Information Visualization

Abstract: In many domains, increased collaboration has lead to more innovation by fostering the sharing of knowledge, skills, and ideas. Shared analysis of information visualizations does not only lead to increased information processing power, but team members can also share, negotiate, and discuss their views and interpretations on a dataset and contribute unique perspectives on a given problem. Designing technologies to support collaboration around information visualizations poses special challenges and relatively few systems have been designed. We focus on suppor ting small groups collaborating around information visualizations in a co-located setting, using a shared interactive tabletop display. We introduce an analysis of challenges and requirements for the design of co-located collaborative information visualization systems. We then present a new system that facilitates hierarchical data comparison tasks for this type of collaborative work. Our system supports multi-user input, shared and individual views on the hierarchical data visualization, flexible use of representations, and flexible workspace organization to facilitate group work around visualizations.

 Information Visualization;  collaboration;  co-located work;  hierarchical data comparison;  

Abstract: In this paper we investigate the effectiveness of animated transitions between common statistical data graphics such as bar charts, pie charts, and scatter plots. We extend theoretical models of data graphics to include such transitions, introducing a taxonomy of transition types. We then propose design principles for creating effective transitions and illustrate the application of these principles in DynaVis, a visualizationsystemfeaturing animated data graphics. Two controlled experiments were conducted to assess the efficacyof various transition types, findingthat animated transitions can significantly improve graphical perception.

 Information Visualization;  design;  animation;  statistical data graphics;  transitions;  experiment;  

Abstract: Numerous systems have been developed to display large collections of data for urban contexts; however, most have focused on layering of single dimensions of data and manual calculations to understand relationships within the urban environment. Furthermore, these systems often limit the users perspectives on the data, thereby diminishing the users spatial understanding of the viewing region. In this paper, we introduce a highly interactive urban visualization tool that provides intuitive understanding of the urban data. Our system utilizes an aggregation method that combines buildings and city blocks into legible clusters, thus providing continuous levels of abstraction while preser ving the users mental model of the city. In conjunction with a 3D view of the urban model, a separate but integrated information visualization view displays multiple disparate dimensions of the urban data, allowing the user to understand the urban environment both spatially and cognitively in one glance. For our evaluation, exper t users from various backgrounds viewed a real city model with census data and confirmed that our system allowed them to gain more intuitive and deeper understanding of the urban model from different perspectives and levels of abstraction than existing commercial urban visualization systems.

 Information Visualization;  urban models;  multi-resolution;  

Abstract: Treemaps provide an interesting solution for representing hierarchical data. However, most studies have mainly focused on layout algorithms and paid limited attention to the interaction with treemaps. This makes it difficult to explore large data sets and to get access to details, especially to those related to the leaves of the trees. We propose the notion of zoomable treemaps (ZTMs), an hybridization between treemaps and zoomable user interfaces that facilitates the navigation in large hierarchical data sets. By providing a consistent set of interaction techniques, ZTMs make it possible for users to browse through ver y large data sets (e.g., 700,000 nodes dispatched amongst 13 levels). These techniques use the structure of the displayed data to guide the interaction and provide a way to improve interactive navigation in treemaps.

 Information Visualization;  multi-scale interaction;  structure-aware navigation;  zoomable treemaps;  

Abstract: This paper presents scented widgets, graphical user interface controls enhanced with embedded visualizations that facilitate navigation in information spaces. We describe design guidelines for adding visual cues to common user interface widgets such as radio buttons, sliders, and combo boxes and contribute a general software framework for applying scented widgets within applications with minimal modifications to existing source code. We provide a number of example applications and describe a controlled experiment which finds that users exploring unfamiliar data make up to twice as many unique discoveries using widgets imbued with social navigation data. However, these differences equalize as familiarity with the data increases.

 Information Visualization;  Visualization;  infovis;  vast;  icons;  large dataset visualization;  text and document visualization;  multiresolution visualization;  geographic visualization;  applications of infovis;  user interface toolkits;  information foraging;  social navigation;  social data analysis;  

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Abstract: Even though interaction is an important part of information visualization (Infovis), it has garnered a relatively low level of attention from the Infovis community. A few frameworks and taxonomies of Infovis interaction techniques exist, but they typically focus on low-level operations and do not address the variety of benefits interaction provides. After conducting an extensive review of Infovis systems and their interactive capabilities, we propose seven general categories of interaction techniques widely used in Infovis: 1) Select, 2) Explore, 3) Reconfigure, 4) Encode, 5) Abstract/Elaborate, 6) Filter, and 7) Connect. These categories are organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system. The categories can act as a framework to help discuss and evaluate interaction techniques and hopefully lay an initial foundation toward a deeper understanding and a science of interaction.

 Information Visualization;  taxonomy;  Visual Analytics;  interaction techniques;  interaction;  

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Abstract: Even though interaction is an important part of information visualization (Infovis), it has garnered a relatively low level of attention from the Infovis community. A few frameworks and taxonomies of Infovis interaction techniques exist, but they typically focus on low-level operations and do not address the variety of benefits interaction provides. After conducting an extensive review of Infovis systems and their interactive capabilities, we propose seven general categories of interaction techniques widely used in Infovis: 1) Select, 2) Explore, 3) Reconfigure, 4) Encode, 5) Abstract/Elaborate, 6) Filter, and 7) Connect. These categories are organized around a user's intent while interacting with a system rather than the low-level interaction techniques provided by a system. The categories can act as a framework to help discuss and evaluate interaction techniques and hopefully lay an initial foundation toward a deeper understanding and a science of interaction.

 Information Visualization;  taxonomy;  Visual Analytics;  interaction techniques;  interaction;  

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Abstract: We present CiteWiz, an extensible framework for visualization of scientific citation networks. The system is based on a taxonomy of citation database usage for researchers, and provides a timeline visualization for overviews and an influence visualization for detailed views. The timeline displays the general chronology and importance of authors and articles in a citation database, whereas the influence visualization is implemented using the Growing Polygons technique, suitably modified to the context of browsing citation data. Using the latter technique, hierarchies of articles with potentially very long citation chains can be graphically represented. The visualization is augmented with mechanisms for parent-child visualization and suitable interaction techniques for interacting with the view hierarchy and the individual articles in the dataset. We also provide an interactive concept map for keywords and co-authorship using a basic force-directed graph layout scheme. A formal user study indicates that CiteWiz is significantly more efficient than traditional database interfaces for high-level analysis tasks relating to influence and overviews, and equally efficient for low-level tasks such as finding a paper and correlating bibliographical data.Information Visualization (2007) 6, 215-232. doi:10.1057/palgrave.ivs.9500156

 Information Visualization;  citation analysis;  bibliographic networks;  

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 Information Visualization;  Visual Analytics;  data management;  data retrieval;  smart aggregation;  situational awareness;  

Abstract: This paper introduces a new Visual Analysis tool named IMAS (Interactive Multigenomic Analysis System), which combines common analysis tools such as Glimmer, BLAST, and Clustal-W into a unified Visual Analytic framework. IMAS displays the primary DNA sequence being analyzed by the biologist in a highly interactive, zoomable visual display. The user may analyze the sequence in a number of ways, and visualize these analyses in a coherent, sequence aligned form, with all related analysis products grouped together. This enables the user to rapidly perform analyses of DNA sequences without the need for tedious and error-prone cutting and pasting of sequence data from text files to and from web-based databases and data analysis services, as is now common practice.

 Information Visualization;  Visual Analytics;  bioinformatics;  intelligence analysis;  investigative analysis;  multiple views;  

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 Information Visualization;  web session log analysis;  visual exploratory data analysis;  

Abstract: The Internet has become a wild place: malicious code is spread on personal computers across the world, deploying botnets ready to attack the network infrastructure. The vast number of security incidents and other anomalies overwhelms attempts at manual analysis, especially when monitoring service provider backbone links. We present an approach to interactive visualization with a case study indicating that interactive visualization can be applied to gain more insight into these large data sets. We superimpose a hierarchy on IP address space, and study the suitability of Treemap variants for each hierarchy level. Because viewing the whole IP hierarchy at once is not practical for most tasks, we evaluate layout stability when eliding large parts of the hierarchy, while maintaining the visibility and ordering of the data of interest.

 Information Visualization;  network security;  treemap;  network monitoring;  

Abstract: Despite a diversity of software architectures supporting information visualization, it is often difficult to identify, evaluate, and re-apply the design solutions implemented within such frameworks. One popular and effective approach for addressing such difficulties is to capture successful solutions in design patterns, abstract descriptions of interacting software components that can be customized to solve design problems within a particular context. Based upon a review of existing frameworks and our own experiences building visualization software, we present a series of design patterns for the domain of information visualization. We discuss the structure, context of use, and interrelations of patterns spanning data representation, graphics, and interaction. By representing design knowledge in a reusable form, these patterns can be used to facilitate software design, implementation, and evaluation, and improve developer education and communication.

 Design Patterns;  Information Visualization;  Software Engineering;  Object-Oriented Programming;  

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 Information Visualization;  graph visualization;  graph clustering;  

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 Information Visualization;  Geovisualization;  Visual Analytics;  multivariate and spatio-temporal data;  ordering;  self-organizing map (SOM);  small multiples.;  

Abstract: Science monitoring is a core issue in the new world of business and research. Companies and institutes need to monitor the activities of their competitors, get information on the market, changing technologies or government policies. This paper presents the Tétralogie platform that is aimed at allowing a user to interactively discover trends in scientific research and communities from large textual collections that include information about geographical location. Tétralogie consists of several agents that communicate with each other on users’ demands in order to deliver results to them. Metadata and document content are extracted before being mined. Results are displayed in the form of histograms, networks and geographical maps; these complementary types of presentations increase the possibilities of analysis compared to the use of these tools separately. We illustrate the overall process through a case study of scientific literature analysis and show how the different agents can be combined to discover the structure of a domain. The system correctly predicts the country contribution to a field in future years and allows exploration of the relationships between countries.

 Information Visualization;  knowledge discovery;  information mining;  data analysis;  Domain knowledge;  Geographical maps;  

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Abstract: Sorry no abstract available for this article

 Information Visualization;  evaluation;  Theory;  analytic gap;  framework;  knowledge tasks;  

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 Information Visualization;  visualization tasks;  visualization techniques and methodologies;  theory and methods;  

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 Information Visualization;  text mining;  event analysis;  time-dependent visualization;  

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 Information Visualization;  hierarchies;  Voronoi treemaps;  trees;  treemaps;  Voronoi tessellations;  

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 Information Visualization;  direct manipulation;  direct data editing;  database user interfaces;  

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 Information Visualization;  visual data mining;  visual clustering;  density-based visualization;  

Abstract: Information visualization is an interdisciplinary research area in which cartographic efforts have mostly addressed the handling of geographic information. Some cartographers have recently become involved in attempts to extend geographic principles and cartographic techniques to the visualization of non-geographic information. This paper reports on current progress and future opportunities in this emerging research field commonly known as spatialization. The discussion is mainly devoted to the computational techniques that turn high-dimensional data into visualizations via processes of projection and transformation. It is argued that cartographically informed engagement of computationally intensive techniques can help to provide richer and less opaque information visualizations. The discussion of spatialization methods is linked to another priority area of cartographic involvement, the development of theory and principles for cognitively plausible spatialization. The paper distinguishes two equally important sets of challenges for cartographic success in spatialization research. One is the recognition that there are distinct advantages to applying a cartographic perspective in information visualization. This requires our community to more thoroughly understand the essence of cartographic activity and to explore the implications of its metaphoric transfer to non-geographic domains. Another challenge lies in cartographers becoming a more integral part of the information visualization community and actively engaging its constituent research fields.

 Information Visualization;  Spatialization;  

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Abstract: We introduce a network visualization technique that supports an analytical method applied in the social sciences. Policy network analysis is an approach to study policy making structures, processes, and outcomes, thereby concentrating on relations between policy actors. An important operational concept for the analysis of policy networks is the notion of centrality, i.e., the distinction of actors according to their importance in a relational structure. We integrate this measure in a layout model for networks by mapping structural to geometric centrality. Thus, centrality values and network data can be presented simultaneously and explored interactively.

 Information Visualization;  social network analysis;  graph drawing;  force-directed placement;  centrality;  

Abstract: Social navigation exploits the knowledge and experience of peer users of information resources. A wide variety of visual--spatial approaches become increasingly popular as a means to optimize information access as well as to foster and sustain a virtual community among geographically distributed users. An information landscape is among the most appealing design options of representing and communicating the essence of distributed information resources to users. A fundamental and challenging issue is how an information landscape can be designed such that it will not only preserve the essence of the underlying information structure, but also accommodate the diversity of individual users. The majority of research in social navigation has been focusing on how to extract useful information from what is in common between users profiles, their interests and preferences. In this article, we explore the role of modelling sequential behaviour patterns of users in augmenting social navigation in thematic landscapes. In particular, we compare and analyse the trails of individual users in thematic spaces along with their cognitive ability measures. We are interested in whether such trails can provide useful guidance for social navigation if they are embedded in a visual--spatial environment. Furthermore, we are interested in whether such information can help users to learn from each other, for example, from the ones who have been successful in retrieving documents. In this article, we first describe how users trails in sessions of an experimental study of visual information retrieval can be characterized by Hidden Markov Models. Trails of users with the most successful retrieval performance are used to estimate parameters of such models. Optimal virtual trails generated from the models are visualized and animated as if they were actual trails of individual users in order to highlight behavioural patterns that may foster social navigation. The findings of the research will provide direct input to the design of social navigation systems as well as to enrich theories of social navigation in a wider context. These findings will lead to the further development and consolidation of a tightly coupled paradigm of spatial, semantic and social navigation.

 Information Visualization;  information foraging;  social navigation;  behaviour semantics;  hidden Markov models;  

Abstract: This paper reports work in progress on the analysis and visualization of the spatial and temporal distribution of user interaction data collected in three-dimensional (3D) virtual worlds. Two tools are introduced. The WorldMapper reads in a so-called propdump file and creates a 2D clickable map showing the layout of the world as well as interaction possibilities such as teleports and clickable web links. The second tool visualizes user interaction data such as navigation, chatting, and Web access activity overlaid on the world map. Resulting visualizations are meant to support social navigation, design evaluation and optimization, and the study of virtual communities. Both tools are demonstrated on a 19-person information treasure hunt for information in a 3D virtual world. The paper concludes with a discussion and an outlook.

 Information Visualization;  usability;  social navigation;  virtual worlds;  spatio-Ttemporal maps;  

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 Information Visualization;  user interfaces;  multiple views;  design guidelines;  usability heuristics;  

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 Information Visualization;  spatial queries;  dynamic queries;  information exploration;  database query;  tight coupling;