DevLan/vispubs huggingface dataset:
Nanocubes for Real-Time Exploration of Spatiotemporal Datasets
Authors: Lauro Didier Lins, James T. Klosowski, Carlos Scheidegger
Published at InfoVis, 2013

Consider real-time exploration of large multidimensional spatiotemporal datasets with billions of entries, each defined by a location, a time, and other attributes. Are certain attributes correlated spatially or temporally? Are there trends or outliers in the data? Answering these questions requires aggregation over arbitrary regions of the domain and attributes of the data. Many relational databases implement the well-known data cube aggregation operation, which in a sense precomputes every possible aggregate query over the database. Data cubes are sometimes assumed to take a prohibitively large amount of space, and to consequently require disk storage. In contrast, we show how to construct a data cube that fits in a modern laptop's main memory, even for billions of entries; we call this data structure a nanocube. We present algorithms to compute and query a nanocube, and show how it can be used to generate well-known visual encodings such as heatmaps, histograms, and parallel coordinate plots. When compared to exact visualizations created by scanning an entire dataset, nanocube plots have bounded screen error across a variety of scales, thanks to a hierarchical structure in space and time. We demonstrate the effectiveness of our technique on a variety of real-world datasets, and present memory, timing, and network bandwidth measurements. We find that the timings for the queries in our examples are dominated by network and user-interaction latencies.
Orthographic Star Coordinates
Authors: Dirk J. Lehmann, Holger Theisel
Published at InfoVis, 2013

Star coordinates is a popular projection technique from an nD data space to a 2D/3D visualization domain. It is defined by setting n coordinate axes in the visualization domain. Since it generally defines an affine projection, strong distortions can occur: an nD sphere can be mapped to an ellipse of arbitrary size and aspect ratio. We propose to restrict star coordinates to orthographic projections which map an nD sphere of radius r to a 2D circle of radius r. We achieve this by formulating conditions for the coordinate axes to define orthographic projections, and by running a repeated non-linear optimization in the background of every modification of the coordinate axes. This way, we define a number of orthographic interaction concepts as well as orthographic data tour sequences: a scatterplot tour, a principle component tour, and a grand tour. All concepts are illustrated and evaluated with synthetic and real data.
Perception of Average Value in Multiclass Scatterplots
Authors: Michael Gleicher, Michael Correll, Christine Nothelfer, Steven Franconeri
Published at InfoVis, 2013

The visual system can make highly efficient aggregate judgements about a set of objects, with speed roughly independent of the number of objects considered. While there is a rich literature on these mechanisms and their ramifications for visual summarization tasks, this prior work rarely considers more complex tasks requiring multiple judgements over long periods of time, and has not considered certain critical aggregation types, such as the localization of the mean value of a set of points. In this paper, we explore these questions using a common visualization task as a case study: relative mean value judgements within multi-class scatterplots. We describe how the perception literature provides a set of expected constraints on the task, and evaluate these predictions with a large-scale perceptual study with crowd-sourced participants. Judgements are no harder when each set contains more points, redundant and conflicting encodings, as well as additional sets, do not strongly affect performance, and judgements are harder when using less salient encodings. These results have concrete ramifications for the design of scatterplots.
Radial Sets: Interactive Visual Analysis of Large Overlapping Sets
Authors: Bilal Alsallakh, Wolfgang Aigner, Silvia Miksch, Helwig Hauser
Published at InfoVis, 2013

In many applications, data tables contain multi-valued attributes that often store the memberships of the table entities to multiple sets such as which languages a person masters, which skills an applicant documents, or which features a product comes with. With a growing number of entities, the resulting element-set membership matrix becomes very rich of information about how these sets overlap. Many analysis tasks targeted at set-typed data are concerned with these overlaps as salient features of such data. This paper presents Radial Sets, a novel visual technique to analyze set memberships for a large number of elements. Our technique uses frequency-based representations to enable quickly finding and analyzing different kinds of overlaps between the sets, and relating these overlaps to other attributes of the table entities. Furthermore, it enables various interactions to select elements of interest, find out if they are over-represented in specific sets or overlaps, and if they exhibit a different distribution for a specific attribute compared to the rest of the elements. These interactions allow formulating highly-expressive visual queries on the elements in terms of their set memberships and attribute values. As we demonstrate via two usage scenarios, Radial Sets enable revealing and analyzing a multitude of overlapping patterns between large sets, beyond the limits of state-of-the-art techniques.
Selecting the Aspect Ratio of a Scatter Plot Based on Its Delaunay Triangulation
Authors: Martin Fink 0001, Jan-Henrik Haunert, Joachim Spoerhase, Alexander Wolff 0001
Published at InfoVis, 2013

Scatter plots are diagrams that visualize two-dimensional data as sets of points in the plane. They allow users to detect correlations and clusters in the data. Whether or not a user can accomplish these tasks highly depends on the aspect ratio selected for the plot, i.e., the ratio between the horizontal and the vertical extent of the diagram. We argue that an aspect ratio is good if the Delaunay triangulation of the scatter plot at this aspect ratio has some nice geometric property, e.g., a large minimum angle or a small total edge length. More precisely, we consider the following optimization problem. Given a set Q of points in the plane, find a scale factor s such that scaling the x-coordinates of the points in Q by s and the y-coordinates by 1=s yields a point set P(s) that optimizes a property of the Delaunay triangulation of P(s), over all choices of s. We present an algorithm that solves this problem efficiently and demonstrate its usefulness on real-world instances. Moreover, we discuss an empirical test in which we asked 64 participants to choose the aspect ratios of 18 scatter plots. We tested six different quality measures that our algorithm can optimize. In conclusion, minimizing the total edge length and minimizing what we call the 'uncompactness' of the triangles of the Delaunay triangulation yielded the aspect ratios that were most similar to those chosen by the participants in the test.
SketchStory: Telling More Engaging Stories with Data through Freeform Sketching
Authors: Bongshin Lee, Rubaiat Habib Kazi, Greg Smith
Published at InfoVis, 2013

Presenting and communicating insights to an audience-telling a story-is one of the main goals of data exploration. Even though visualization as a storytelling medium has recently begun to gain attention, storytelling is still underexplored in information visualization and little research has been done to help people tell their stories with data. To create a new, more engaging form of storytelling with data, we leverage and extend the narrative storytelling attributes of whiteboard animation with pen and touch interactions. We present SketchStory, a data-enabled digital whiteboard that facilitates the creation of personalized and expressive data charts quickly and easily. SketchStory recognizes a small set of sketch gestures for chart invocation, and automatically completes charts by synthesizing the visuals from the presenter-provided example icon and binding them to the underlying data. Furthermore, SketchStory allows the presenter to move and resize the completed data charts with touch, and filter the underlying data to facilitate interactive exploration. We conducted a controlled experiment for both audiences and presenters to compare SketchStory with a traditional presentation system, Microsoft PowerPoint. Results show that the audience is more engaged by presentations done with SketchStory than PowerPoint. Eighteen out of 24 audience participants preferred SketchStory to PowerPoint. Four out of five presenter participants also favored SketchStory despite the extra effort required for presentation.
SoccerStories: A Kick-off for Visual Soccer Analysis
Authors: Charles Perin, Romain Vuillemot, Jean-Daniel Fekete
Published at InfoVis, 2013

This article presents SoccerStories, a visualization interface to support analysts in exploring soccer data and communicating interesting insights. Currently, most analyses on such data relate to statistics on individual players or teams. However, soccer analysts we collaborated with consider that quantitative analysis alone does not convey the right picture of the game, as context, player positions and phases of player actions are the most relevant aspects. We designed SoccerStories to support the current practice of soccer analysts and to enrich it, both in the analysis and communication stages. Our system provides an overview+detail interface of game phases, and their aggregation into a series of connected visualizations, each visualization being tailored for actions such as a series of passes or a goal attempt. To evaluate our tool, we ran two qualitative user studies on recent games using SoccerStories with data from one of the world's leading live sports data providers. The first study resulted in a series of four articles on soccer tactics, by a tactics analyst, who said he would not have been able to write these otherwise. The second study consisted in an exploratory follow-up to investigate design alternatives for embedding soccer phases into word-sized graphics. For both experiments, we received a very enthusiastic feedback and participants consider further use of SoccerStories to enhance their current workflow.
StoryFlow: Tracking the Evolution of Stories
Authors: Shixia Liu, Yingcai Wu, Enxun Wei, Mengchen Liu, Yang Liu 0014
Published at InfoVis, 2013

Storyline visualizations, which are useful in many applications, aim to illustrate the dynamic relationships between entities in a story. However, the growing complexity and scalability of stories pose great challenges for existing approaches. In this paper, we propose an efficient optimization approach to generating an aesthetically appealing storyline visualization, which effectively handles the hierarchical relationships between entities over time. The approach formulates the storyline layout as a novel hybrid optimization approach that combines discrete and continuous optimization. The discrete method generates an initial layout through the ordering and alignment of entities, and the continuous method optimizes the initial layout to produce the optimal one. The efficient approach makes real-time interactions (e.g., bundling and straightening) possible, thus enabling users to better understand and track how the story evolves. Experiments and case studies are conducted to demonstrate the effectiveness and usefulness of the optimization approach.
Understanding Interfirm Relationships in Business Ecosystems with Interactive Visualization
Authors: Rahul C. Basole, Trustin A. Clear, Mengdie Hu, Harshit Mehrotra, John T. Stasko
Published at InfoVis, 2013

Business ecosystems are characterized by large, complex, and global networks of firms, often from many different market segments, all collaborating, partnering, and competing to create and deliver new products and services. Given the rapidly increasing scale, complexity, and rate of change of business ecosystems, as well as economic and competitive pressures, analysts are faced with the formidable task of quickly understanding the fundamental characteristics of these interfirm networks. Existing tools, however, are predominantly query- or list-centric with limited interactive, exploratory capabilities. Guided by a field study of corporate analysts, we have designed and implemented dotlink360, an interactive visualization system that provides capabilities to gain systemic insight into the compositional, temporal, and connective characteristics of business ecosystems. dotlink360 consists of novel, multiple connected views enabling the analyst to explore, discover, and understand interfirm networks for a focal firm, specific market segments or countries, and the entire business ecosystem. System evaluation by a small group of prototypical users shows supporting evidence of the benefits of our approach. This design study contributes to the relatively unexplored, but promising area of exploratory information visualization in market research and business strategy.
Using Concrete Scales: A Practical Framework for Effective Visual Depiction of Complex Measures
Authors: Fanny Chevalier, Romain Vuillemot, Guia Gali
Published at InfoVis, 2013

From financial statistics to nutritional values, we are frequently exposed to quantitative information expressed in measures of either extreme magnitudes or unfamiliar units, or both. A common practice used to comprehend such complex measures is to relate, re-express, and compare them through visual depictions using magnitudes and units that are easier to grasp. Through this practice, we create a new graphic composition that we refer to as a concrete scale. To the best of our knowledge, there are no design guidelines that exist for concrete scales despite their common use in communication, educational, and decision-making settings. We attempt to fill this void by introducing a novel framework that would serve as a practical guide for their analysis and design. Informed by a thorough analysis of graphic compositions involving complex measures and an extensive literature review of scale cognition mechanisms, our framework outlines the design space of various measure relations-specifically relations involving the re-expression of complex measures to more familiar concepts-and their visual representations as graphic compositions.
Variant View: Visualizing Sequence Variants in their Gene Context
Authors: Joel A. Ferstay, Cydney B. Nielsen, Tamara Munzner
Published at InfoVis, 2013

Scientists use DNA sequence differences between an individual's genome and a standard reference genome to study the genetic basis of disease. Such differences are called sequence variants, and determining their impact in the cell is difficult because it requires reasoning about both the type and location of the variant across several levels of biological context. In this design study, we worked with four analysts to design a visualization tool supporting variant impact assessment for three different tasks. We contribute data and task abstractions for the problem of variant impact assessment, and the carefully justified design and implementation of the Variant View tool. Variant View features an information-dense visual encoding that provides maximal information at the overview level, in contrast to the extensive navigation required by currently-prevalent genome browsers. We provide initial evidence that the tool simplified and accelerated workflows for these three tasks through three case studies. Finally, we reflect on the lessons learned in creating and refining data and task abstractions that allow for concise overviews of sprawling information spaces that can reduce or remove the need for the memory-intensive use of navigation.
Visual Compression of Workflow Visualizations with Automated Detection of Macro Motifs
Authors: Eamonn Maguire, Philippe Rocca-Serra, Susanna-Assunta Sansone, Jim Davies, Min Chen 0001
Published at InfoVis, 2013

This paper is concerned with the creation of 'macros' in workflow visualization as a support tool to increase the efficiency of data curation tasks. We propose computation of candidate macros based on their usage in large collections of workflows in data repositories. We describe an efficient algorithm for extracting macro motifs from workflow graphs. We discovered that the state transition information, used to identify macro candidates, characterizes the structural pattern of the macro and can be harnessed as part of the visual design of the corresponding macro glyph. This facilitates partial automation and consistency in glyph design applicable to a large set of macro glyphs. We tested this approach against a repository of biological data holding some 9,670 workflows and found that the algorithmically generated candidate macros are in keeping with domain expert expectations.
Visual Sedimentation
Authors: Samuel Huron, Romain Vuillemot, Jean-Daniel Fekete
Published at InfoVis, 2013

We introduce Visual Sedimentation, a novel design metaphor for visualizing data streams directly inspired by the physical process of sedimentation. Visualizing data streams (e. g., Tweets, RSS, Emails) is challenging as incoming data arrive at unpredictable rates and have to remain readable. For data streams, clearly expressing chronological order while avoiding clutter, and keeping aging data visible, are important. The metaphor is drawn from the real-world sedimentation processes: objects fall due to gravity, and aggregate into strata over time. Inspired by this metaphor, data is visually depicted as falling objects using a force model to land on a surface, aggregating into strata over time. In this paper, we discuss how this metaphor addresses the specific challenge of smoothing the transition between incoming and aging data. We describe the metaphor's design space, a toolkit developed to facilitate its implementation, and example applications to a range of case studies. We then explore the generative capabilities of the design space through our toolkit. We finally illustrate creative extensions of the metaphor when applied to real streams of data.
Visualization of Shape Motions in Shape Space
Authors: Vahid Taimouri, Jing Hua 0001
Published at InfoVis, 2013

Analysis of dynamic object deformations such as cardiac motion is of great importance, especially when there is a necessity to visualize and compare the deformation behavior across subjects. However, there is a lack of effective techniques for comparative visualization and assessment of a collection of motion data due to its 4-dimensional nature, i.e., timely varying three-dimensional shapes. From the geometric point of view, the motion change can be considered as a function defined on the 2D manifold of the surface. This paper presents a novel classification and visualization method based on a medial surface shape space, in which two novel shape descriptors are defined, for discriminating normal and abnormal human heart deformations as well as localizing the abnormal motion regions. In our medial surface shape space, the geodesic distance connecting two points in the space measures the similarity between their corresponding medial surfaces, which can quantify the similarity and disparity of the 3D heart motions. Furthermore, the novel descriptors can effectively localize the inconsistently deforming myopathic regions on the left ventricle. An easy visualization of heart motion sequences on the projected space allows users to distinguish the deformation differences. Our experimental results on both synthetic and real imaging data show that this method can automatically classify the healthy and myopathic subjects and accurately detect myopathic regions on the left ventricle, which outperforms other conventional cardiac diagnostic methods.
Visualizing Change over Time Using Dynamic Hierarchies: TreeVersity2 and the StemView
Authors: John Alexis Guerra Gómez, Michael L. Pack, Catherine Plaisant, Ben Shneiderman
Published at InfoVis, 2013

To analyze data such as the US Federal Budget or characteristics of the student population of a University it is common to look for changes over time. This task can be made easier and more fruitful if the analysis is performed by grouping by attributes, such as by Agencies, Bureaus and Accounts for the Budget, or Ethnicity, Gender and Major in a University. We present TreeVersity2, a web based interactive data visualization tool that allows users to analyze change in datasets by creating dynamic hierarchies based on the data attributes. TreeVersity2 introduces a novel space filling visualization (StemView) to represent change in trees at multiple levels - not just at the leaf level. With this visualization users can explore absolute and relative changes, created and removed nodes, and each node's actual values, while maintaining the context of the tree. In addition, TreeVersity2 provides overviews of change over the entire time period, and a reporting tool that lists outliers in textual form, which helps users identify the major changes in the data without having to manually setup filters. We validated TreeVersity2 with 12 case studies with organizations as diverse as the National Cancer Institute, Federal Drug Administration, Department of Transportation, Office of the Bursar of the University of Maryland, or eBay. Our case studies demonstrated that TreeVersity2 is flexible enough to be used in different domains and provide useful insights for the data owners. A TreeVersity2 demo can be found at https://treeversity.cattlab.umd.edu.
Visualizing Fuzzy Overlapping Communities in Networks
Authors: Corinna Vehlow, Thomas Reinhardt, Daniel Weiskopf
Published at InfoVis, 2013

An important feature of networks for many application domains is their community structure. This is because objects within the same community usually have at least one property in common. The investigation of community structure can therefore support the understanding of object attributes from the network topology alone. In real-world systems, objects may belong to several communities at the same time, i.e., communities can overlap. Analyzing fuzzy community memberships is essential to understand to what extent objects contribute to different communities and whether some communities are highly interconnected. We developed a visualization approach that is based on node-link diagrams and supports the investigation of fuzzy communities in weighted undirected graphs at different levels of detail. Starting with the network of communities, the user can continuously drill down to the network of individual nodes and finally analyze the membership distribution of nodes of interest. Our approach uses layout strategies and further visual mappings to graphically encode the fuzzy community memberships. The usefulness of our approach is illustrated by two case studies analyzing networks of different domains: social networking and biological interactions. The case studies showed that our layout and visualization approach helps investigate fuzzy overlapping communities. Fuzzy vertices as well as the different communities to which they belong can be easily identified based on node color and position.