DevLan/vispubs huggingface dataset:
Exploring Multiple Trees through DAG Representations
Authors: Martin Graham 0001, Jessie Kennedy
Published at InfoVis, 2007

We present a directed acyclic graph visualisation designed to allow interaction with a set of multiple classification trees, specifically to find overlaps and differences between groups of trees and individual trees. The work is motivated by the need to find a representation for multiple trees that has the space-saving property of a general graph representation and the intuitive parent-child direction cues present in individual representation of trees. Using example taxonomic data sets, we describe augmentations to the common barycenter DAG layout method that reveal shared sets of child nodes between common parents in a clearer manner. Other interactions such as displaying the multiple ancestor paths of a node when it occurs in several trees, and revealing intersecting sibling sets within the context of a single DAG representation are also discussed.
Geographically Weighted Visualization: Interactive Graphics for Scale-Varying Exploratory Analysis
Authors: Jason Dykes, Chris Brunsdon
Published at InfoVis, 2007

We introduce a series of geographically weighted (GW) interactive graphics, or geowigs, and use them to explore spatial relationships at a range of scales. We visually encode information about geographic and statistical proximity and variation in novel ways through &lt;i&gt;gw-choropleth maps&lt;/i&gt;, multivariate &lt;i&gt;gw-boxplots, gw-shading&lt;/i&gt; and &lt;i&gt;scalograms&lt;/i&gt;. The new graphic types reveal information about GW statistics at several scales concurrently. We impement these views in prototype software containing dynamic links and GW interactions that encourage exploration and refine them to consider directional geographies. An informal evaluation uses interactive GW techniques to consider Guerry's dataset of 'moral statistics', casting doubt on correlations originally proposed through visual analysis, revealing new local anomalies and suggesting multivariate geographic relationships. Few attempts at visually synthesising geography with multivariate statistical values at multiple scales have been reported. The &lt;i&gt;geowigs &lt;/i&gt;proposed here provide informative representations of multivariate local variation, particularly when combined with interactions that coordinate views and result in &lt;i&gt;gw-shading&lt;/i&gt;. We argue that they are widely applicable to area and point-based geographic data and provide a set of methods to support visual analysis using GW statistics through which the effects of geography can be explored at multiple scales.
Hotmap: Looking at Geographic Attention
Authors: Danyel Fisher
Published at InfoVis, 2007

Understanding how people use online maps allows data acquisition teams to concentrate their efforts on the portions of the map that are most seen by users. Online maps represent vast databases, and so it is insufficient to simply look at a list of the most-accessed URLs. Hotmap takes advantage of the design of a mapping system's imagery pyramid to superpose a heatmap of the log files over the original maps. Users' behavior within the system can be observed and interpreted. This paper discusses the imagery acquisition task that motivated Hotmap, and presents several examples of information that Hotmap makes visible. We discuss the design choices behind Hotmap, including logarithmic color schemes; low-saturation background images; and tuning images to explore both infrequently-viewed and frequently-viewed spaces.
Interactive Tree Comparison for Co-located Collaborative Information Visualization
Authors: Petra Isenberg, Sheelagh Carpendale
Published at InfoVis, 2007

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 supporting 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.
Interactive Visual Exploration of a Large Spatio-temporal Dataset: Reflections on a Geovisualization Mashup.
Authors: Jo Wood, Jason Dykes, Aidan Slingsby, Keith C. Clarke
Published at InfoVis, 2007

Exploratory visual analysis is useful for the preliminary investigation of large structured, multifaceted spatio-temporal datasets. This process requires the selection and aggregation of records by time, space and attribute, the ability to transform data and the flexibility to apply appropriate visual encodings and interactions. We propose an approach inspired by geographical 'mashups' in which freely-available functionality and data are loosely but flexibly combined using de facto exchange standards. Our case study combines MySQL, PHP and the LandSerf GIS to allow Google Earth to be used for visual synthesis and interaction with encodings described in KML. This approach is applied to the exploration of a log of 1.42 million requests made of a mobile directory service. Novel combinations of interaction and visual encoding are developed including spatial 'tag clouds', 'tag maps', 'data dials' and multi-scale density surfaces. Four aspects of the approach are informally evaluated: the visual encodings employed, their success in the visual exploration of the dataset, the specific tools used and the 'mashup' approach. Preliminary findings will be beneficial to others considering using mashups for visualization. The specific techniques developed may be more widely applied to offer insights into the structure of multifarious spatio-temporal data of the type explored here.
Legible Cities: Focus-Dependent Multi-Resolution Visualization of Urban Relationships
Authors: Remco Chang, Ginette Wessel, Robert Kosara, Eric Sauda, William Ribarsky
Published at InfoVis, 2007

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 user's perspectives on the data, thereby diminishing the user's 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 preserving the user's 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, expert 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.
ManyEyes: a Site for Visualization at Internet Scale
Authors: Fernanda B. Viégas, Martin Wattenberg, Frank van Ham, Jesse Kriss, Matthew M. McKeon
Published at InfoVis, 2007

We describe the design and deployment of Many Eyes, a public Web site where users may upload data, create interactive visualizations, and carry on discussions. The goal of the site is to support collaboration around visualizations at a large scale by fostering a social style of data analysis in which visualizations not only serve as a discovery tool for individuals but also as a medium to spur discussion among users. To support this goal, the site includes novel mechanisms for end-user creation of visualizations and asynchronous collaboration around those visualizations. In addition to describing these technologies, we provide a preliminary report on the activity of our users.
Multi-Level Graph Layout on the GPU
Authors: Yaniv Frishman, Ayellet Tal
Published at InfoVis, 2007

This paper presents a new algorithm for force directed graph layout on the GPU. The algorithm, whose goal is to compute layouts accurately and quickly, has two contributions. The first contribution is proposing a general multi-level scheme, which is based on spectral partitioning. The second contribution is computing the layout on the GPU. Since the GPU requires a data parallel programming model, the challenge is devising a mapping of a naturally unstructured graph into a well-partitioned structured one. This is done by computing a balanced partitioning of a general graph. This algorithm provides a general multi-level scheme, which has the potential to be used not only for computation on the GPU, but also on emerging multi-core architectures. The algorithm manages to compute high quality layouts of large graphs in a fraction of the time required by existing algorithms of similar quality. An application for visualization of the topologies of ISP (Internet service provider) networks is presented.
NodeTrix: a Hybrid Visualization of Social Networks
Authors: Nathalie Henry Riche, Jean-Daniel Fekete, Michael J. McGuffin
Published at InfoVis, 2007

The need to visualize large social networks is growing as hardware capabilities make analyzing large networks feasible and many new data sets become available. Unfortunately, the visualizations in existing systems do not satisfactorily resolve the basic dilemma of being readable both for the global structure of the network and also for detailed analysis of local communities. To address this problem, we present NodeTrix, a hybrid representation for networks that combines the advantages of two traditional representations: node-link diagrams are used to show the global structure of a network, while arbitrary portions of the network can be shown as adjacency matrices to better support the analysis of communities. A key contribution is a set of interaction techniques. These allow analysts to create a NodeTrix visualization by dragging selections to and from node-link and matrix forms, and to flexibly manipulate the NodeTrix representation to explore the dataset and create meaningful summary visualizations of their findings. Finally, we present a case study applying NodeTrix to the analysis of the InfoVis 2004 coauthorship dataset to illustrate the capabilities of NodeTrix as both an exploration tool and an effective means of communicating results.
Overview Use in Multiple Visual Information Resolution Interfaces
Authors: Heidi Lam, Tamara Munzner, Robert Kincaid
Published at InfoVis, 2007

In interfaces that provide multiple visual information resolutions (VIR), low-VIR overviews typically sacrifice visual details for display capacity, with the assumption that users can select regions of interest to examine at higher VI Rs. Designers can create low VIRs based on multi-level structure inherent in the data, but have little guidance with single-level data. To better guide design tradeoff between display capacity and visual target perceivability, we looked at overview use in two multiple-VIR interfaces with high-VIR displays either embedded within, or separate from, the overviews. We studied two visual requirements for effective overview and found that participants would reliably use the low-VIR overviews only when the visual targets were simple and had small visual spans. Otherwise, at least 20% chose to use the high-VIR view exclusively. Surprisingly, neither of the multiple-VIR interfaces provided performance benefits when compared to using the high-VIR view alone. However, we did observe benefits in providing side-by-side comparisons for target matching. We conjecture that the high cognitive load of multiple-VIR interface interactions, whether real or perceived, is a more considerable barrier to their effective use than was previously considered.
Scented Widgets: Improving Navigation Cues with Embedded Visualizations
Authors: Wesley Willett, Jeffrey Heer, Maneesh Agrawala
Published at InfoVis, 2007

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.
Sequential Document Visualization
Authors: Yi Mao, Joshua V. Dillon, Guy Lebanon
Published at InfoVis, 2007

Documents and other categorical valued time series are often characterized by the frequencies of short range sequential patterns such as n-grams. This representation converts sequential data of varying lengths to high dimensional histogram vectors which are easily modeled by standard statistical models. Unfortunately, the histogram representation ignores most of the medium and long range sequential dependencies making it unsuitable for visualizing sequential data. We present a novel framework for sequential visualization of discrete categorical time series based on the idea of local statistical modeling. The framework embeds categorical time series as smooth curves in the multinomial simplex summarizing the progression of sequential trends. We discuss several visualization techniques based on the above framework and demonstrate their usefulness for document visualization.
Show Me: Automatic Presentation for Visual Analysis
Authors: Jock D. Mackinlay, Pat Hanrahan, Chris Stolte
Published at InfoVis, 2007

This paper describes Show Me, an integrated set of user interface commands and defaults that incorporate automatic presentation into a commercial visual analysis system called Tableau. A key aspect of Tableau is VizQL, a language for specifying views, which is used by Show Me to extend automatic presentation to the generation of tables of views (commonly called small multiple displays). A key research issue for the commercial application of automatic presentation is the user experience, which must support the flow of visual analysis. User experience has not been the focus of previous research on automatic presentation. The Show Me user experience includes the automatic selection of mark types, a command to add a single field to a view, and a pair of commands to build views for multiple fields. Although the use of these defaults and commands is optional, user interface logs indicate that Show Me is used by commercial users.
Spatialization Design: Comparing Points and Landscapes
Authors: Melanie Tory, David W. Sprague, Fuqu Wu, Wing Yan So, Tamara Munzner
Published at InfoVis, 2007

Spatializations represent non-spatial data using a spatial layout similar to a map. We present an experiment comparing different visual representations of spatialized data, to determine which representations are best for a non-trivial search and point estimation task. Primarily, we compare point-based displays to 2D and 3D information landscapes. We also compare a colour (hue) scale to a grey (lightness) scale. For the task we studied, point-based spatializations were far superior to landscapes, and 2D landscapes were superior to 3D landscapes. Little or no benefit was found for redundantly encoding data using colour or greyscale combined with landscape height. 3D landscapes with no colour scale (height-only) were particularly slow and inaccurate. A colour scale was found to be better than a greyscale for all display types, but a greyscale was helpful compared to height-only. These results suggest that point-based spatializations should be chosen over landscape representations, at least for tasks involving only point data itself rather than derived information about the data space.
Toward a Deeper Understanding of the Role of Interaction in Information Visualization
Authors: Ji Soo Yi, Youn ah Kang, John T. Stasko, Julie A. Jacko
Published at InfoVis, 2007

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.
VisLink: Revealing Relationships Amongst Visualizations
Authors: Christopher Collins 0001, Sheelagh Carpendale
Published at InfoVis, 2007

We present VisLink, a method by which visualizations and the relationships between them can be interactively explored. VisLink readily generalizes to support multiple visualizations, empowers inter-representational queries, and enables the reuse of the spatial variables, thus supporting efficient information encoding and providing for powerful visualization bridging. Our approach uses multiple 2D layouts, drawing each one in its own plane. These planes can then be placed and re-positioned in 3D space: side by side, in parallel, or in chosen placements that provide favoured views. Relationships, connections, and patterns between visualizations can be revealed and explored using a variety of interaction techniques including spreading activation and search filters.
Visual Analysis of Network Traffic for Resource Planning, Interactive Monitoring, and Interpretation of Security Threats
Authors: Florian Mansmann, Daniel A. Keim, Stephen C. North, Brian Rexroad, Daniel Sheleheda
Published at InfoVis, 2007

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.
Visualization of Heterogeneous Data
Authors: Mike Cammarano, Xin Dong 0001, Bryan Chan 0001, Jeff Klingner, Justin Talbot, Alon Y. Halevy, Pat Hanrahan
Published at InfoVis, 2007

Both the resource description framework (RDF), used in the semantic web, and Maya Viz u-forms represent data as a graph of objects connected by labeled edges. Existing systems for flexible visualization of this kind of data require manual specification of the possible visualization roles for each data attribute. When the schema is large and unfamiliar, this requirement inhibits exploratory visualization by requiring a costly up-front data integration step. To eliminate this step, we propose an automatic technique for mapping data attributes to visualization attributes. We formulate this as a schema matching problem, finding appropriate paths in the data model for each required visualization attribute in a visualization template.
Visualizing Causal Semantics Using Animations
Authors: Nivedita R. Kadaba, Pourang Irani, Jason Leboe-McGowan
Published at InfoVis, 2007

Michotte's theory of ampliation suggests that causal relationships are perceived by objects animated under appropriate spatiotemporal conditions. We extend the theory of ampliation and propose that the immediate perception of complex causal relations is also dependent on a set of structural and temporal rules. We designed animated representations, based on Michotte's rules, for showing complex causal relationships or causal semantics. In this paper we describe a set of animations for showing semantics such as causal amplification, causal strength, causal dampening, and causal multiplicity. In a two part study we compared the effectiveness of both the static and animated representations. The first study (N=44) asked participants to recall passages that were previously displayed using both types of representations. Participants were 8% more accurate in recalling causal semantics when they were presented using animations instead of static graphs. In the second study (N=112) we evaluated the intuitiveness of the representations. Our results showed that while users were as accurate with the static graphs as with the animations, they were 9% faster in matching the correct causal statements in the animated condition. Overall our results show that animated diagrams that are designed based on perceptual rules such as those proposed by Michotte have the potential to facilitate comprehension of complex causal relations.
Visualizing Changes of Hierarchical Data using Treemaps
Authors: Ying Tu, Han-Wei Shen
Published at InfoVis, 2007

While the treemap is a popular method for visualizing hierarchical data, it is often difficult for users to track layout and attribute changes when the data evolve over time. When viewing the treemaps side by side or back and forth, there exist several problems that can prevent viewers from performing effective comparisons. Those problems include abrupt layout changes, a lack of prominent visual patterns to represent layouts, and a lack of direct contrast to highlight differences. In this paper, we present strategies to visualize changes of hierarchical data using treemaps. A new treemap layout algorithm is presented to reduce abrupt layout changes and produce consistent visual patterns. Techniques are proposed to effectively visualize the difference and contrast between two treemap snapshots in terms of the map items' colors, sizes, and positions. Experimental data show that our algorithm can achieve a good balance in maintaining a treemap's stability, continuity, readability, and average aspect ratio. A software tool is created to compare treemaps and generate the visualizations. User studies show that the users can better understand the changes in the hierarchy and layout, and more quickly notice the color and size differences using our method.