter, then details-on-demand. If an additional hierarchical organization of the vertices is available, this is attached to the matrix by vertical and horizontal layered icicle plots allowing one to explore the data on different levels of hierarchical granularity. The usefulness of the tool is demonstrated by applying it to time-varying migration data in the hierarchically structured world. View full abstract»

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  • Text Visualization: Expressive Materials and Diverse Approaches

    Publication Year: 2013 , Page(s): 74 - 79
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (624 KB) |  | HTML iconHTML  

    Researches on text visualization have been extensively carried out with the development of the computer, the rise of open data based on Open API, and the commodification of visualization tools. Also, text visualization has led to the convergence of different fields, such as science, art, liberal arts, and sociology. Text visualization has a wide range of materials from the form and structure of text to contents text has created, not to mention independent meaning of each text. These materials are deliberately selected in accordance with the object of text visualization: what to express. A diversity of options could be used to achieve this goal. This paper is aimed to examine text data as materials for text visualization, an important part of data visualization, and discuss its types, nature and traits. This paper also explores different text visualization cases to provide a diversified analysis of expressive approaches to text visualization. View full abstract»

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  • Checkered Tree: Interactive Toolset for Flexible Data Exploration

    Publication Year: 2013 , Page(s): 80 - 85
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (782 KB) |  | HTML iconHTML  

    The fact is that in many Visual Analysis tasks are often used various mapping methods and techniques, inherited from the pre-computer era. Even for Data Exploration, despite of advanced interactive features of modern hardware and software. These ways of graphical representation with a static design are often rigidly adhered to a specific data structure. With such advantages of compact illustration for print (where paper space is crucial), the statically charts are principally at disadvantage in compositional flexibility. Unlike a paper version, array of interactive capabilities plays an important role in chart implementation for screen displaying. The paper reviews an original approach to categorical data visualization, which takes into account features of the visual perception of form and color, as well as distribution and focusing characteristics of the visual attention, along with advantages of using the interactive computer graphics capabilities. View full abstract»

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  • Evaluating MoodPic - a Concept for Collaborative Mood Music Playlist Creation

    Publication Year: 2013 , Page(s): 86 - 95
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (886 KB) |  | HTML iconHTML  

    This paper studies a MoodPic concept and a prototype implementation enabling collaborative creation of mood picture based musical play lists, evaluated qualitatively with 30 Finnish participants. In general, MoodPic was found to be a successful concept and stated to add novel experiences to music listening. Accessing music through mood pictures was highly appreciated and seen as a good way to discover new music over the genre boundaries and receive music recommendations from real users based on their mood picture interpretation. Sorting music based on mood pictures instead of genres was seen as an interesting and easy way to interact with music. Based on the interview results, this paper introduces several ideas for further improving the music listening experience using mood pictures as a basis for play lists. This paper summarizes the main findings and proposes an extensive set of generalized design implications to take into account when designing solutions for social music discovery. View full abstract»

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  • Voronoi-Based Label Placement for Metro Maps

    Publication Year: 2013 , Page(s): 96 - 101
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1660 KB) |  | HTML iconHTML  

    Metro maps with thumbnail photographs serve as common travel guides for providing sufficient information to meet the requirements of travelers in the cities. However, conventional methods attempt to minimize the total distance between stations and labels while maximizing the number of the labels rather than further taking into account the overall balance of the spatial distribution of labels. This paper presents an entropy-based approach for effectively annotating large annotation labels sufficiently close to the metro stations. Our idea is to decompose the entire labeling space intro regions bounded by the metro lines, and then further partition each region into Voronoi cells, each of which is reserved for a station to be annotated. This is accomplished by incorporating a new genetic-based optimization, while the fitness of the decomposition is evaluated by the entropy of the relative coverage ratios of such Voronoi cells. We also include several design examples to demonstrate that the proposed approach successfully distributes large labels around the metro network with minimal user intervention. View full abstract»

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