14 - 19 OCTOBER, 2012. SEATTLE, WASHINGTON, USA

2012 IEEE INFOVIS Papers

INFOVIS Papers: Evaluation and Methodology
Session : 
Evaluation and Methodology
Date & Time : October 16 10:30 am - 12:10 pm
Location : Grand Ballroom C
Chair : Leland Wilkinson
Papers : 
How Capacity Limits of Attention Influence Information Visualization Effectiveness
Authors:
Steve Haroz, David Whitney
Abstract :
In this paper, we explore how the capacity limits of attention influence the effectiveness of information visualizations. We conducted a series of experiments to test how visual feature type (color vs. motion), layout, and variety of visual elements impacted user performance. The experiments tested users' abilities to (1) determine if a specified target is on the screen, (2) detect an odd-ball, deviant target, different from the other visible objects, and (3) gain a qualitative overview by judging the number of unique categories on the screen. Our results show that the severe capacity limits of attention strongly modulate the effectiveness of information visualizations, particularly the ability to detect unexpected information. Keeping in mind these capacity limits, we conclude with a set of design guidelines which depend on a visualization's intended use.
Different Strokes for Different Folks: Visual Presentation Design between Disciplines
Authors:
Steven R. Gomez, Radu Jianu, Caroline Ziemkiewicz, Hua Guo, David H. Laidlaw
Abstract :
We present an ethnographic study of design differences in visual presentations between academic disciplines. Characterizing design conventions between users and data domains is an important step in developing hypotheses, tools, and design guidelines for information visualization. In this paper, disciplines are compared at a coarse scale between four groups of fields: social, natural, and formal sciences; and the humanities. Two commonplace presentation types were analyzed: electronic slideshows and whiteboard chalk talks. We found design differences in slideshows using two methods: coding and comparing manually-selected features, like charts and diagrams, and an image-based analysis using PCA called eigenslides. In whiteboard talks with controlled topics, we observed design behaviors, including using representations and formalisms from a participant's own discipline, that suggest authors might benefit from novel assistive tools for designing presentations. Based on these findings, we discuss opportunities for visualization ethnography and human-centered authoring tools for visual information.
Does an Eye Tracker Tell the Truth about Visualizations?: Findings while Investigating Visualizations for Decision Making
Authors:
Sung-Hee Kim, Zhihua Dong, Hanjun Xian, Benjavan Upatising, Ji Soo Yi
Abstract :
For information visualization researchers, eye tracking has been a useful tool to investigate research participants' underlying cognitive processes by tracking their eye movements while they interact with visual techniques. We used an eye tracker to better understand why participants with a variant of a tabular visualization called 'SimulSort' outperformed ones with a conventional table and typical one-column sorting feature (i.e., Typical Sorting). The collected eye-tracking data certainly shed light on the detailed cognitive processes of the participants; SimulSort helped with decision-making tasks by promoting efficient browsing behavior and compensatory decision-making strategies. However, more interestingly, we also found unexpected eye-tracking patterns with Simul- Sort. We investigated the cause of the unexpected patterns through a crowdsourcing-based study (i.e., Experiment 2), which elicited an important limitation of the eye tracking method: incapability of capturing peripheral vision. This particular result would be a caveat for other visualization researchers who plan to use an eye tracker in their studies. In addition, the method to use a testing stimulus (i.e., influential column) in Experiment 2 to verify the existence of such limitations would be useful for researchers who would like to verify their eye tracking results.
Design Study Methodology: Reflections from the Trenches and the Stacks
Authors:
Michael Sedlmair, Miriah Meyer, Tamara Munzner
Abstract :
Design studies are an increasingly popular form of problem-driven visualization research, yet there is little guidance available about how to do them effectively. In this paper we reflect on our combined experience of conducting twenty-one design studies, as well as reading and reviewing many more, and on an extensive literature review of other field work methods and methodologies. Based on this foundation we provide definitions, propose a methodological framework, and provide practical guidance for conducting design studies. We define a design study as a project in which visualization researchers analyze a specific real-world problem faced by domain experts, design a visualization system that supports solving this problem, validate the design, and reflect about lessons learned in order to refine visualization design guidelines. We characterize two axes - a task clarity axis from fuzzy to crisp and an information location axis from the domain expert's head to the computer - and use these axes to reason about design study contributions, their suitability, and uniqueness from other approaches. The proposed methodological framework consists of 9 stages: learn, winnow, cast, discover, design, implement, deploy, reflect, and write. For each stage we provide practical guidance and outline potential pitfalls. We also conducted an extensive literature survey of related methodological approaches that involve a significant amount of qualitative field work, and compare design study methodology to that of ethnography, grounded theory, and action research.
Graphical Tests for Power Comparison of Competing Designs
Authors:
Heike Hofmann, Lendie Follett, Mahbubul Majumder, Dianne Cook
Abstract :
Lineups [4, 28] have been established as tools for visual testing similar to standard statistical inference tests, allowing us to evaluate the validity of graphical findings in an objective manner. In simulation studies [12] lineups have been shown as being efficient: the power of visual tests is comparable to classical tests while being much less stringent in terms of distributional assumptions made. This makes lineups versatile, yet powerful, tools in situations where conditions for regular statistical tests are not or cannot be met. In this paper we introduce lineups as a tool for evaluating the power of competing graphical designs. We highlight some of the theoretical properties and then show results from two studies evaluating competing designs: both studies are designed to go to the limits of our perceptual abilities to highlight differences between designs. We use both accuracy and speed of evaluation as measures of a successful design. The first study compares the choice of coordinate system: polar versus cartesian coordinates. The results show strong support in favor of cartesian coordinates in finding fast and accurate answers to spotting patterns. The second study is aimed at finding shift differences between distributions. Both studies are motivated by data problems that we have recently encountered, and explore using simulated data to evaluate the plot designs under controlled conditions. Amazon Mechanical Turk (MTurk) is used to conduct the studies. The lineups provide an effective mechanism for objectively evaluating plot designs.
INFOVIS Papers: Graphs and Networks
Session : 
Graphs and Networks
Date & Time : October 16 02:00 pm - 03:40 pm
Location : Grand Ballroom C
Chair : Nathalie Henry-Riche
Papers : 
A User Study on Curved Edges in Graph Visualization
Authors:
Kai Xu, Chris Rooney, Peter Passmore, Dong-Han Ham, Phong H. Nguyen
Abstract :
Recently there has been increasing research interest in displaying graphs with curved edges to produce more readable visualizations. While there are several automatic techniques, little has been done to evaluate their effectiveness empirically. In this paper we present two experiments studying the impact of edge curvature on graph readability. The goal is to understand the advantages and disadvantages of using curved edges for common graph tasks compared to straight line segments, which are the conventional choice for showing edges in node-link diagrams. We included several edge variations: straight edges, edges with different curvature levels, and mixed straight and curved edges. During the experiments, participants were asked to complete network tasks including determination of connectivity, shortest path, node degree, and common neighbors. We also asked the participants to provide subjective ratings of the aesthetics of different edge types. The results show significant performance differences between the straight and curved edges and clear distinctions between variations of curved edges.
Compressed Adjacency Matrices: Untangling Gene Regulatory Networks
Authors:
Kasper Dinkla, Michel A. Westenberg, Jarke J. van Wijk
Abstract :
We present a novel technique-Compressed Adjacency Matrices-for visualizing gene regulatory networks. These directed networks have strong structural characteristics: out-degrees with a scale-free distribution, in-degrees bound by a low maximum, and few and small cycles. Standard visualization techniques, such as node-link diagrams and adjacency matrices, are impeded by these network characteristics. The scale-free distribution of out-degrees causes a high number of intersecting edges in node-link diagrams. Adjacency matrices become space-inefficient due to the low in-degrees and the resulting sparse network. Compressed adjacency matrices, however, exploit these structural characteristics. By cutting open and rearranging an adjacency matrix, we achieve a compact and neatly-arranged visualization. Compressed adjacency matrices allow for easy detection of subnetworks with a specific structure, so-called motifs, which provide important knowledge about gene regulatory networks to domain experts. We summarize motifs commonly referred to in the literature, and relate them to network analysis tasks common to the visualization domain. We show that a user can easily find the important motifs in compressed adjacency matrices, and that this is hard in standard adjacency matrix and node-link diagrams. We also demonstrate that interaction techniques for standard adjacency matrices can be used for our compressed variant. These techniques include rearrangement clustering, highlighting, and filtering.
Visualizing Network Traffic to Understand the Performance of Massively Parallel Simulations
Authors:
Aaditya G. Landge, Joshua A. Levine, Katherine E. Isaacs, Abhinav Bhatele, Todd Gamblin, Martin Schu
Abstract :
The performance of massively parallel applications is often heavily impacted by the cost of communication among compute nodes. However, determining how to best use the network is a formidable task, made challenging by the ever increasing size and complexity of modern supercomputers. This paper applies visualization techniques to aid parallel application developers in understanding the network activity by enabling a detailed exploration of the flow of packets through the hardware interconnect. In order to visualize this large and complex data, we employ two linked views of the hardware network. The first is a 2D view, that represents the network structure as one of several simplified planar projections. This view is designed to allow a user to easily identify trends and patterns in the network traffic. The second is a 3D view that augments the 2D view by preserving the physical network topology and providing a context that is familiar to the application developers. Using the massively parallel multi-physics code pF3D as a case study, we demonstrate that our tool provides valuable insight that we use to explain and optimize pF3D's performance on an IBM Blue Gene/P system.
Memorability of Visual Features in Network Diagrams
Authors:
Kim Marriott, Helen Purchase, Michael Wybrow, Cagatay Goncu
Abstract :
We investigate the cognitive impact of various layout features-symmetry, alignment, collinearity, axis alignment and orthogonality-on the recall of network diagrams (graphs). This provides insight into how people internalize these diagrams and what features should or shouldn't be utilised when designing static and interactive network-based visualisations. Participants were asked to study, remember, and draw a series of small network diagrams, each drawn to emphasise a particular visual feature. The visual features were based on existing theories of perception, and the task enabled visual processing at the visceral level only. Our results strongly support the importance of visual features such as symmetry, collinearity and orthogonality, while not showing any significant impact for node-alignment or parallel edges.
Interactive Level-of-Detail Rendering of Large Graphs
Authors:
Michael Zinsmaier, Ulrik Brandes, Oliver Deussen, Hendrik Strobelt
Abstract :
We propose a technique that allows straight-line graph drawings to be rendered interactively with adjustable level of detail. The approach consists of a novel combination of edge cumulation with density-based node aggregation and is designed to exploit common graphics hardware for speed. It operates directly on graph data and does not require precomputed hierarchies or meshes. As proof of concept, we present an implementation that scales to graphs with millions of nodes and edges, and discuss several example applications.
INFOVIS Papers: Representation and Perception
Session : 
Representation and Perception
Date & Time : October 16 04:15 pm - 05:55 pm
Location : Grand Ballroom C
Chair : Enrico Bertini
Papers : 
Visual Semiotics & Uncertainty Visualization: An Empirical Study
Authors:
Alan M. MacEachren, Robert E. Roth, James O'Brien, Bonan Li, Derek Swingley, Mark Gahegan
Abstract :
This paper presents two linked empirical studies focused on uncertainty visualization. The experiments are framed from two conceptual perspectives. First, a typology of uncertainty is used to delineate kinds of uncertainty matched with space, time, and attribute components of data. Second, concepts from visual semiotics are applied to characterize the kind of visual signification that is appropriate for representing those different categories of uncertainty. This framework guided the two experiments reported here. The first addresses representation intuitiveness, considering both visual variables and iconicity of representation. The second addresses relative performance of the most intuitive abstract and iconic representations of uncertainty on a map reading task. Combined results suggest initial guidelines for representing uncertainty and discussion focuses on practical applicability of results.
Comparing Clusterings Using Bertin's Idea
Authors:
Alexander Pilhofer, Alexander Gribov, Antony Unwin
Abstract :
Classifying a set of objects into clusters can be done in numerous ways, producing different results. They can be visually compared using contingency tables [27], mosaicplots [13], fluctuation diagrams [15], tableplots [20] , (modified) parallel coordinates plots [28], Parallel Sets plots [18] or circos diagrams [19]. Unfortunately the interpretability of all these graphical displays decreases rapidly with the numbers of categories and clusterings. In his famous book A Semiology of Graphics [5] Bertin writes the discovery of an ordered concept appears as the ultimate point in logical simplification since it permits reducing to a single instant the assimilation of series which previously required many instants of study. Or in more everyday language, if you use good orderings you can see results immediately that with other orderings might take a lot of effort. This is also related to the idea of effect ordering [12], that data should be organised to reflect the effect you want to observe. This paper presents an efficient algorithm based on Bertin's idea and concepts related to Kendall's t [17], which finds informative joint orders for two or more nominal classification variables. We also show how these orderings improve the various displays and how groups of corresponding categories can be detected using a top-down partitioning algorithm. Different clusterings based on data on the environmental performance of cars sold in Germany are used for illustration. All presented methods are available in the R package extracat which is used to compute the optimized orderings for the example dataset.
Perception of Visual Variables on Tiled Wall-Sized Displays for Information Visualization Applications
Authors:
Anastasia Bezerianos, Petra Isenberg
Abstract :
We present the results of two user studies on the perception of visual variables on tiled high-resolution wall-sized displays. We contribute an understanding of, and indicators predicting how, large variations in viewing distances and viewing angles affect the accurate perception of angles, areas, and lengths. Our work, thus, helps visualization researchers with design considerations on how to create effective visualizations for these spaces. The first study showed that perception accuracy was impacted most when viewers were close to the wall but differently for each variable (Angle, Area, Length). Our second study examined the effect of perception when participants could move freely compared to when they had a static viewpoint. We found that a far but static viewpoint was as accurate but less time consuming than one that included free motion. Based on our findings, we recommend encouraging viewers to stand further back from the display when conducting perception estimation tasks. If tasks need to be conducted close to the wall display, important information should be placed directly in front of the viewer or above, and viewers should be provided with an estimation of the distortion effects predicted by our work-or encouraged to physically navigate the wall in specific ways to reduce judgement error.
Visualizing Flow of Uncertainty through Analytical Processes
Authors:
Yingcai Wu, Guo-Xun Yuan, Kwan-Liu Ma
Abstract :
Uncertainty can arise in any stage of a visual analytics process, especially in data-intensive applications with a sequence of data transformations. Additionally, throughout the process of multidimensional, multivariate data analysis, uncertainty due to data transformation and integration may split, merge, increase, or decrease. This dynamic characteristic along with other features of uncertainty pose a great challenge to effective uncertainty-aware visualization. This paper presents a new framework for modeling uncertainty and characterizing the evolution of the uncertainty information through analytical processes. Based on the framework, we have designed a visual metaphor called uncertainty flow to visually and intuitively summarize how uncertainty information propagates over the whole analysis pipeline. Our system allows analysts to interact with and analyze the uncertainty information at different levels of detail. Three experiments were conducted to demonstrate the effectiveness and intuitiveness of our design.
Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing
Authors:
Luana Micallef, Pierre Dragicevic, Jean-Daniel Fekete
Abstract :
People have difficulty understanding statistical information and are unaware of their wrong judgments, particularly in Bayesian reasoning. Psychology studies suggest that the way Bayesian problems are represented can impact comprehension, but few visual designs have been evaluated and only populations with a specific background have been involved. In this study, a textual and six visual representations for three classic problems were compared using a diverse subject pool through crowdsourcing. Visualizations included area-proportional Euler diagrams, glyph representations, and hybrid diagrams combining both. Our study failed to replicate previous findings in that subjects' accuracy was remarkably lower and visualizations exhibited no measurable benefit. A second experiment confirmed that simply adding a visualization to a textual Bayesian problem is of little help, even when the text refers to the visualization, but suggests that visualizations are more effective when the text is given without numerical values. We discuss our findings and the need for more such experiments to be carried out on heterogeneous populations of non-experts.
INFOVIS Papers: Space and Maps
Session : 
Space and Maps
Date & Time : October 17 08:30 am - 10:10 am
Location : Grand Ballroom C
Chair : Tobias Isenberg
Papers : 
Organizing Search Results with a Reference Map
Authors:
Arlind Nocaj, Ulrik Brandes
Abstract :
We propose a method to highlight query hits in hierarchically clustered collections of interrelated items such as digital libraries or knowledge bases. The method is based on the idea that organizing search results similarly to their arrangement on a fixed reference map facilitates orientation and assessment by preserving a user's mental map. Here, the reference map is built from an MDS layout of the items in a Voronoi treemap representing their hierarchical clustering, and we use techniques from dynamic graph layout to align query results with the map. The approach is illustrated on an archive of newspaper articles.
Spatial Text Visualization Using Automatic Typographic Maps
Authors:
Shehzad Afzal, Ross Maciejewski, Yun Jang, Niklas Elmqvist, David S. Ebert
Abstract :
We present a method for automatically building typographic maps that merge text and spatial data into a visual representation where text alone forms the graphical features. We further show how to use this approach to visualize spatial data such as traffic density, crime rate, or demographic data. The technique accepts a vector representation of a geographic map and spatializes the textual labels in the space onto polylines and polygons based on user-defined visual attributes and constraints. Our sample implementation runs as a Web service, spatializing shape files from the OpenStreetMap project into typographic maps for any region.
Stacking-Based Visualization of Trajectory Attribute Data
Authors:
Christian Tominski, Heidrun Schumann, Gennady Andrienko, Natalia Andrienko
Abstract :
Visualizing trajectory attribute data is challenging because it involves showing the trajectories in their spatio-temporal context as well as the attribute values associated with the individual points of trajectories. Previous work on trajectory visualization addresses selected aspects of this problem, but not all of them. We present a novel approach to visualizing trajectory attribute data. Our solution covers space, time, and attribute values. Based on an analysis of relevant visualization tasks, we designed the visualization solution around the principle of stacking trajectory bands. The core of our approach is a hybrid 2D/3D display. A 2D map serves as a reference for the spatial context, and the trajectories are visualized as stacked 3D trajectory bands along which attribute values are encoded by color. Time is integrated through appropriate ordering of bands and through a dynamic query mechanism that feeds temporally aggregated information to a circular time display. An additional 2D time graph shows temporal information in full detail by stacking 2D trajectory bands. Our solution is equipped with analytical and interactive mechanisms for selecting and ordering of trajectories, and adjusting the color mapping, as well as coordinated highlighting and dedicated 3D navigation. We demonstrate the usefulness of our novel visualization by three examples related to radiation surveillance, traffic analysis, and maritime navigation. User feedback obtained in a small experiment indicates that our hybrid 2D/3D solution can be operated quite well.
Adaptive Composite Map Projections
Authors:
Bernhard Jenny
Abstract :
All major web mapping services use the web Mercator projection. This is a poor choice for maps of the entire globe or areas of the size of continents or larger countries because the Mercator projection shows medium and higher latitudes with extreme areal distortion and provides an erroneous impression of distances and relative areas. The web Mercator projection is also not able to show the entire globe, as polar latitudes cannot be mapped. When selecting an alternative projection for information visualization, rivaling factors have to be taken into account, such as map scale, the geographic area shown, the map_s height-to-width ratio, and the type of cartographic visualization. It is impossible for a single map projection to meet the requirements for all these factors. The proposed composite map projection combines several projections that are recommended in cartographic literature and seamlessly morphs map space as the user changes map scale or the geographic region displayed. The composite projection adapts the map_s geometry to scale, to the map_s height-to-width ratio, and to the central latitude of the displayed area by replacing projections and adjusting their parameters. The composite projection shows the entire globe including poles; it portrays continents or larger countries with less distortio, optionally without areal distortion); and it can morph to the web Mercator projection for maps showing small regions.
Algorithms for Labeling Focus Regions
Authors:
Martin Fink, Jan-Henrik Haunert, Andre Schulz, Joachim Spoerhase, Alexander Wolff
Abstract :
Focus+context techniques, data clustering, mobile and ubiquitous visualization, geographic/geospatial visualization.
INFOVIS Papers: Design Spaces
Session : 
Design Spaces
Date & Time : October 17 10:30 am - 12:10 pm
Location : Grand Ballroom C
Chair : Tamara Munzner
Papers : 
Capturing the Design Space of Sequential Space-Filling Layouts
Authors:
Thomas Baudel, Bertjan Broeksema
Abstract :
We characterize the design space of the algorithms that sequentially tile a rectangular area with smaller, fixed-surface, rectangles. This space consist of five independent dimensions: Order, Size, Score, Recurse and Phrase. Each of these dimensions describe a particular aspect of such layout tasks. This class of layouts is interesting, because, beyond encompassing simple grids, tables and trees, it also includes all kinds of treemaps involving the placement of rectangles. For instance, Slice and dice, Squarified, Strip and Pivot layouts are various points in this five dimensional space. Many classic statistics visualizations, such as 100% stacked bar charts, mosaic plots and dimensional stacking, are also instances of this class. A few new and potentially interesting points in this space are introduced, such as spiral treemaps and variations on the strip layout. The core algorithm is implemented as a JavaScript prototype that can be used as a layout component in a variety of InfoViz toolkits.
Taxonomy-Based Glyph Design-with a Case Study on Visualizing Workflows of Biological Experiments
Authors:
Eamonn Maguire, Philippe Rocca-Serra, Susanna-Assunta Sansone, Jim Davies, Min Chen
Abstract :
Glyph-based visualization can offer elegant and concise presentation of multivariate information while enhancing speed and ease in visual search experienced by users. As with icon designs, glyphs are usually created based on the designers' experience and intuition, often in a spontaneous manner. Such a process does not scale well with the requirements of applications where a large number of concepts are to be encoded using glyphs. To alleviate such limitations, we propose a new systematic process for glyph design by exploring the parallel between the hierarchy of concept categorization and the ordering of discriminative capacity of visual channels. We examine the feasibility of this approach in an application where there is a pressing need for an efficient and effective means to visualize workflows of biological experiments. By processing thousands of workflow records in a public archive of biological experiments, we demonstrate that a cost-effective glyph design can be obtained by following a process of formulating a taxonomy with the aid of computation, identifying visual channels hierarchically, and defining application-specific abstraction and metaphors.
An Empirical Model of Slope Ratio Comparisons
Authors:
Justin Talbot, John Gerth, Pat Hanrahan
Abstract :
Comparing slopes is a fundamental graph reading task and the aspect ratio chosen for a plot influences how easy these comparisons are to make. According to Banking to 45 degrees, a classic design guideline first proposed and studied by Cleveland et al., aspect ratios that center slopes around 45 degrees minimize errors in visual judgments of slope ratios. This paper revisits this earlier work. Through exploratory pilot studies that expand Cleveland et al.'s experimental design, we develop an empirical model of slope ratio estimation that fits more extreme slope ratio judgments and two common slope ratio estimation strategies. We then run two experiments to validate our model. In the first, we show that our model fits more generally than the one proposed by Cleveland et al. and we find that, in general, slope ratio errors are not minimized around 45 degrees. In the second experiment, we explore a novel hypothesis raised by our model: that visible baselines can substantially mitigate errors made in slope judgments. We conclude with an application of our model to aspect ratio selection.
Representative Factor Generation for the Interactive Visual Analysis of High-Dimensional Data
Authors:
Cagatay Turkay, Arvid Lundervold, Astri Johansen Lundervold, Helwig Hauser
Abstract :
Datasets with a large number of dimensions per data item (hundreds or more) are challenging both for computational and visual analysis. Moreover, these dimensions have different characteristics and relations that result in sub-groups and/or hierarchies over the set of dimensions. Such structures lead to heterogeneity within the dimensions. Although the consideration of these structures is crucial for the analysis, most of the available analysis methods discard the heterogeneous relations among the dimensions. In this paper, we introduce the construction and utilization of representative factors for the interactive visual analysis of structures in high-dimensional datasets. First, we present a selection of methods to investigate the sub-groups in the dimension set and associate representative factors with those groups of dimensions. Second, we introduce how these factors are included in the interactive visual analysis cycle together with the original dimensions. We then provide the steps of an analytical procedure that iteratively analyzes the datasets through the use of representative factors. We discuss how our methods improve the reliability and interpretability of the analysis process by enabling more informed selections of computational tools. Finally, we demonstrate our techniques on the analysis of brain imaging study results that are performed over a large group of subjects.
Graphical Overlays: Using Layered Elements to Aid Chart Reading
Authors:
Nicholas Kong, Maneesh Agrawala
Abstract :
Reading a visualization can involve a number of tasks such as extracting, comparing or aggregating numerical values. Yet, most of the charts that are published in newspapers, reports, books, and on the Web only support a subset of these tasks. In this paper we introduce graphical overlays-visual elements that are layered onto charts to facilitate a larger set of chart reading tasks. These overlays directly support the lower-level perceptual and cognitive processes that viewers must perform to read a chart. We identify five main types of overlays that support these processes; the overlays can provide (1) reference structures such as gridlines, (2) highlights such as outlines around important marks, (3) redundant encodings such as numerical data labels, (4) summary statistics such as the mean or max and (5) annotations such as descriptive text for context. We then present an automated system that applies user-chosen graphical overlays to existing chart bitmaps. Our approach is based on the insight that generating most of these graphical overlays only requires knowing the properties of the visual marks and axes that encode the data, but does not require access to the underlying data values. Thus, our system analyzes the chart bitmap to extract only the properties necessary to generate the desired overlay. We also discuss techniques for generating interactive overlays that provide additional controls to viewers. We demonstrate several examples of each overlay type for bar, pie and line charts.
INFOVIS Papers: Text and Time
Session : 
Text and Time
Date & Time : October 18 02:00 pm - 03:40 pm
Location : Grand Ballroom C
Chair : Melanie Tory
Papers : 
Facilitating Discourse Analysis with Interactive Visualization
Authors:
Jian Zhao, Fanny Chevalier, Christopher Collins, Ravin Balakrishnan
Abstract :
A discourse parser is a natural language processing system which can represent the organization of a document based on a rhetorical structure tree-one of the key data structures enabling applications such as text summarization, question answering and dialogue generation. Computational linguistics researchers currently rely on manually exploring and comparing the discourse structures to get intuitions for improving parsing algorithms. In this paper, we present DAViewer, an interactive visualization system for assisting computational linguistics researchers to explore, compare, evaluate and annotate the results of discourse parsers. An iterative user-centered design process with domain experts was conducted in the development of DAViewer. We report the results of an informal formative study of the system to better understand how the proposed visualization and interaction techniques are used in the real research environment.
Whisper: Tracing the Spatiotemporal Process of Information Diffusion in Real Time
Authors:
Nan Cao, Yu-Ru Lin, Xiaohua Sun, David Lazer, Shixia Liu, Huamin Qu
Abstract :
When and where is an idea dispersed? Social media, like Twitter, has been increasingly used for exchanging information, opinions and emotions about events that are happening across the world. Here we propose a novel visualization design, Whisper, for tracing the process of information diffusion in social media in real time. Our design highlights three major characteristics of diffusion processes in social media: the temporal trend, social-spatial extent, and community response of a topic of interest. Such social, spatiotemporal processes are conveyed based on a sunflower metaphor whose seeds are often dispersed far away. In Whisper, we summarize the collective responses of communities on a given topic based on how tweets were retweeted by groups of users, through representing the sentiments extracted from the tweets, and tracing the pathways of retweets on a spatial hierarchical layout. We use an efficient flux line-drawing algorithm to trace multiple pathways so the temporal and spatial patterns can be identified even for a bursty event. A focused diffusion series highlights key roles such as opinion leaders in the diffusion process. We demonstrate how our design facilitates the understanding of when and where a piece of information is dispersed and what are the social responses of the crowd, for large-scale events including political campaigns and natural disasters. Initial feedback from domain experts suggests promising use for today's information consumption and dispersion in the wild.
Exploring Flow, Factors, and Outcomes of Temporal Event Sequences with the Outflow Visualization
Authors:
Krist Wongsuphasawat, David Gotz
Abstract :
Event sequence data is common in many domains, ranging from electronic medical records (EMRs) to sports events. Moreover, such sequences often result in measurable outcomes (e.g., life or death, win or loss). Collections of event sequences can be aggregated together to form event progression pathways. These pathways can then be connected with outcomes to model how alternative chains of events may lead to different results. This paper describes the Outflow visualization technique, designed to (1) aggregate multiple event sequences, (2) display the aggregate pathways through different event states with timing and cardinality, (3) summarize the pathways' corresponding outcomes, and (4) allow users to explore external factors that correlate with specific pathway state transitions. Results from a user study with twelve participants show that users were able to learn how to use Outflow easily with limited training and perform a range of tasks both accurately and rapidly.
RankExplorer: Visualization of Ranking Changes in Large Time Series Data
Authors:
Conglei Shi, Weiwei Cui, Shixia Liu, Panpan Xu, Wei Chen, Huamin Qu
Abstract :
For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.
Design Considerations for Optimizing Storyline Visualizations
Authors:
Yuzuru Tanahashi, Kwan-Liu Ma
Abstract :
Storyline visualization is a technique used to depict the temporal dynamics of social interactions. This visualization technique was first introduced as a hand-drawn illustration in XKCD's Movie Narrative Charts [21]. If properly constructed, the visualization can convey both global trends and local interactions in the data. However, previous methods for automating storyline visualizations are overly simple, failing to achieve some of the essential principles practiced by professional illustrators. This paper presents a set of design considerations for generating aesthetically pleasing and legible storyline visualizations. Our layout algorithm is based on evolutionary computation, allowing us to effectively incorporate multiple objective functions. We show that the resulting visualizations have significantly improved aesthetics and legibility compared to existing techniques.
INFOVIS Papers: Interaction
Session : 
Interaction
Date & Time : October 18 08:30 am - 10:10 am
Location : Grand Ballroom C
Chair : Miriah Meyer
Papers : 
Beyond Mouse and Keyboard: Expanding Design Considerations for Information Visualization Interactions
Authors:
Bongshin Lee, Petra Isenberg, Nathalie Henry Riche, Sheelagh Carpendale
Abstract :
The importance of interaction to Information Visualization (InfoVis) and, in particular, of the interplay between interactivity and cognition is widely recognized [12][15][32][55][70]. This interplay, combined with the demands from increasingly large and complex datasets, is driving the increased significance of interaction in InfoVis. In parallel, there have been rapid advances in many facets of interaction technologies. However, InfoVis interactions have yet to take full advantage of these new possibilities in interaction technologies, as they largely still employ the traditional desktop, mouse, and keyboard setup of WIMP (Windows, Icons, Menus, and a Pointer) interfaces. In this paper, we reflect more broadly about the role of more natural interactions for InfoVis and provide opportunities for future research. We discuss and relate general HCI interaction models to existing InfoVis interaction classifications by looking at interactions from a novel angle, taking into account the entire spectrum of interactions. Our discussion of InfoVis-specific interaction design considerations helps us identify a series of underexplored attributes of interaction that can lead to new, more natural, interaction techniques for InfoVis.
Intelligent Graph Layout Using Many Users' Input
Authors:
Xiaoru Yuan, Limei Che, Yifan Hu, Xin Zhang
Abstract :
In this paper, we propose a new strategy for graph drawing utilizing layouts of many sub-graphs supplied by a large group of people in a crowd sourcing manner. We developed an algorithm based on Laplacian constrained distance embedding to merge subgraphs submitted by different users, while attempting to maintain the topological information of the individual input layouts. To facilitate collection of layouts from many people, a light-weight interactive system has been designed to enable convenient dynamic viewing, modification and traversing between layouts. Compared with other existing graph layout algorithms, our approach can achieve more aesthetic and meaningful layouts with high user preference.
PivotPaths: Strolling through Faceted Information Spaces
Authors:
Marian Dörk, Nathalie Henry Riche, Gonzalo Ramos, Susan Dumais
Abstract :

We present PivotPaths, an interactive visualization for exploring faceted information resources. During both work and leisure, we increasingly interact with information spaces that contain multiple facets and relations, such as authors, keywords, and citations of academic publications, or actors and genres of movies. To navigate these interlinked resources today, one typically selects items from facet lists resulting in abrupt changes from one subset of data to another. While filtering is useful to retrieve results matching specific criteria, it can be difficult to see how facets and items relate and to comprehend the effect of filter operations. In contrast, the PivotPaths interface exposes faceted relations as visual paths in arrangements that invite the viewer to 'take a stroll' through an information space. PivotPaths supports pivot operations as lightweight interaction techniques that trigger gradual transitions between views. We designed the interface to allow for casual traversal of large collections in an aesthetically pleasing manner that encourages exploration and serendipitous discoveries. This paper shares the findings from our iterative design-and-evaluation process that included semi-structured interviews and a two-week deployment of PivotPaths applied to a large database of academic publications.

Interaction Support for Visual Comparison Inspired by Natural Behavior
Authors:
Christian Tominski, Camilla Forsell, Jimmy Johansson
Abstract :
Visual comparison is an intrinsic part of interactive data exploration and analysis. The literature provides a large body of existing solutions that help users accomplish comparison tasks. These solutions are mostly of visual nature and custom-made for specific data. We ask the question if a more general support is possible by focusing on the interaction aspect of comparison tasks. As an answer to this question, we propose a novel interaction concept that is inspired by real-world behavior of people comparing information printed on paper. In line with real-world interaction, our approach supports users (1) in interactively specifying pieces of graphical information to be compared, (2) in flexibly arranging these pieces on the screen, and (3) in performing the actual comparison of side-by-side and overlapping arrangements of the graphical information. Complementary visual cues and add-ons further assist users in carrying out comparison tasks. Our concept and the integrated interaction techniques are generally applicable and can be coupled with different visualization techniques. We implemented an interactive prototype and conducted a qualitative user study to assess the concept's usefulness in the context of three different visualization techniques. The obtained feedback indicates that our interaction techniques mimic the natural behavior quite well, can be learned quickly, and are easy to apply to visual comparison tasks.
RelEx: Visualization for Actively Changing Overlay Network Specifications
Authors:
Michael Sedlmair, Annika Frank, Tamara Munzner, Andreas Butz
Abstract :
We present a network visualization design study focused on supporting automotive engineers who need to specify and optimize traffic patterns for in-car communication networks. The task and data abstractions that we derived support actively making changes to an overlay network, where logical communication specifications must be mapped to an underlying physical network. These abstractions are very different from the dominant use case in visual network analysis, namely identifying clusters and central nodes, that stems from the domain of social network analysis. Our visualization tool RelEx was created and iteratively refined through a full user-centered design process that included a full problem characterization phase before tool design began, paper prototyping, iterative refinement in close collaboration with expert users for formative evaluation, deployment in the field with real analysts using their own data, usability testing with non-expert users, and summative evaluation at the end of the deployment. In the summative post-deployment study, which entailed domain experts using the tool over several weeks in their daily practice, we documented many examples where the use of RelEx simplified or sped up their work compared to previous practices.
INFOVIS Papers: Sketching and Designing Visualizations
Session : 
Sketching and Designing Visualizations
Date & Time : October 18 04:15 pm - 05:55 pm
Location : Grand Ballroom C
Chair : Caroline Ziemkiewicz
Papers : 
Evaluating the Effect of Style in Information Visualization
Authors:
Andrew Vande Moere, Martin Tomitsch, Christoph Wimmer, Christoph Boesch, Thomas Grechenig
Abstract :
This paper reports on a between-subject, comparative online study of three information visualization demonstrators that each displayed the same dataset by way of an identical scatterplot technique, yet were different in style in terms of visual and interactive embellishment. We validated stylistic adherence and integrity through a separate experiment in which a small cohort of participants assigned our three demonstrators to predefined groups of stylistic examples, after which they described the styles with their own words. From the online study, we discovered significant differences in how participants execute specific interaction operations, and the types of insights that followed from them. However, in spite of significant differences in apparent usability, enjoyability and usefulness between the style demonstrators, no variation was found on the self-reported depth, expert-rated depth, confidence or difficulty of the resulting insights. Three different methods of insight analysis have been applied, revealing how style impacts the creation of insights, ranging from higher-level pattern seeking to a more reflective and interpretative engagement with content, which is what underlies the patterns. As this study only forms the first step in determining how the impact of style in information visualization could be best evaluated, we propose several guidelines and tips on how to gather, compare and categorize insights through an online evaluation study, particularly in terms of analyzing the concise, yet wide variety of insights and observations in a trustworthy and reproducable manner.
Sketchy Rendering for Information Visualization
Authors:
Jo Wood, Petra Isenberg, Tobias Isenberg, Jason Dykes, Nadia Boukhelifa, Aidan Slingsby
Abstract :
We present and evaluate a framework for constructing sketchy style information visualizations that mimic data graphics drawn by hand. We provide an alternative renderer for the Processing graphics environment that redefines core drawing primitives including line, polygon and ellipse rendering. These primitives allow higher-level graphical features such as bar charts, line charts, treemaps and node-link diagrams to be drawn in a sketchy style with a specified degree of sketchiness. The framework is designed to be easily integrated into existing visualization implementations with minimal programming modification or design effort. We show examples of use for statistical graphics, conveying spatial imprecision and for enhancing aesthetic and narrative qualities of visualization. We evaluate user perception of sketchiness of areal features through a series of stimulus-response tests in order to assess users' ability to place sketchiness on a ratio scale, and to estimate area. Results suggest relative area judgment is compromised by sketchy rendering and that its influence is dependent on the shape being rendered. They show that degree of sketchiness may be judged on an ordinal scale but that its judgement varies strongly between individuals. We evaluate higher-level impacts of sketchiness through user testing of scenarios that encourage user engagement with data visualization and willingness to critique visualization design. Results suggest that where a visualization is clearly sketchy, engagement may be increased and that attitudes to participating in visualization annotation are more positive. The results of our work have implications for effective information visualization design that go beyond the traditional role of sketching as a tool for prototyping or its use for an indication of general uncertainty.
An Empirical Study on Using Visual Embellishments in Visualization
Authors:
Rita Borgo, Alfie Abdul-Rahman, Farhan Mohamed, Philip W. Grant, Irene Reppa, Luciano Floridi, Min C
Abstract :
In written and spoken communications, figures of speech (e.g., metaphors and synecdoche) are often used as an aid to help convey abstract or less tangible concepts. However, the benefits of using rhetorical illustrations or embellishments in visualization have so far been inconclusive. In this work, we report an empirical study to evaluate hypotheses that visual embellishments may aid memorization, visual search and concept comprehension. One major departure from related experiments in the literature is that we make use of a dualtask methodology in our experiment. This design offers an abstraction of typical situations where viewers do not have their full attention focused on visualization (e.g., in meetings and lectures). The secondary task introduces divided attention, and makes the effects of visual embellishments more observable. In addition, it also serves as additional masking in memory-based trials. The results of this study show that visual embellishments can help participants better remember the information depicted in visualization. On the other hand, visual embellishments can have a negative impact on the speed of visual search. The results show a complex pattern as to the benefits of visual embellishments in helping participants grasp key concepts from visualization.
Evaluating Sketchiness as a Visual Variable for the Depiction of Qualitative Uncertainty
Authors:
Nadia Boukhelifa, Anastasia Bezerianos, Tobias Isenberg, Jean-Daniel Fekete
Abstract :
We report on results of a series of user studies on the perception of four visual variables that are commonly used in the literature to depict uncertainty. To the best of our knowledge, we provide the first formal evaluation of the use of these variables to facilitate an easier reading of uncertainty in visualizations that rely on line graphical primitives. In addition to blur, dashing and grayscale, we investigate the use of 'sketchiness' as a visual variable because it conveys visual impreciseness that may be associated with data quality. Inspired by work in non-photorealistic rendering and by the features of hand-drawn lines, we generate line trajectories that resemble hand-drawn strokes of various levels of proficiency-ranging from child to adult strokes-where the amount of perturbations in the line corresponds to the level of uncertainty in the data. Our results show that sketchiness is a viable alternative for the visualization of uncertainty in lines and is as intuitive as blur; although people subjectively prefer dashing style over blur, grayscale and sketchiness. We discuss advantages and limitations of each technique and conclude with design considerations on how to deploy these visual variables to effectively depict various levels of uncertainty for line marks.
Understanding Pen and Touch Interaction for Data Exploration on Interactive Whiteboards
Authors:
Jagoda Walny, Bongshin Lee, Paul Johns, Nathalie Henry Riche, Sheelagh Carpendale
Abstract :
Current interfaces for common information visualizations such as bar graphs, line graphs, and scatterplots usually make use of the WIMP (Windows, Icons, Menus and a Pointer) interface paradigm with its frequently discussed problems of multiple levels of indirection via cascading menus, dialog boxes, and control panels. Recent advances in interface capabilities such as the availability of pen and touch interaction challenge us to re-think this and investigate more direct access to both the visualizations and the data they portray. We conducted a Wizard of Oz study to explore applying pen and touch interaction to the creation of information visualization interfaces on interactive whiteboards without implementing a plethora of recognizers. Our wizard acted as a robust and flexible pen and touch recognizer, giving participants maximum freedom in how they interacted with the system. Based on our qualitative analysis of the interactions our participants used, we discuss our insights about pen and touch interactions in the context of learnability and the interplay between pen and touch gestures. We conclude with suggestions for designing pen and touch enabled interactive visualization interfaces.
INFOVIS Papers: Education and Popular Applications
Session : 
Education and Popular Applications
Date & Time : October 19 08:30 am - 10:10 am
Location : Grand Ballroom C
Chair : Danyel Fisher
Papers : 
The DeepTree Exhibit: Visualizing the Tree of Life to Facilitate Informal Learning
Authors:
Florian Block, Michael S. Horn, Brenda Caldwell Phillips, Judy Diamond, E. Margaret Evans, Chia Shen
Abstract :
In this paper, we present the DeepTree exhibit, a multi-user, multi-touch interactive visualization of the Tree of Life. We developed DeepTree to facilitate collaborative learning of evolutionary concepts. We will describe an iterative process in which a team of computer scientists, learning scientists, biologists, and museum curators worked together throughout design, development, and evaluation. We present the importance of designing the interactions and the visualization hand-in-hand in order to facilitate active learning. The outcome of this process is a fractal-based tree layout that reduces visual complexity while being able to capture all life on earth; a custom rendering and navigation engine that prioritizes visual appeal and smooth fly-through; and a multi-user interface that encourages collaborative exploration while offering guided discovery. We present an evaluation showing that the large dataset encouraged free exploration, triggers emotional responses, and facilitates visitor engagement and informal learning.
Living Liquid: Design and Evaluation of an Exploratory Visualization Tool for Museum Visitors
Authors:
Joyce Ma, Isaac Liao, Kwan-Liu Ma, Jennifer Frazier
Abstract :
Interactive visualizations can allow science museum visitors to explore new worlds by seeing and interacting with scientific data. However, designing interactive visualizations for informal learning environments, such as museums, presents several challenges. First, visualizations must engage visitors on a personal level. Second, visitors often lack the background to interpret visualizations of scientific data. Third, visitors have very limited time at individual exhibits in museums. This paper examines these design considerations through the iterative development and evaluation of an interactive exhibit as a visualization tool that gives museumgoers access to scientific data generated and used by researchers. The exhibit prototype, Living Liquid, encourages visitors to ask and answer their own questions while exploring the time-varying global distribution of simulated marine microbes using a touchscreen interface. Iterative development proceeded through three rounds of formative evaluations using think-aloud protocols and interviews, each round informing a key visualization design decision: (1) what to visualize to initiate inquiry, (2) how to link data at the microscopic scale to global patterns, and (3) how to include additional data that allows visitors to pursue their own questions. Data from visitor evaluations suggests that, when designing visualizations for public audiences, one should (1) avoid distracting visitors from data that they should explore, (2) incorporate background information into the visualization, (3) favor understandability over scientific accuracy, and (4) layer data accessibility to structure inquiry. Lessons learned from this case study add to our growing understanding of how to use visualizations to actively engage learners with scientific data.
Visualizing Student Histories Using Clustering and Composition
Authors:
David Trimm, Penny Rheingans, Marie desJardins
Abstract :
While intuitive time-series visualizations exist for common datasets, student course history data is difficult to represent using traditional visualization techniques due its concurrent nature. A visual composition process is developed and applied to reveal trends across various groupings. By working closely with educators, analytic strategies and techniques are developed to leverage the visualization composition to reveal unknown trends in the data. Furthermore, clustering algorithms are developed to group common course-grade histories for further analysis. Lastly, variations of the composition process are implemented to reveal subtle differences in the underlying data. These analytic tools and techniques enabled educators to confirm expected trends and to discover new ones.
SnapShot: Visualization to Propel Ice Hockey Analytics
Authors:
Hannah Pileggi, Charles D. Stolper, J. Michael Boyle, John T. Stasko
Abstract :
Sports analysts live in a world of dynamic games flattened into tables of numbers, divorced from the rinks, pitches, and courts where they were generated. Currently, these professional analysts use R, Stata, SAS, and other statistical software packages for uncovering insights from game data. Quantitative sports consultants seek a competitive advantage both for their clients and for themselves as analytics becomes increasingly valued by teams, clubs, and squads. In order for the information visualization community to support the members of this blossoming industry, it must recognize where and how visualization can enhance the existing analytical workflow. In this paper, we identify three primary stages of today's sports analyst's routine where visualization can be beneficially integrated: 1) exploring a dataspace; 2) sharing hypotheses with internal colleagues; and 3) communicating findings to stakeholders.Working closely with professional ice hockey analysts, we designed and built SnapShot, a system to integrate visualization into the hockey intelligence gathering process. SnapShot employs a variety of information visualization techniques to display shot data, yet given the importance of a specific hockey statistic, shot length, we introduce a technique, the radial heat map. Through a user study, we received encouraging feedback from several professional analysts, both independent consultants and professional team personnel.