Authors
Michael Douma
Grzegorz Ligierko
Ovidiu Ancuta
Pavel Gritsai
Sean Liu

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.183

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Abstract
Trees and graphs are relevant to many online tasks such as visualizing social networks, product catalogs, educational portals, digital libraries, the semantic web, concept maps and personalized information management. SpicyNodes is an information-visualization technology that builds upon existing research on radial tree layouts and graph structures. Users can browse a tree, clicking from node to node, as well as successively viewing a node, immediately related nodes and the path back to the “home” nodes. SpicyNodes’ layout algorithms maintain balanced layouts using a hybrid mixture of a geometric layout (a succession of spanning radial trees) and force-directed layouts to minimize overlapping nodes, plus several other improvements over prior art. It provides XML-based API and GUI authoring tools. The goal of the SpicyNodes project is to implement familiar principles of radial maps and focus+context with an attractive and inviting look and feel in an open system that is accessible to virtually any Internet user.

Author
Matt McKeon

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.148

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Abstract
We describe the design and deployment of Dashiki, a public website where users may collaboratively build
visualization dashboards through a combination of a wiki-like syntax and interactive editors. Our goals are to extend existing research on social data analysis into presentation and organization of data from multiple sources, explore new metaphors for these activities, and participate more fully in the web!s information ecology by providing tighter integration with real-time data. To support these goals, our design includes novel and low-barrier mechanisms for editing and layout of dashboard pages and visualizations, connection to data sources, and coordinating interaction between visualizations. In addition to describing these technologies, we provide a preliminary report on the public launch of a prototype based on this design, including a description of the activities of our users derived from observation and interviews.

Authors
Sabrina Bresciani
Martin J. Eppler

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.188

Abstract
A great corpus of studies reports empirical evidence of how information visualization supports comprehension and analysis of data. The benefits of visualization for synchronous group knowledge work, however, have not been addressed extensively. Anecdotal evidence and use cases illustrate the benefits of synchronous collaborative information visualization, but very few empirical studies have rigorously examined the impact of visualization on group knowledge work. We have consequently designed and conducted an experiment in which we have analyzed the impact of visualization on knowledge sharing in situated work groups. Our experimental study consists of evaluating the performance of 131 subjects (all experienced managers) in groups of 5 (for a total of 26 groups), working together on a real-life knowledge sharing task. We compare (1) the control condition (no visualization provided), with two visualization supports: (2) optimal and (3) suboptimal visualization (based on a previous survey). The facilitator of each group was asked to populate the provided interactive visual template with insights from the group, and to organize the contributions according to the group consensus. We have evaluated the results through both objective and subjective measures. Our statistical analysis clearly shows that interactive visualization has a statistically significant, objective and positive impact on the outcomes of knowledge sharing, but that the subjects seem not to be aware of this. In particular, groups supported by visualization achieved higher productivity, higher quality of outcome and greater knowledge gains. No statistically significant results could be found between an optimal and a suboptimal visualization though (as classified by the pre-experiment survey). Subjects also did not seem to be aware of the benefits that the visualizations provided as no difference between the visualization and the control conditions was found for the self-reported measures of satisfaction and participation. An implication of our study for information visualization applications is to extend them by using real-time group annotation functionalities that aid in the group sense making process of the represented data.

Authors
Matthew Tobiasz
Petra Isenberg
Sheelagh Carpendale

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.162

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Abstract
Large multi-touch displays are expanding the possibilities of multiple-coordinated views by allowing multiple people to interact with data in concert or independently. We present Lark, a system that facilitates the coordination of interactions with information visualizations on shared digital workspaces. We focus on supporting this coordination according to four main criteria: scoped interaction, temporal flexibility, spatial flexibility, and changing collaboration styles. These are achieved by integrating a representation of the information visualization pipeline into the shared workspace, thus explicitly indicating coordination points on data, representation, presentation, and view levels. This integrated meta-visualization supports both the awareness of how views are linked and the freedom to work in concert or independently. Lark incorporates these four main criteria into a coherent visualization collaboration interaction environment by providing direct visual and algorithmic support for the coordination of data analysis actions over shared large displays.

Authors
Edward C. Clarkson
Krishna Desai
James D. Foley

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.176

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Running Time: 20 min 47 sec

Abstract
Hierarchical representations are common in digital repositories, yet are not always fully leveraged in their online
search interfaces. This work describes ResultMaps, which use hierarchical treemap representations with query string-driven digital library search engines. We describe two lab experiments, which find that ResultsMap users yield significantly better results over a control condition on some subjective measures, and we find evidence that ResultMaps have ancillary benefits via increased understanding of some aspects of repository content. The ResultMap system and experiments contribute an understanding of the benefits—direct and indirect—of the ResultMap approach to repository search visualization.

Authors
Taowei David Wang
Catherine Plaisant
Ben Shneiderman
Neil Spring
David Roseman
Greg Marchand
Vikramjit Mukherjee
Mark Smith

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.187

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Abstract
When analyzing thousands of event histories, analysts often want to see the events as an aggregate to detect insights and generate new hypotheses about the data. An analysis tool must emphasize both the prevalence and the temporal ordering of these events. Additionally, the analysis tool must also support flexible comparisons to allow analysts to gather visual evidence. In a previsous work, we introduced align, rank, and filter (ARF) to accentuate temporal ordering. In this paper, we present temporal summaries, an interactive visualization technique that highlights the prevalence of event occurrences. Temporal summaries dynamically aggregate events in multiple granularities (year, month, week, day, hour, etc.) for the purpose of spotting trends over time and comparing several groups of records. They provide affordances for analysts to perform temporal range filters. We demonstrate the applicability of this approach in two extensive case studies with analysts who applied temporal summaries to search, filter, and look for patterns in electronic health records and academic records.

Author
Diansheng Guo

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.143

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Abstract
Spatial interactions (or flows), such as population migration and disease spread, naturally form a weighted location-to-location network (graph). Such geographically embedded networks (graphs) are usually very large. For example, the county-to-county migration data in the U.S. has thousands of counties and about a million migration paths. Moreover, many variables are associated with each flow, such as the number of migrants for different age groups, income levels, and occupations. It is a challenging task to visualize such data and discover network structures, multivariate relations, and their geographic patterns simultaneously. This paper addresses these challenges by developing an integrated interactive visualization framework that consists three coupled components: (1) a spatially constrained graph partitioning method that can construct a hierarchy of geographical regions (communities), where there are more flows or connections within regions than across regions; (2) a multivariate clustering and visualization method to detect and present multivariate patterns in the aggregated region-to-region flows; and (3) a highly interactive flow mapping component to map both flow and multivariate patterns in the geographic space, at different hierarchical levels. The proposed approach can process relatively large data sets and effectively discover and visualize major flow structures and multivariate relations at the same time. User interactions are supported to facilitate the understanding of both an overview and detailed patterns.

Authors
Melanie Tory
Colin Swindells
Rebecca Dreezer

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.127

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Abstract
Spatialization displays use a geographic metaphor to arrange non-spatial data. For example, spatializations are
commonly applied to document collections so that document themes appear as geographic features such as hills. Many common spatialization interfaces use a 3-D landscape metaphor to present data. However, it is not clear whether 3-D spatializations afford improved speed and accuracy for user tasks compared to similar 2-D spatializations. We describe a user study comparing users’ ability to remember dot displays, 2-D landscapes, and 3-D landscapes for two different data densities (500 vs. 1000 points). Participants’ visual memory was statistically more accurate when viewing dot displays and 3-D landscapes compared to 2-D landscapes. Furthermore, accuracy remembering a spatialization was significantly better overall for denser spatializations. These
results are of benefit to visualization designers who are contemplating the best ways to present data using spatialization techniques.

Authors
Zhicheng Liu
John Stasko
Timothy Sullivan

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.180

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Abstract
We present a case study of our experience designing SellTrend, a visualization system for analyzing airline travel purchase requests. The relevant transaction data can be characterized as multi-variate temporal and categorical event sequences, and the chief problem addressed is how to help company analysts identify complex combinations of transaction attributes that contribute to failed purchase requests. SellTrend combines a diverse set of techniques ranging from time series visualization to faceted browsing and historical trend analysis in order to help analysts make sense of the data. We believe that the combination of views and interaction capabilities in SellTrend provides an innovative approach to this problem and to other similar types of multivariate, temporally driven transaction data analysis. Initial feedback from company analysts confirms the utility and benefits of the system.

Authors
Christophe Hurter
Benjamin Tissoires
Stéphane Conversy

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.145

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Running Time: 19 min 32 sec

Abstract
When displaying thousands of aircraft trajectories on a screen, the visualization is spoiled by a tangle of trails. The visual analysis is therefore difficult, especially if a specific class of trajectories in an erroneous dataset has to be studied. We designed FromDaDy, a trajectory visualization tool that tackles the difficulties of exploring the visualization of multiple trails. This multidimensional data exploration is based on scatterplots, brushing, pick and drop, juxtaposed views and rapid visual design. Users can organize the workspace composed of multiple juxtaposed views. They can define the visual configuration of the views by connecting data dimensions from the dataset to Bertin’s visual variables. They can then brush trajectories, and with a pick and drop operation they can spread the brushed information across views. They can then repeat these interactions, until they extract a set of relevant data, thus formulating complex queries. Through two real-world scenarios, we show how FromDaDy supports iterative queries and the extraction of trajectories in a dataset that contains up to 5 million data.