Conference stringclasses 6 values | Year int64 1.99k 2.03k | Title stringlengths 8 187 | DOI stringlengths 16 32 | Abstract stringlengths 128 7.15k ⌀ | Accessible bool 2 classes | Early bool 2 classes | AuthorNames-Deduped listlengths 1 24 | Award listlengths 0 2 | Resources listlengths 0 5 | ResourceLinks listlengths 0 10 |
|---|---|---|---|---|---|---|---|---|---|---|
CHI | 2,014 | Visualization of personal history for video navigation | 10.1145/2556288.2557106 | We present an investigation of two different visualizations of video history: Video Timeline and Video Tiles. Video Timeline extends the commonly employed list-based visualization for navigation history by applying size to indicate heuristics and occupying the full screen with a two-sided timeline. Video Tiles visualizes history items in a grid-based layout by following pre-defined templates based on items' heuristics and ordering, utilizing screen space more effectively at the expense of a clearer temporal location. The visualizations are compared against the state-of-the-art method (a filmstrip-based visualization), with ten participants tasked with sharing their previously-seen affective intervals. Our study shows that our visualizations are perceived as intuitive and both outperform and are strongly preferred to the current method. Based on these results, Video Timeline and Video Tiles provide an effective addition to video viewers to help manage the growing quantity of video. They provide users with insight into their navigation patterns, allowing them to quickly find previously-seen intervals, leading to efficient clip sharing, simpler authoring and video summarization. | false | false | [
"Abir Al Hajri",
"Gregor Miller",
"Matthew Fong",
"Sidney S. Fels"
] | [] | [] | [] |
CHI | 2,014 | Visualizing dynamic networks with matrix cubes | 10.1145/2556288.2557010 | Designing visualizations of dynamic networks is challenging, both because the data sets tend to be complex and because the tasks associated with them are often cognitively demand- ing. We introduce the Matrix Cube, a novel visual representation and navigation model for dynamic networks, inspired by the way people comprehend and manipulate physical cubes. Users can change their perspective on the data by rotating or decomposing the 3D cube. These manipulations can produce a range of different 2D visualizations that emphasize specific aspects of the dynamic network suited to particular analysis tasks. We describe Matrix Cubes and the interactions that can be performed on them in the Cubix system. We then show how two domain experts, an astronomer and a neurologist, used Cubix to explore and report on their own network data. | false | false | [
"Benjamin Bach",
"Emmanuel Pietriga",
"Jean-Daniel Fekete"
] | [] | [] | [] |
CHI | 2,014 | Visualizing interactive narratives: employing a branching comic to tell a story and show its readings | 10.1145/2556288.2557296 | This paper describes the design and evaluation of a branching comic to compare how readers recall a visual narrative when presented as an interactive, digital program, or as a linear sequence on paper. The layout of the comic is used to visualize this data as heat maps and explore patterns of users' recollections. We describe the theoretical justification for this based upon previous work in narrative visualizations, interactive stories and comics. Having tested the comic with school boys aged 11-12; we saw patterns in the data that complement other research in both interactive stories and visualizations. We argue that the heat maps helped identify these patterns, which have implications for future designs and analyses of interactive visual and/or narrative media. | false | false | [
"Daniel Andrews",
"Chris Baber"
] | [] | [] | [] |
VAST | 2,013 | A Partition-Based Framework for Building and Validating Regression Models | 10.1109/TVCG.2013.125 | Regression models play a key role in many application domains for analyzing or predicting a quantitative dependent variable based on one or more independent variables. Automated approaches for building regression models are typically limited with respect to incorporating domain knowledge in the process of selecting input variables (also known as feature subset selection). Other limitations include the identification of local structures, transformations, and interactions between variables. The contribution of this paper is a framework for building regression models addressing these limitations. The framework combines a qualitative analysis of relationship structures by visualization and a quantification of relevance for ranking any number of features and pairs of features which may be categorical or continuous. A central aspect is the local approximation of the conditional target distribution by partitioning 1D and 2D feature domains into disjoint regions. This enables a visual investigation of local patterns and largely avoids structural assumptions for the quantitative ranking. We describe how the framework supports different tasks in model building (e.g., validation and comparison), and we present an interactive workflow for feature subset selection. A real-world case study illustrates the step-wise identification of a five-dimensional model for natural gas consumption. We also report feedback from domain experts after two months of deployment in the energy sector, indicating a significant effort reduction for building and improving regression models. | false | false | [
"Thomas Mühlbacher",
"Harald Piringer"
] | [
"BP"
] | [] | [] |
VAST | 2,013 | An Extensible Framework for Provenance in Human Terrain Visual Analytics | 10.1109/TVCG.2013.132 | We describe and demonstrate an extensible framework that supports data exploration and provenance in the context of Human Terrain Analysis (HTA). Working closely with defence analysts we extract requirements and a list of features that characterise data analysed at the end of the HTA chain. From these, we select an appropriate non-classified data source with analogous features, and model it as a set of facets. We develop ProveML, an XML-based extension of the Open Provenance Model, using these facets and augment it with the structures necessary to record the provenance of data, analytical process and interpretations. Through an iterative process, we develop and refine a prototype system for Human Terrain Visual Analytics (HTVA), and demonstrate means of storing, browsing and recalling analytical provenance and process through analytic bookmarks in ProveML. We show how these bookmarks can be combined to form narratives that link back to the live data. Throughout the process, we demonstrate that through structured workshops, rapid prototyping and structured communication with intelligence analysts we are able to establish requirements, and design schema, techniques and tools that meet the requirements of the intelligence community. We use the needs and reactions of defence analysts in defining and steering the methods to validate the framework. | false | false | [
"Rick Walker",
"Aidan Slingsby",
"Jason Dykes",
"Kai Xu 0003",
"Jo Wood",
"Phong Hai Nguyen",
"Derek Stephens",
"B. L. William Wong",
"Yongjun Zheng"
] | [] | [] | [] |
VAST | 2,013 | Decision Exploration Lab: A Visual Analytics Solution for Decision Management | 10.1109/TVCG.2013.146 | We present a visual analytics solution designed to address prevalent issues in the area of Operational Decision Management (ODM). In ODM, which has its roots in Artificial Intelligence (Expert Systems) and Management Science, it is increasingly important to align business decisions with business goals. In our work, we consider decision models (executable models of the business domain) as ontologies that describe the business domain, and production rules that describe the business logic of decisions to be made over this ontology. Executing a decision model produces an accumulation of decisions made over time for individual cases. We are interested, first, to get insight in the decision logic and the accumulated facts by themselves. Secondly and more importantly, we want to see how the accumulated facts reveal potential divergences between the reality as captured by the decision model, and the reality as captured by the executed decisions. We illustrate the motivation, added value for visual analytics, and our proposed solution and tooling through a business case from the car insurance industry. | false | false | [
"Bertjan Broeksema",
"Thomas Baudel",
"Arthur G. Telea",
"Paolo Crisafulli"
] | [] | [] | [] |
VAST | 2,013 | Explainers: Expert Explorations with Crafted Projections | 10.1109/TVCG.2013.157 | This paper introduces an approach to exploration and discovery in high-dimensional data that incorporates a user's knowledge and questions to craft sets of projection functions meaningful to them. Unlike most prior work that defines projections based on their statistical properties, our approach creates projection functions that align with user-specified annotations. Therefore, the resulting derived dimensions represent concepts defined by the user's examples. These especially crafted projection functions, or explainers, can help find and explain relationships between the data variables and user-designated concepts. They can organize the data according to these concepts. Sets of explainers can provide multiple perspectives on the data. Our approach considers tradeoffs in choosing these projection functions, including their simplicity, expressive power, alignment with prior knowledge, and diversity. We provide techniques for creating collections of explainers. The methods, based on machine learning optimization frameworks, allow exploring the tradeoffs. We demonstrate our approach on model problems and applications in text analysis. | false | false | [
"Michael Gleicher"
] | [
"HM"
] | [] | [] |
VAST | 2,013 | HierarchicalTopics: Visually Exploring Large Text Collections Using Topic Hierarchies | 10.1109/TVCG.2013.162 | Analyzing large textual collections has become increasingly challenging given the size of the data available and the rate that more data is being generated. Topic-based text summarization methods coupled with interactive visualizations have presented promising approaches to address the challenge of analyzing large text corpora. As the text corpora and vocabulary grow larger, more topics need to be generated in order to capture the meaningful latent themes and nuances in the corpora. However, it is difficult for most of current topic-based visualizations to represent large number of topics without being cluttered or illegible. To facilitate the representation and navigation of a large number of topics, we propose a visual analytics system - HierarchicalTopic (HT). HT integrates a computational algorithm, Topic Rose Tree, with an interactive visual interface. The Topic Rose Tree constructs a topic hierarchy based on a list of topics. The interactive visual interface is designed to present the topic content as well as temporal evolution of topics in a hierarchical fashion. User interactions are provided for users to make changes to the topic hierarchy based on their mental model of the topic space. To qualitatively evaluate HT, we present a case study that showcases how HierarchicalTopics aid expert users in making sense of a large number of topics and discovering interesting patterns of topic groups. We have also conducted a user study to quantitatively evaluate the effect of hierarchical topic structure. The study results reveal that the HT leads to faster identification of large number of relevant topics. We have also solicited user feedback during the experiments and incorporated some suggestions into the current version of HierarchicalTopics. | false | false | [
"Wenwen Dou",
"Li Yu",
"Derek Xiaoyu Wang",
"Zhiqiang Ma 0004",
"William Ribarsky"
] | [] | [] | [] |
VAST | 2,013 | Identifying Redundancy and Exposing Provenance in Crowdsourced Data Analysis | 10.1109/TVCG.2013.164 | We present a system that lets analysts use paid crowd workers to explore data sets and helps analysts interactively examine and build upon workers' insights. We take advantage of the fact that, for many types of data, independent crowd workers can readily perform basic analysis tasks like examining views and generating explanations for trends and patterns. However, workers operating in parallel can often generate redundant explanations. Moreover, because workers have different competencies and domain knowledge, some responses are likely to be more plausible than others. To efficiently utilize the crowd's work, analysts must be able to quickly identify and consolidate redundant responses and determine which explanations are the most plausible. In this paper, we demonstrate several crowd-assisted techniques to help analysts make better use of crowdsourced explanations: (1) We explore crowd-assisted strategies that utilize multiple workers to detect redundant explanations. We introduce color clustering with representative selection-a strategy in which multiple workers cluster explanations and we automatically select the most-representative result-and show that it generates clusterings that are as good as those produced by experts. (2) We capture explanation provenance by introducing highlighting tasks and capturing workers' browsing behavior via an embedded web browser, and refine that provenance information via source-review tasks. We expose this information in an explanation-management interface that allows analysts to interactively filter and sort responses, select the most plausible explanations, and decide which to explore further. | false | false | [
"Wesley Willett",
"Shiry Ginosar",
"Avital Steinitz",
"Björn Hartmann",
"Maneesh Agrawala"
] | [] | [] | [] |
VAST | 2,013 | Interactive Exploration of Implicit and Explicit Relations in Faceted Datasets | 10.1109/TVCG.2013.167 | Many datasets, such as scientific literature collections, contain multiple heterogeneous facets which derive implicit relations, as well as explicit relational references between data items. The exploration of this data is challenging not only because of large data scales but also the complexity of resource structures and semantics. In this paper, we present PivotSlice, an interactive visualization technique which provides efficient faceted browsing as well as flexible capabilities to discover data relationships. With the metaphor of direct manipulation, PivotSlice allows the user to visually and logically construct a series of dynamic queries over the data, based on a multi-focus and multi-scale tabular view that subdivides the entire dataset into several meaningful parts with customized semantics. PivotSlice further facilitates the visual exploration and sensemaking process through features including live search and integration of online data, graphical interaction histories and smoothly animated visual state transitions. We evaluated PivotSlice through a qualitative lab study with university researchers and report the findings from our observations and interviews. We also demonstrate the effectiveness of PivotSlice using a scenario of exploring a repository of information visualization literature. | false | false | [
"Jian Zhao 0010",
"Christopher Collins 0001",
"Fanny Chevalier",
"Ravin Balakrishnan"
] | [] | [] | [] |
VAST | 2,013 | Interactive Exploration of Surveillance Video through Action Shot Summarization and Trajectory Visualization | 10.1109/TVCG.2013.168 | We propose a novel video visual analytics system for interactive exploration of surveillance video data. Our approach consists of providing analysts with various views of information related to moving objects in a video. To do this we first extract each object's movement path. We visualize each movement by (a) creating a single action shot image (a still image that coalesces multiple frames), (b) plotting its trajectory in a space-time cube and (c) displaying an overall timeline view of all the movements. The action shots provide a still view of the moving object while the path view presents movement properties such as speed and location. We also provide tools for spatial and temporal filtering based on regions of interest. This allows analysts to filter out large amounts of movement activities while the action shot representation summarizes the content of each movement. We incorporated this multi-part visual representation of moving objects in sViSIT, a tool to facilitate browsing through the video content by interactive querying and retrieval of data. Based on our interaction with security personnel who routinely interact with surveillance video data, we identified some of the most common tasks performed. This resulted in designing a user study to measure time-to-completion of the various tasks. These generally required searching for specific events of interest (targets) in videos. Fourteen different tasks were designed and a total of 120 min of surveillance video were recorded (indoor and outdoor locations recording movements of people and vehicles). The time-to-completion of these tasks were compared against a manual fast forward video browsing guided with movement detection. We demonstrate how our system can facilitate lengthy video exploration and significantly reduce browsing time to find events of interest. Reports from expert users identify positive aspects of our approach which we summarize in our recommendations for future video visual analytics systems. | false | false | [
"Amir H. Meghdadi",
"Pourang Irani"
] | [] | [] | [] |
VAST | 2,013 | MotionExplorer: Exploratory Search in Human Motion Capture Data Based on Hierarchical Aggregation | 10.1109/TVCG.2013.178 | We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions, and synthesis of motion vectors by interpolation and combination. In the practice of research and application of human motion data, challenges exist in providing visual summaries and drill-down functionality for handling large motion data collections. We find that this domain can benefit from appropriate visual retrieval and analysis support to handle these tasks in presence of large motion data. To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation, exploration, and search. Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand. We developed MotionExplorer in close collaboration with the targeted users who are researchers working on human motion synthesis and analysis, including a summative field study. Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture data with only a few mouse clicks. The researchers unanimously confirm that the system can efficiently support their work. | false | false | [
"Jürgen Bernard",
"Nils Wilhelm",
"Björn Krüger",
"Thorsten May",
"Tobias Schreck",
"Jörn Kohlhammer"
] | [] | [] | [] |
VAST | 2,013 | Open-Box Spectral Clustering: Applications to Medical Image Analysis | 10.1109/TVCG.2013.181 | Spectral clustering is a powerful and versatile technique, whose broad range of applications includes 3D image analysis. However, its practical use often involves a tedious and time-consuming process of tuning parameters and making application-specific choices. In the absence of training data with labeled clusters, help from a human analyst is required to decide the number of clusters, to determine whether hierarchical clustering is needed, and to define the appropriate distance measures, parameters of the underlying graph, and type of graph Laplacian. We propose to simplify this process via an open-box approach, in which an interactive system visualizes the involved mathematical quantities, suggests parameter values, and provides immediate feedback to support the required decisions. Our framework focuses on applications in 3D image analysis, and links the abstract high-dimensional feature space used in spectral clustering to the three-dimensional data space. This provides a better understanding of the technique, and helps the analyst predict how well specific parameter settings will generalize to similar tasks. In addition, our system supports filtering outliers and labeling the final clusters in such a way that user actions can be recorded and transferred to different data in which the same structures are to be found. Our system supports a wide range of inputs, including triangular meshes, regular grids, and point clouds. We use our system to develop segmentation protocols in chest CT and brain MRI that are then successfully applied to other datasets in an automated manner. | false | false | [
"Thomas Schultz 0001",
"Gordon L. Kindlmann"
] | [] | [] | [] |
VAST | 2,013 | ScatterBlogs2: Real-Time Monitoring of Microblog Messages through User-Guided filtering | 10.1109/TVCG.2013.186 | The number of microblog posts published daily has reached a level that hampers the effective retrieval of relevant messages, and the amount of information conveyed through services such as Twitter is still increasing. Analysts require new methods for monitoring their topic of interest, dealing with the data volume and its dynamic nature. It is of particular importance to provide situational awareness for decision making in time-critical tasks. Current tools for monitoring microblogs typically filter messages based on user-defined keyword queries and metadata restrictions. Used on their own, such methods can have drawbacks with respect to filter accuracy and adaptability to changes in trends and topic structure. We suggest ScatterBlogs2, a new approach to let analysts build task-tailored message filters in an interactive and visual manner based on recorded messages of well-understood previous events. These message filters include supervised classification and query creation backed by the statistical distribution of terms and their co-occurrences. The created filter methods can be orchestrated and adapted afterwards for interactive, visual real-time monitoring and analysis of microblog feeds. We demonstrate the feasibility of our approach for analyzing the Twitter stream in emergency management scenarios. | false | false | [
"Harald Bosch",
"Dennis Thom",
"Florian Heimerl",
"Edwin Puttmann",
"Steffen Koch 0001",
"Robert Krüger",
"Michael Wörner 0001",
"Thomas Ertl"
] | [] | [] | [] |
VAST | 2,013 | Semantics of Directly Manipulating Spatializations | 10.1109/TVCG.2013.188 | When high-dimensional data is visualized in a 2D plane by using parametric projection algorithms, users may wish to manipulate the layout of the data points to better reflect their domain knowledge or to explore alternative structures. However, few users are well-versed in the algorithms behind the visualizations, making parameter tweaking more of a guessing game than a series of decisive interactions. Translating user interactions into algorithmic input is a key component of Visual to Parametric Interaction (V2PI) [13]. Instead of adjusting parameters, users directly move data points on the screen, which then updates the underlying statistical model. However, we have found that some data points that are not moved by the user are just as important in the interactions as the data points that are moved. Users frequently move some data points with respect to some other 'unmoved' data points that they consider as spatially contextual. However, in current V2PI interactions, these points are not explicitly identified when directly manipulating the moved points. We design a richer set of interactions that makes this context more explicit, and a new algorithm and sophisticated weighting scheme that incorporates the importance of these unmoved data points into V2PI. | false | false | [
"Xinran Hu",
"Lauren Bradel",
"Dipayan Maiti",
"Leanna House",
"Chris North 0001",
"Scotland Leman"
] | [] | [] | [] |
VAST | 2,013 | SketchPadN-D: WYDIWYG Sculpting and Editing in High-Dimensional Space | 10.1109/TVCG.2013.190 | High-dimensional data visualization has been attracting much attention. To fully test related software and algorithms, researchers require a diverse pool of data with known and desired features. Test data do not always provide this, or only partially. Here we propose the paradigm WYDIWYGS (What You Draw Is What You Get). Its embodiment, SketchPad<sup>ND</sup>, is a tool that allows users to generate high-dimensional data in the same interface they also use for visualization. This provides for an immersive and direct data generation activity, and furthermore it also enables users to interactively edit and clean existing high-dimensional data from possible artifacts. SketchPad<sup>ND</sup> offers two visualization paradigms, one based on parallel coordinates and the other based on a relatively new framework using an N-D polygon to navigate in high-dimensional space. The first interface allows users to draw arbitrary profiles of probability density functions along each dimension axis and sketch shapes for data density and connections between adjacent dimensions. The second interface embraces the idea of sculpting. Users can carve data at arbitrary orientations and refine them wherever necessary. This guarantees that the data generated is truly high-dimensional. We demonstrate our tool's usefulness in real data visualization scenarios. | false | false | [
"Bing Wang 0007",
"Puripant Ruchikachorn",
"Klaus Mueller 0001"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1308.0762v1",
"icon": "paper"
}
] |
VAST | 2,013 | Space Transformation for Understanding Group Movement | 10.1109/TVCG.2013.193 | We suggest a methodology for analyzing movement behaviors of individuals moving in a group. Group movement is analyzed at two levels of granularity: the group as a whole and the individuals it comprises. For analyzing the relative positions and movements of the individuals with respect to the rest of the group, we apply space transformation, in which the trajectories of the individuals are converted from geographical space to an abstract 'group space'. The group space reference system is defined by both the position of the group center, which is taken as the coordinate origin, and the direction of the group's movement. Based on the individuals' positions mapped onto the group space, we can compare the behaviors of different individuals, determine their roles and/or ranks within the groups, and, possibly, understand how group movement is organized. The utility of the methodology has been evaluated by applying it to a set of real data concerning movements of wild social animals and discussing the results with experts in animal ethology. | false | false | [
"Natalia V. Andrienko",
"Gennady L. Andrienko",
"Louise Barrett",
"Marcus Dostie",
"S. Peter Henzi"
] | [] | [] | [] |
VAST | 2,013 | Space-Time Visual Analytics of Eye-Tracking Data for Dynamic Stimuli | 10.1109/TVCG.2013.194 | We introduce a visual analytics method to analyze eye movement data recorded for dynamic stimuli such as video or animated graphics. The focus lies on the analysis of data of several viewers to identify trends in the general viewing behavior, including time sequences of attentional synchrony and objects with strong attentional focus. By using a space-time cube visualization in combination with clustering, the dynamic stimuli and associated eye gazes can be analyzed in a static 3D representation. Shot-based, spatiotemporal clustering of the data generates potential areas of interest that can be filtered interactively. We also facilitate data drill-down: the gaze points are shown with density-based color mapping and individual scan paths as lines in the space-time cube. The analytical process is supported by multiple coordinated views that allow the user to focus on different aspects of spatial and temporal information in eye gaze data. Common eye-tracking visualization techniques are extended to incorporate the spatiotemporal characteristics of the data. For example, heat maps are extended to motion-compensated heat maps and trajectories of scan paths are included in the space-time visualization. Our visual analytics approach is assessed in a qualitative users study with expert users, which showed the usefulness of the approach and uncovered that the experts applied different analysis strategies supported by the system. | false | false | [
"Kuno Kurzhals",
"Daniel Weiskopf"
] | [] | [] | [] |
VAST | 2,013 | Supporting Awareness through Collaborative Brushing and Linking of Tabular Data | 10.1109/TVCG.2013.197 | Maintaining an awareness of collaborators' actions is critical during collaborative work, including during collaborative visualization activities. Particularly when collaborators are located at a distance, it is important to know what everyone is working on in order to avoid duplication of effort, share relevant results in a timely manner and build upon each other's results. Can a person's brushing actions provide an indication of their queries and interests in a data set? Can these actions be revealed to a collaborator without substantially disrupting their own independent work? We designed a study to answer these questions in the context of distributed collaborative visualization of tabular data. Participants in our study worked independently to answer questions about a tabular data set, while simultaneously viewing brushing actions of a fictitious collaborator, shown directly within a shared workspace. We compared three methods of presenting the collaborator's actions: brushing &amp; linking (i.e. highlighting exactly what the collaborator would see), selection (i.e. showing only a selected item), and persistent selection (i.e. showing only selected items but having them persist for some time). Our results demonstrated that persistent selection enabled some awareness of the collaborator's activities while causing minimal interference with independent work. Other techniques were less effective at providing awareness, and brushing &amp; linking caused substantial interference. These findings suggest promise for the idea of exploiting natural brushing actions to provide awareness in collaborative work. | false | false | [
"Amir Hossein Hajizadeh",
"Melanie Tory",
"Rock Leung"
] | [] | [] | [] |
VAST | 2,013 | Supporting the Visual Analysis of Dynamic Networks by Clustering associated Temporal Attributes | 10.1109/TVCG.2013.198 | The visual analysis of dynamic networks is a challenging task. In this paper, we introduce a new approach supporting the discovery of substructures sharing a similar trend over time by combining computation, visualization and interaction. With existing techniques, their discovery would be a tedious endeavor because of the number of nodes, edges as well as time points to be compared. First, on the basis of the supergraph, we therefore group nodes and edges according to their associated attributes that are changing over time. Second, the supergraph is visualized to provide an overview of the groups of nodes and edges with similar behavior over time in terms of their associated attributes. Third, we provide specific interactions to explore and refine the temporal clustering, allowing the user to further steer the analysis of the dynamic network. We demonstrate our approach by the visual analysis of a large wireless mesh network. | false | false | [
"Steffen Hadlak",
"Heidrun Schumann",
"Clemens H. Cap",
"Till Wollenberg"
] | [] | [] | [] |
VAST | 2,013 | Temporal Event Sequence Simplification | 10.1109/TVCG.2013.200 | Electronic Health Records (EHRs) have emerged as a cost-effective data source for conducting medical research. The difficulty in using EHRs for research purposes, however, is that both patient selection and record analysis must be conducted across very large, and typically very noisy datasets. Our previous work introduced EventFlow, a visualization tool that transforms an entire dataset of temporal event records into an aggregated display, allowing researchers to analyze population-level patterns and trends. As datasets become larger and more varied, however, it becomes increasingly difficult to provide a succinct, summarizing display. This paper presents a series of user-driven data simplifications that allow researchers to pare event records down to their core elements. Furthermore, we present a novel metric for measuring visual complexity, and a language for codifying disjoint strategies into an overarching simplification framework. These simplifications were used by real-world researchers to gain new and valuable insights from initially overwhelming datasets. | false | false | [
"Megan Monroe",
"Rongjian Lan",
"Hanseung Lee",
"Catherine Plaisant",
"Ben Shneiderman"
] | [
"HM"
] | [] | [] |
VAST | 2,013 | The Impact of Physical Navigation on Spatial Organization for Sensemaking | 10.1109/TVCG.2013.205 | Spatial organization has been proposed as a compelling approach to externalizing the sensemaking process. However, there are two ways in which space can be provided to the user: by creating a physical workspace that the user can interact with directly, such as can be provided by a large, high-resolution display, or through the use of a virtual workspace that the user navigates using virtual navigation techniques such as zoom and pan. In this study we explicitly examined the use of spatial sensemaking techniques within these two environments. The results demonstrate that these two approaches to providing sensemaking space are not equivalent, and that the greater embodiment afforded by the physical workspace changes how the space is perceived and used, leading to increased externalization of the sensemaking process. | false | false | [
"Christopher Andrews",
"Chris North 0001"
] | [] | [] | [] |
VAST | 2,013 | TimeBench: A Data Model and Software Library for Visual Analytics of Time-Oriented Data | 10.1109/TVCG.2013.206 | Time-oriented data play an essential role in many Visual Analytics scenarios such as extracting medical insights from collections of electronic health records or identifying emerging problems and vulnerabilities in network traffic. However, many software libraries for Visual Analytics treat time as a flat numerical data type and insufficiently tackle the complexity of the time domain such as calendar granularities and intervals. Therefore, developers of advanced Visual Analytics designs need to implement temporal foundations in their application code over and over again. We present TimeBench, a software library that provides foundational data structures and algorithms for time-oriented data in Visual Analytics. Its expressiveness and developer accessibility have been evaluated through application examples demonstrating a variety of challenges with time-oriented data and long-term developer studies conducted in the scope of research and student projects. | false | false | [
"Alexander Rind",
"Tim Lammarsch",
"Wolfgang Aigner",
"Bilal Alsallakh",
"Silvia Miksch"
] | [] | [
"PW",
"P",
"C"
] | [
{
"name": "Paper Preprint",
"url": "https://arind.media.fhstp.ac.at/preprint/PubDat_219700.pdf",
"icon": "paper"
},
{
"name": "Source Code",
"url": "https://github.com/ieg-vienna/TimeBench",
"icon": "code"
},
{
"name": "Project Website",
"url": "https://www.cvast.tuwien.ac.at/projects/timebench",
"icon": "project_website"
}
] |
VAST | 2,013 | Transformation of an Uncertain Video Search Pipeline to a Sketch-Based Visual Analytics Loop | 10.1109/TVCG.2013.207 | Traditional sketch-based image or video search systems rely on machine learning concepts as their core technology. However, in many applications, machine learning alone is impractical since videos may not be semantically annotated sufficiently, there may be a lack of suitable training data, and the search requirements of the user may frequently change for different tasks. In this work, we develop a visual analytics systems that overcomes the shortcomings of the traditional approach. We make use of a sketch-based interface to enable users to specify search requirement in a flexible manner without depending on semantic annotation. We employ active machine learning to train different analytical models for different types of search requirements. We use visualization to facilitate knowledge discovery at the different stages of visual analytics. This includes visualizing the parameter space of the trained model, visualizing the search space to support interactive browsing, visualizing candidature search results to support rapid interaction for active learning while minimizing watching videos, and visualizing aggregated information of the search results. We demonstrate the system for searching spatiotemporal attributes from sports video to identify key instances of the team and player performance. | false | false | [
"Philip A. Legg",
"David H. S. Chung",
"Matthew L. Parry",
"Rhodri Bown",
"Mark W. Jones",
"Iwan W. Griffiths",
"Min Chen 0001"
] | [] | [] | [] |
VAST | 2,013 | Using Interactive Visual Reasoning to Support Sense-Making: Implications for Design | 10.1109/TVCG.2013.211 | This research aims to develop design guidelines for systems that support investigators and analysts in the exploration and assembly of evidence and inferences. We focus here on the problem of identifying candidate 'influencers' within a community of practice. To better understand this problem and its related cognitive and interaction needs, we conducted a user study using a system called INVISQUE (INteractive Visual Search and QUery Environment) loaded with content from the ACM Digital Library. INVISQUE supports search and manipulation of results over a freeform infinite 'canvas'. The study focuses on the representations user create and their reasoning process. It also draws on some pre-established theories and frameworks related to sense-making and cognitive work in general, which we apply as a 'theoretical lenses' to consider findings and articulate solutions. Analysing the user-study data in the light of these provides some understanding of how the high-level problem of identifying key players within a domain can translate into lower-level questions and interactions. This, in turn, has informed our understanding of representation and functionality needs at a level of description which abstracts away from the specifics of the problem at hand to the class of problems of interest. We consider the study outcomes from the perspective of implications for design. | false | false | [
"Neesha Kodagoda",
"Simon Attfield",
"B. L. William Wong",
"Chris Rooney",
"Sharmin (Tinni) Choudhury"
] | [] | [] | [] |
VAST | 2,013 | UTOPIAN: User-Driven Topic Modeling Based on Interactive Nonnegative Matrix Factorization | 10.1109/TVCG.2013.212 | Topic modeling has been widely used for analyzing text document collections. Recently, there have been significant advancements in various topic modeling techniques, particularly in the form of probabilistic graphical modeling. State-of-the-art techniques such as Latent Dirichlet Allocation (LDA) have been successfully applied in visual text analytics. However, most of the widely-used methods based on probabilistic modeling have drawbacks in terms of consistency from multiple runs and empirical convergence. Furthermore, due to the complicatedness in the formulation and the algorithm, LDA cannot easily incorporate various types of user feedback. To tackle this problem, we propose a reliable and flexible visual analytics system for topic modeling called UTOPIAN (User-driven Topic modeling based on Interactive Nonnegative Matrix Factorization). Centered around its semi-supervised formulation, UTOPIAN enables users to interact with the topic modeling method and steer the result in a user-driven manner. We demonstrate the capability of UTOPIAN via several usage scenarios with real-world document corpuses such as InfoVis/VAST paper data set and product review data sets. | false | false | [
"Jaegul Choo",
"Changhyun Lee",
"Chandan K. Reddy",
"Haesun Park"
] | [] | [] | [] |
VAST | 2,013 | VAICo: Visual Analysis for Image Comparison | 10.1109/TVCG.2013.213 | Scientists, engineers, and analysts are confronted with ever larger and more complex sets of data, whose analysis poses special challenges. In many situations it is necessary to compare two or more datasets. Hence there is a need for comparative visualization tools to help analyze differences or similarities among datasets. In this paper an approach for comparative visualization for sets of images is presented. Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost. This paper introduces a new method for visualizing differences and similarities in large sets of images which preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application which allows users to rapidly explore the space of differences and drill-down on particular features. We demonstrate the flexibility of our approach by applying it to multiple distinct domains. | false | false | [
"Johanna Schmidt",
"M. Eduard Gröller",
"Stefan Bruckner"
] | [] | [] | [] |
VAST | 2,013 | Vis4Heritage: Visual Analytics Approach on Grotto Wall Painting Degradations | 10.1109/TVCG.2013.219 | For preserving the grotto wall paintings and protecting these historic cultural icons from the damage and deterioration in nature environment, a visual analytics framework and a set of tools are proposed for the discovery of degradation patterns. In comparison with the traditional analysis methods that used restricted scales, our method provides users with multi-scale analytic support to study the problems on site, cave, wall and particular degradation area scales, through the application of multidimensional visualization techniques. Several case studies have been carried out using real-world wall painting data collected from a renowned World Heritage site, to verify the usability and effectiveness of the proposed method. User studies and expert reviews were also conducted through by domain experts ranging from scientists such as microenvironment researchers, archivists, geologists, chemists, to practitioners such as conservators, restorers and curators. | false | false | [
"Jiawan Zhang",
"Kai Kang",
"Dajian Liu",
"Ye Yuan",
"E. Yanli"
] | [] | [] | [] |
VAST | 2,013 | Visual Analysis of Higher-Order Conjunctive Relationships in Multidimensional Data Using a Hypergraph Query System | 10.1109/TVCG.2013.220 | Visual exploration and analysis of multidimensional data becomes increasingly difficult with increasing dimensionality. We want to understand the relationships between dimensions of data, but lack flexible techniques for exploration beyond low-order relationships. Current visual techniques for multidimensional data analysis focus on binary conjunctive relationships between dimensions. Recent techniques, such as cross-filtering on an attribute relationship graph, facilitate the exploration of some higher-order conjunctive relationships, but require a great deal of care and precision to do so effectively. This paper provides a detailed analysis of the expressive power of existing visual querying systems and describes a more flexible approach in which users can explore n-ary conjunctive inter- and intra- dimensional relationships by interactively constructing queries as visual hypergraphs. In a hypergraph query, nodes represent subsets of values and hyperedges represent conjunctive relationships. Analysts can dynamically build and modify the query using sequences of simple interactions. The hypergraph serves not only as a query specification, but also as a compact visual representation of the interactive state. Using examples from several domains, focusing on the digital humanities, we describe the design considerations for developing the querying system and incorporating it into visual analysis tools. We analyze query expressiveness with regard to the kinds of questions it can and cannot pose, and describe how it simultaneously expands the expressiveness of and is complemented by cross-filtering. | false | false | [
"Rachel Shadoan",
"Chris E. Weaver"
] | [] | [] | [] |
VAST | 2,013 | Visual Analysis of Topic Competition on Social Media | 10.1109/TVCG.2013.221 | How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement. | false | false | [
"Panpan Xu",
"Yingcai Wu",
"Enxun Wei",
"Tai-Quan Peng",
"Shixia Liu",
"Jonathan J. H. Zhu",
"Huamin Qu"
] | [] | [] | [] |
VAST | 2,013 | Visual Analytics for Model Selection in Time Series Analysis | 10.1109/TVCG.2013.222 | Model selection in time series analysis is a challenging task for domain experts in many application areas such as epidemiology, economy, or environmental sciences. The methodology used for this task demands a close combination of human judgement and automated computation. However, statistical software tools do not adequately support this combination through interactive visual interfaces. We propose a Visual Analytics process to guide domain experts in this task. For this purpose, we developed the TiMoVA prototype that implements this process based on user stories and iterative expert feedback on user experience. The prototype was evaluated by usage scenarios with an example dataset from epidemiology and interviews with two external domain experts in statistics. The insights from the experts' feedback and the usage scenarios show that TiMoVA is able to support domain experts in model selection tasks through interactive visual interfaces with short feedback cycles. | false | false | [
"Markus Bögl",
"Wolfgang Aigner",
"Peter Filzmoser",
"Tim Lammarsch",
"Silvia Miksch",
"Alexander Rind"
] | [] | [
"PW",
"P",
"V"
] | [
{
"name": "Project Website",
"url": "https://www.cvast.tuwien.ac.at/TiMoVa",
"icon": "project_website"
},
{
"name": "Paper Preprint",
"url": "https://arind.media.fhstp.ac.at/preprint/PubDat_220251.pdf",
"icon": "paper"
},
{
"name": "Overview",
"url": "http://youtu.be/Aw5wYgcHX9I",
"icon": "video"
}
] |
VAST | 2,013 | Visual Analytics for Multimodal Social Network Analysis: A Design Study with Social Scientists | 10.1109/TVCG.2013.223 | Social network analysis (SNA) is becoming increasingly concerned not only with actors and their relations, but also with distinguishing between different types of such entities. For example, social scientists may want to investigate asymmetric relations in organizations with strict chains of command, or incorporate non-actors such as conferences and projects when analyzing coauthorship patterns. Multimodal social networks are those where actors and relations belong to different types, or modes, and multimodal social network analysis (mSNA) is accordingly SNA for such networks. In this paper, we present a design study that we conducted with several social scientist collaborators on how to support mSNA using visual analytics tools. Based on an openended, formative design process, we devised a visual representation called parallel node-link bands (PNLBs) that splits modes into separate bands and renders connections between adjacent ones, similar to the list view in Jigsaw. We then used the tool in a qualitative evaluation involving five social scientists whose feedback informed a second design phase that incorporated additional network metrics. Finally, we conducted a second qualitative evaluation with our social scientist collaborators that provided further insights on the utility of the PNLBs representation and the potential of visual analytics for mSNA. | false | false | [
"Sohaib Ghani",
"Bum Chul Kwon",
"Seungyoon Lee",
"Ji Soo Yi",
"Niklas Elmqvist"
] | [] | [] | [] |
VAST | 2,013 | Visual Analytics for Spatial Clustering: Using a Heuristic Approach for Guided Exploration | 10.1109/TVCG.2013.224 | We propose a novel approach of distance-based spatial clustering and contribute a heuristic computation of input parameters for guiding users in the search of interesting cluster constellations. We thereby combine computational geometry with interactive visualization into one coherent framework. Our approach entails displaying the results of the heuristics to users, as shown in Figure 1, providing a setting from which to start the exploration and data analysis. Addition interaction capabilities are available containing visual feedback for exploring further clustering options and is able to cope with noise in the data. We evaluate, and show the benefits of our approach on a sophisticated artificial dataset and demonstrate its usefulness on real-world data. | false | false | [
"Eli Packer",
"Peter Bak",
"Mikko Nikkilä",
"Valentin Polishchuk",
"Harold J. Ship"
] | [] | [] | [] |
VAST | 2,013 | Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Trips | 10.1109/TVCG.2013.226 | As increasing volumes of urban data are captured and become available, new opportunities arise for data-driven analysis that can lead to improvements in the lives of citizens through evidence-based decision making and policies. In this paper, we focus on a particularly important urban data set: taxi trips. Taxis are valuable sensors and information associated with taxi trips can provide unprecedented insight into many different aspects of city life, from economic activity and human behavior to mobility patterns. But analyzing these data presents many challenges. The data are complex, containing geographical and temporal components in addition to multiple variables associated with each trip. Consequently, it is hard to specify exploratory queries and to perform comparative analyses (e.g., compare different regions over time). This problem is compounded due to the size of the data-there are on average 500,000 taxi trips each day in NYC. We propose a new model that allows users to visually query taxi trips. Besides standard analytics queries, the model supports origin-destination queries that enable the study of mobility across the city. We show that this model is able to express a wide range of spatio-temporal queries, and it is also flexible in that not only can queries be composed but also different aggregations and visual representations can be applied, allowing users to explore and compare results. We have built a scalable system that implements this model which supports interactive response times; makes use of an adaptive level-of-detail rendering strategy to generate clutter-free visualization for large results; and shows hidden details to the users in a summary through the use of overlay heat maps. We present a series of case studies motivated by traffic engineers and economists that show how our model and system enable domain experts to perform tasks that were previously unattainable for them. | false | false | [
"Nivan Ferreira",
"Jorge Poco",
"Huy T. Vo",
"Juliana Freire",
"Cláudio T. Silva"
] | [
"TT"
] | [] | [] |
VAST | 2,013 | Visual Traffic Jam Analysis Based on Trajectory Data | 10.1109/TVCG.2013.228 | In this work, we present an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system. | false | false | [
"Zuchao Wang",
"Min Lu 0002",
"Xiaoru Yuan",
"Junping Zhang",
"Huub van de Wetering"
] | [] | [] | [] |
SciVis | 2,013 | A Lightweight Tangible 3D Interface for Interactive Visualization of Thin fiber Structures | 10.1109/TVCG.2013.121 | We present a prop-based, tangible interface for 3D interactive visualization of thin fiber structures. These data are commonly found in current bioimaging datasets, for example second-harmonic generation microscopy of collagen fibers in tissue. Our approach uses commodity visualization technologies such as a depth sensing camera and low-cost 3D display. Unlike most current uses of these emerging technologies in the games and graphics communities, we employ the depth sensing camera to create a fish-tank sterePoscopic virtual reality system at the scientist's desk that supports tracking of small-scale gestures with objects already found in the work space. We apply the new interface to the problem of interactive exploratory visualization of three-dimensional thin fiber data. A critical task for the visual analysis of these data is understanding patterns in fiber orientation throughout a volume.The interface enables a new, fluid style of data exploration and fiber orientation analysis by using props to provide needed passive-haptic feedback, making 3D interactions with these fiber structures more controlled. We also contribute a low-level algorithm for extracting fiber centerlines from volumetric imaging. The system was designed and evaluated with two biophotonic experts who currently use it in their lab. As compared to typical practice within their field, the new visualization system provides a more effective way to examine and understand the 3D bioimaging datasets they collect. | false | false | [
"Bret Jackson",
"Tung Yuen Lau",
"David Schroeder",
"Kimani C. Toussaint",
"Daniel F. Keefe"
] | [] | [] | [] |
SciVis | 2,013 | A Multi-Criteria Approach to Camera Motion Design for Volume Data Animation | 10.1109/TVCG.2013.123 | We present an integrated camera motion design and path generation system for building volume data animations. Creating animations is an essential task in presenting complex scientific visualizations. Existing visualization systems use an established animation function based on keyframes selected by the user. This approach is limited in providing the optimal in-between views of the data. Alternatively, computer graphics and virtual reality camera motion planning is frequently focused on collision free movement in a virtual walkthrough. For semi-transparent, fuzzy, or blobby volume data the collision free objective becomes insufficient. Here, we provide a set of essential criteria focused on computing camera paths to establish effective animations of volume data. Our dynamic multi-criteria solver coupled with a force-directed routing algorithm enables rapid generation of camera paths. Once users review the resulting animation and evaluate the camera motion, they are able to determine how each criterion impacts path generation. In this paper, we demonstrate how incorporating this animation approach with an interactive volume visualization system reduces the effort in creating context-aware and coherent animations. This frees the user to focus on visualization tasks with the objective of gaining additional insight from the volume data. | false | false | [
"Wei-Hsien Hsu",
"Yubo Zhang 0001",
"Kwan-Liu Ma"
] | [] | [] | [] |
SciVis | 2,013 | A Systematic Review on the Practice of Evaluating Visualization | 10.1109/TVCG.2013.126 | We present an assessment of the state and historic development of evaluation practices as reported in papers published at the IEEE Visualization conference. Our goal is to reflect on a meta-level about evaluation in our community through a systematic understanding of the characteristics and goals of presented evaluations. For this purpose we conducted a systematic review of ten years of evaluations in the published papers using and extending a coding scheme previously established by Lam et al. [2012]. The results of our review include an overview of the most common evaluation goals in the community, how they evolved over time, and how they contrast or align to those of the IEEE Information Visualization conference. In particular, we found that evaluations specific to assessing resulting images and algorithm performance are the most prevalent (with consistently 80-90% of all papers since 1997). However, especially over the last six years there is a steady increase in evaluation methods that include participants, either by evaluating their performances and subjective feedback or by evaluating their work practices and their improved analysis and reasoning capabilities using visual tools. Up to 2010, this trend in the IEEE Visualization conference was much more pronounced than in the IEEE Information Visualization conference which only showed an increasing percentage of evaluation through user performance and experience testing. Since 2011, however, also papers in IEEE Information Visualization show such an increase of evaluations of work practices and analysis as well as reasoning using visual tools. Further, we found that generally the studies reporting requirements analyses and domain-specific work practices are too informally reported which hinders cross-comparison and lowers external validity. | false | false | [
"Tobias Isenberg 0001",
"Petra Isenberg",
"Jian Chen 0006",
"Michael Sedlmair",
"Torsten Möller"
] | [] | [] | [] |
SciVis | 2,013 | Acuity-Driven Gigapixel Visualization | 10.1109/TVCG.2013.127 | We present a framework for acuity-driven visualization of super-high resolution image data on gigapixel displays. Tiled display walls offer a large workspace that can be navigated physically by the user. Based on head tracking information, the physical characteristics of the tiled display and the formulation of visual acuity, we guide an out-of-core gigapixel rendering scheme by delivering high levels of detail only in places where it is perceivable to the user. We apply this principle to gigapixel image rendering through adaptive level of detail selection. Additionally, we have developed an acuity-driven tessellation scheme for high-quality Focus-and-Context (F+C) lenses that significantly reduces visual artifacts while accurately capturing the underlying lens function. We demonstrate this framework on the Reality Deck, an immersive gigapixel display. We present the results of a user study designed to quantify the impact of our acuity-driven rendering optimizations in the visual exploration process. We discovered no evidence suggesting a difference in search task performance between our framework and naive rendering of gigapixel resolution data, while realizing significant benefits in terms of data transfer overhead. Additionally, we show that our acuity-driven tessellation scheme offers substantially increased frame rates when compared to naive pre-tessellation, while providing indistinguishable image quality. | false | false | [
"Charilaos Papadopoulos",
"Arie E. Kaufman"
] | [] | [] | [] |
SciVis | 2,013 | Adaptive Refinement of the Flow Map Using Sparse Samples | 10.1109/TVCG.2013.128 | We present a new efficient and scalable method for the high quality reconstruction of the flow map from sparse samples. The flow map describes the transport of massless particles along the flow. As such, it is a fundamental concept in the analysis of transient flow phenomena and all so-called Lagrangian flow visualization techniques require its approximation. The flow map is generally obtained by integrating a dense 1D, 2D, or 3D set of particles across the domain of definition of the flow. Despite its embarrassingly parallel nature, this computation creates a performance bottleneck in the analysis of large-scale datasets that existing adaptive techniques alleviate only partially. Our iterative approximation method significantly improves upon the state of the art by precisely modeling the flow behavior around automatically detected geometric structures embedded in the flow, thus effectively restricting the sampling effort to interesting regions. Our data reconstruction is based on a modified version of Sibson's scattered data interpolation and allows us at each step to offer an intermediate dense approximation of the flow map and to seamlessly integrate regions that will be further refined in subsequent steps. We present a quantitative and qualitative evaluation of our method on different types of flow datasets and offer a detailed comparison with existing techniques. | false | false | [
"Samer S. Barakat",
"Xavier Tricoche"
] | [
"HM"
] | [] | [] |
SciVis | 2,013 | Ambient Volume Scattering | 10.1109/TVCG.2013.129 | We present ambient scattering as a preintegration method for scattering on mesoscopic scales in direct volume rendering. Far-range scattering effects usually provide negligible contributions to a given location due to the exponential attenuation with increasing distance. This motivates our approach to preintegrating multiple scattering within a finite spherical region around any given sample point. To this end, we solve the full light transport with a Monte-Carlo simulation within a set of spherical regions, where each region may have different material parameters regarding anisotropy and extinction. This precomputation is independent of the data set and the transfer function, and results in a small preintegration table. During rendering, the look-up table is accessed for each ray sample point with respect to the viewing direction, phase function, and material properties in the spherical neighborhood of the sample. Our rendering technique is efficient and versatile because it readily fits in existing ray marching algorithms and can be combined with local illumination and volumetric ambient occlusion. It provides interactive volumetric scattering and soft shadows, with interactive control of the transfer function, anisotropy parameter of the phase function, lighting conditions, and viewpoint. A GPU implementation demonstrates the benefits of ambient scattering for the visualization of different types of data sets, with respect to spatial perception, high-quality illumination, translucency, and rendering speed. | false | false | [
"Marco Ament",
"Filip Sadlo",
"Daniel Weiskopf"
] | [
"HM"
] | [] | [] |
SciVis | 2,013 | An Exploration Framework to Identify and Track Movement of Cloud Systems | 10.1109/TVCG.2013.131 | We describe a framework to explore and visualize the movement of cloud systems. Using techniques from computational topology and computer vision, our framework allows the user to study this movement at various scales in space and time. Such movements could have large temporal and spatial scales such as the Madden Julian Oscillation (MJO), which has a spatial scale ranging from 1000 km to 10000 km and time of oscillation of around 40 days. Embedded within these larger scale oscillations are a hierarchy of cloud clusters which could have smaller spatial and temporal scales such as the Nakazawa cloud clusters. These smaller cloud clusters, while being part of the equatorial MJO, sometimes move at speeds different from the larger scale and in a direction opposite to that of the MJO envelope. Hitherto, one could only speculate about such movements by selectively analysing data and a priori knowledge of such systems. Our framework automatically delineates such cloud clusters and does not depend on the prior experience of the user to define cloud clusters. Analysis using our framework also shows that most tropical systems such as cyclones also contain multi-scale interactions between clouds and cloud systems. We show the effectiveness of our framework to track organized cloud system during one such rainfall event which happened at Mumbai, India in July 2005 and for cyclone Aila which occurred in Bay of Bengal during May 2009. | false | false | [
"Harish Doraiswamy",
"Vijay Natarajan",
"Ravi S. Nanjundiah"
] | [] | [] | [] |
SciVis | 2,013 | An Information-Aware Framework for Exploring Multivariate Data Sets | 10.1109/TVCG.2013.133 | Information theory provides a theoretical framework for measuring information content for an observed variable, and has attracted much attention from visualization researchers for its ability to quantify saliency and similarity among variables. In this paper, we present a new approach towards building an exploration framework based on information theory to guide the users through the multivariate data exploration process. In our framework, we compute the total entropy of the multivariate data set and identify the contribution of individual variables to the total entropy. The variables are classified into groups based on a novel graph model where a node represents a variable and the links encode the mutual information shared between the variables. The variables inside the groups are analyzed for their representativeness and an information based importance is assigned. We exploit specific information metrics to analyze the relationship between the variables and use the metrics to choose isocontours of selected variables. For a chosen group of points, parallel coordinates plots (PCP) are used to show the states of the variables and provide an interface for the user to select values of interest. Experiments with different data sets reveal the effectiveness of our proposed framework in depicting the interesting regions of the data sets taking into account the interaction among the variables. | false | false | [
"Ayan Biswas",
"Soumya Dutta",
"Han-Wei Shen",
"Jonathan Woodring"
] | [] | [] | [] |
SciVis | 2,013 | Area-Preservation Mapping using Optimal Mass Transport | 10.1109/TVCG.2013.135 | We present a novel area-preservation mapping/flattening method using the optimal mass transport technique, based on the Monge-Brenier theory. Our optimal transport map approach is rigorous and solid in theory, efficient and parallel in computation, yet general for various applications. By comparison with the conventional Monge-Kantorovich approach, our method reduces the number of variables from O(n<sup>2</sup>) to O(n), and converts the optimal mass transport problem to a convex optimization problem, which can now be efficiently carried out by Newton's method. Furthermore, our framework includes the area weighting strategy that enables users to completely control and adjust the size of areas everywhere in an accurate and quantitative way. Our method significantly reduces the complexity of the problem, and improves the efficiency, flexibility and scalability during visualization. Our framework, by combining conformal mapping and optimal mass transport mapping, serves as a powerful tool for a broad range of applications in visualization and graphics, especially for medical imaging. We provide a variety of experimental results to demonstrate the efficiency, robustness and efficacy of our novel framework. | false | false | [
"Xin Zhao 0015",
"Zhengyu Su",
"Xianfeng Gu",
"Arie E. Kaufman",
"Jian Sun 0002",
"Jie Gao 0001",
"Feng Luo 0002"
] | [] | [] | [] |
SciVis | 2,013 | Characterizing and Visualizing Predictive Uncertainty in Numerical Ensembles Through Bayesian Model Averaging | 10.1109/TVCG.2013.138 | Numerical ensemble forecasting is a powerful tool that drives many risk analysis efforts and decision making tasks. These ensembles are composed of individual simulations that each uniquely model a possible outcome for a common event of interest: e.g., the direction and force of a hurricane, or the path of travel and mortality rate of a pandemic. This paper presents a new visual strategy to help quantify and characterize a numerical ensemble's predictive uncertainty: i.e., the ability for ensemble constituents to accurately and consistently predict an event of interest based on ground truth observations. Our strategy employs a Bayesian framework to first construct a statistical aggregate from the ensemble. We extend the information obtained from the aggregate with a visualization strategy that characterizes predictive uncertainty at two levels: at a global level, which assesses the ensemble as a whole, as well as a local level, which examines each of the ensemble's constituents. Through this approach, modelers are able to better assess the predictive strengths and weaknesses of the ensemble as a whole, as well as individual models. We apply our method to two datasets to demonstrate its broad applicability. | false | false | [
"Luke J. Gosink",
"Kevin Bensema",
"Trenton Pulsipher",
"Harald Obermaier",
"Michael Henry",
"Hank Childs",
"Kenneth I. Joy"
] | [] | [] | [] |
SciVis | 2,013 | Colon Flattening Using Heat Diffusion Riemannian Metric | 10.1109/TVCG.2013.139 | We propose a new colon flattening algorithm that is efficient, shape-preserving, and robust to topological noise. Unlike previous approaches, which require a mandatory topological denoising to remove fake handles, our algorithm directly flattens the colon surface without any denoising. In our method, we replace the original Euclidean metric of the colon surface with a heat diffusion metric that is insensitive to topological noise. Using this heat diffusion metric, we then solve a Laplacian equation followed by an integration step to compute the final flattening. We demonstrate that our method is shape-preserving and the shape of the polyps are well preserved. The flattened colon also provides an efficient way to enhance the navigation and inspection in virtual colonoscopy. We further show how the existing colon registration pipeline is made more robust by using our colon flattening. We have tested our method on several colon wall surfaces and the experimental results demonstrate the robustness and the efficiency of our method. | false | false | [
"Krishna Chaitanya Gurijala",
"Rui Shi",
"Wei Zeng 0002",
"Xianfeng Gu",
"Arie E. Kaufman"
] | [] | [] | [] |
SciVis | 2,013 | Comparative Visual Analysis of Lagrangian Transport in CFD Ensembles | 10.1109/TVCG.2013.141 | Sets of simulation runs based on parameter and model variation, so-called ensembles, are increasingly used to model physical behaviors whose parameter space is too large or complex to be explored automatically. Visualization plays a key role in conveying important properties in ensembles, such as the degree to which members of the ensemble agree or disagree in their behavior. For ensembles of time-varying vector fields, there are numerous challenges for providing an expressive comparative visualization, among which is the requirement to relate the effect of individual flow divergence to joint transport characteristics of the ensemble. Yet, techniques developed for scalar ensembles are of little use in this context, as the notion of transport induced by a vector field cannot be modeled using such tools. We develop a Lagrangian framework for the comparison of flow fields in an ensemble. Our techniques evaluate individual and joint transport variance and introduce a classification space that facilitates incorporation of these properties into a common ensemble visualization. Variances of Lagrangian neighborhoods are computed using pathline integration and Principal Components Analysis. This allows for an inclusion of uncertainty measurements into the visualization and analysis approach. Our results demonstrate the usefulness and expressiveness of the presented method on several practical examples. | false | false | [
"Mathias Hummel",
"Harald Obermaier",
"Christoph Garth",
"Kenneth I. Joy"
] | [
"BP"
] | [] | [] |
SciVis | 2,013 | ConnectomeExplorer: Query-Guided Visual Analysis of Large Volumetric Neuroscience Data | 10.1109/TVCG.2013.142 | This paper presents ConnectomeExplorer, an application for the interactive exploration and query-guided visual analysis of large volumetric electron microscopy (EM) data sets in connectomics research. Our system incorporates a knowledge-based query algebra that supports the interactive specification of dynamically evaluated queries, which enable neuroscientists to pose and answer domain-specific questions in an intuitive manner. Queries are built step by step in a visual query builder, building more complex queries from combinations of simpler queries. Our application is based on a scalable volume visualization framework that scales to multiple volumes of several teravoxels each, enabling the concurrent visualization and querying of the original EM volume, additional segmentation volumes, neuronal connectivity, and additional meta data comprising a variety of neuronal data attributes. We evaluate our application on a data set of roughly one terabyte of EM data and 750 GB of segmentation data, containing over 4,000 segmented structures and 1,000 synapses. We demonstrate typical use-case scenarios of our collaborators in neuroscience, where our system has enabled them to answer specific scientific questions using interactive querying and analysis on the full-size data for the first time. | false | false | [
"Johanna Beyer",
"Ali K. Al-Awami",
"Narayanan Kasthuri",
"Jeff Lichtman",
"Hanspeter Pfister",
"Markus Hadwiger"
] | [] | [] | [] |
SciVis | 2,013 | Contour Boxplots: A Method for Characterizing Uncertainty in Feature Sets from Simulation Ensembles | 10.1109/TVCG.2013.143 | Ensembles of numerical simulations are used in a variety of applications, such as meteorology or computational solid mechanics, in order to quantify the uncertainty or possible error in a model or simulation. Deriving robust statistics and visualizing the variability of an ensemble is a challenging task and is usually accomplished through direct visualization of ensemble members or by providing aggregate representations such as an average or pointwise probabilities. In many cases, the interesting quantities in a simulation are not dense fields, but are sets of features that are often represented as thresholds on physical or derived quantities. In this paper, we introduce a generalization of boxplots, called contour boxplots, for visualization and exploration of ensembles of contours or level sets of functions. Conventional boxplots have been widely used as an exploratory or communicative tool for data analysis, and they typically show the median, mean, confidence intervals, and outliers of a population. The proposed contour boxplots are a generalization of functional boxplots, which build on the notion of data depth. Data depth approximates the extent to which a particular sample is centrally located within its density function. This produces a center-outward ordering that gives rise to the statistical quantities that are essential to boxplots. Here we present a generalization of functional data depth to contours and demonstrate methods for displaying the resulting boxplots for two-dimensional simulation data in weather forecasting and computational fluid dynamics. | false | false | [
"Ross T. Whitaker",
"Mahsa Mirzargar",
"Robert M. Kirby"
] | [
"TT"
] | [] | [] |
SciVis | 2,013 | Coupled Ensemble Flow Line Advection and Analysis | 10.1109/TVCG.2013.144 | Ensemble run simulations are becoming increasingly widespread. In this work, we couple particle advection with pathline analysis to visualize and reveal the differences among the flow fields of ensemble runs. Our method first constructs a variation field using a Lagrangian-based distance metric. The variation field characterizes the variation between vector fields of the ensemble runs, by extracting and visualizing the variation of pathlines within ensemble. Parallelism in a MapReduce style is leveraged to handle data processing and computing at scale. Using our prototype system, we demonstrate how scientists can effectively explore and investigate differences within ensemble simulations. | false | false | [
"Hanqi Guo 0001",
"Xiaoru Yuan",
"Jian Huang 0007",
"Xiaomin Zhu"
] | [] | [] | [] |
SciVis | 2,013 | Design by Dragging: An Interface for Creative Forward and Inverse Design with Simulation Ensembles | 10.1109/TVCG.2013.147 | We present an interface for exploring large design spaces as encountered in simulation-based engineering, design of visual effects, and other tasks that require tuning parameters of computationally-intensive simulations and visually evaluating results. The goal is to enable a style of design with simulations that feels as-direct-as-possible so users can concentrate on creative design tasks. The approach integrates forward design via direct manipulation of simulation inputs (e.g., geometric properties, applied forces) in the same visual space with inverse design via 'tugging' and reshaping simulation outputs (e.g., scalar fields from finite element analysis (FEA) or computational fluid dynamics (CFD)). The interface includes algorithms for interpreting the intent of users' drag operations relative to parameterized models, morphing arbitrary scalar fields output from FEA and CFD simulations, and in-place interactive ensemble visualization. The inverse design strategy can be extended to use multi-touch input in combination with an as-rigid-as-possible shape manipulation to support rich visual queries. The potential of this new design approach is confirmed via two applications: medical device engineering of a vacuum-assisted biopsy device and visual effects design using a physically based flame simulation. | false | false | [
"Dane M. Coffey",
"Chi-Lun Lin",
"Arthur G. Erdman",
"Daniel F. Keefe"
] | [
"HM"
] | [] | [] |
SciVis | 2,013 | Detecting Symmetry in Scalar fields Using Augmented Extremum Graphs | 10.1109/TVCG.2013.148 | Visualizing symmetric patterns in the data often helps the domain scientists make important observations and gain insights about the underlying experiment. Detecting symmetry in scalar fields is a nascent area of research and existing methods that detect symmetry are either not robust in the presence of noise or computationally costly. We propose a data structure called the augmented extremum graph and use it to design a novel symmetry detection method based on robust estimation of distances. The augmented extremum graph captures both topological and geometric information of the scalar field and enables robust and computationally efficient detection of symmetry. We apply the proposed method to detect symmetries in cryo-electron microscopy datasets and the experiments demonstrate that the algorithm is capable of detecting symmetry even in the presence of significant noise. We describe novel applications that use the detected symmetry to enhance visualization of scalar field data and facilitate their exploration. | false | false | [
"Dilip Mathew Thomas",
"Vijay Natarajan"
] | [] | [] | [] |
SciVis | 2,013 | Efficient Local Statistical Analysis via Integral Histograms with Discrete Wavelet Transform | 10.1109/TVCG.2013.152 | Histograms computed from local regions are commonly used in many visualization applications, and allowing the user to query histograms interactively in regions of arbitrary locations and sizes plays an important role in feature identification and tracking. Computing histograms in regions with arbitrary location and size, nevertheless, can be time consuming for large data sets since it involves expensive I/O and scan of data elements. To achieve both performance- and storage-efficient query of local histograms, we present a new algorithm called WaveletSAT, which utilizes integral histograms, an extension of the summed area tables (SAT), and discrete wavelet transform (DWT). Similar to SAT, an integral histogram is the histogram computed from the area between each grid point and the grid origin, which can be be pre-computed to support fast query. Nevertheless, because one histogram contains multiple bins, it will be very expensive to store one integral histogram at each grid point. To reduce the storage cost for large integral histograms, WaveletSAT treats the integral histograms of all grid points as multiple SATs, each of which can be converted into a sparse representation via DWT, allowing the reconstruction of axis-aligned region histograms of arbitrary sizes from a limited number of wavelet coefficients. Besides, we present an efficient wavelet transform algorithm for SATs that can operate on each grid point separately in logarithmic time complexity, which can be extended to parallel GPU-based implementation. With theoretical and empirical demonstration, we show that WaveletSAT can achieve fast preprocessing and smaller storage overhead than the conventional integral histogram approach with close query performance. | false | false | [
"Teng-Yok Lee",
"Han-Wei Shen"
] | [] | [] | [] |
SciVis | 2,013 | Evaluation of Static and Dynamic Visualization Training Approaches for Users with Different Spatial Abilities | 10.1109/TVCG.2013.156 | Conflicting results are reported in the literature on whether dynamic visualizations are more effective than static visualizations for learning and mastering 3-D tasks, and only a few investigations have considered the influence of the spatial abilities of the learners. In a study with 117 participants, we compared the benefit of static vs. dynamic visualization training tools on learners with different spatial abilities performing a typical 3-D task (specifically, creating orthographic projections of a 3-D object). We measured the spatial abilities of the participants using the Mental Rotation Test (MRT) and classified participants into two groups (high and low abilities) to examine how the participants' abilities predicted change in performance after training with static versus dynamic training tools. Our results indicate that: 1) visualization training programs can help learners to improve 3-D task performance, 2) dynamic visualizations provide no advantages over static visualizations that show intermediate steps, 3) training programs are more beneficial for individuals with low spatial abilities than for individuals with high spatial abilities, and 4) training individuals with high spatial abilities using dynamic visualizations provides little benefit. | false | false | [
"Maria-Elena Froese",
"Melanie Tory",
"Guy-Warwick Evans",
"Kedar Shrikhande"
] | [] | [] | [] |
SciVis | 2,013 | Fast Blending Scheme for Molecular Surface Representation | 10.1109/TVCG.2013.158 | Representation of molecular surfaces is a well established way to study the interaction of molecules. The state-of-theart molecular representation is the SES model, which provides a detailed surface visualization. Nevertheless, it is computationally expensive, so the less accurate Gaussian model is traditionally preferred. We introduce a novel surface representation that resembles the SES and approaches the rendering performance of the Gaussian model. Our technique is based on the iterative blending of implicit functions and avoids any pre-computation. Additionally, we propose a GPU-based ray-casting algorithm that efficiently visualize our molecular representation. A qualitative and quantitative comparison of our model with respect to the Gaussian and SES models is presented. As showcased in the paper, our technique is a valid and appealing alternative to the Gaussian representation. This is especially relevant in all the applications where the cost of the SES is prohibitive. | false | false | [
"Július Parulek",
"Andrea Brambilla"
] | [] | [] | [] |
SciVis | 2,013 | Fast Generation of Virtual X-ray Images for Reconstruction of 3D Anatomy | 10.1109/TVCG.2013.159 | We propose a novel GPU-based approach to render virtual X-ray projections of deformable tetrahedral meshes. These meshes represent the shape and the internal density distribution of a particular anatomical structure and are derived from statistical shape and intensity models (SSIMs). We apply our method to improve the geometric reconstruction of 3D anatomy (e.g. pelvic bone) from 2D X-ray images. For that purpose, shape and density of a tetrahedral mesh are varied and virtual X-ray projections are generated within an optimization process until the similarity between the computed virtual X-ray and the respective anatomy depicted in a given clinical X-ray is maximized. The OpenGL implementation presented in this work deforms and projects tetrahedral meshes of high resolution (200.000+ tetrahedra) at interactive rates. It generates virtual X-rays that accurately depict the density distribution of an anatomy of interest. Compared to existing methods that accumulate X-ray attenuation in deformable meshes, our novel approach significantly boosts the deformation/projection performance. The proposed projection algorithm scales better with respect to mesh resolution and complexity of the density distribution, and the combined deformation and projection on the GPU scales better with respect to the number of deformation parameters. The gain in performance allows for a larger number of cycles in the optimization process. Consequently, it reduces the risk of being stuck in a local optimum. We believe that our approach will improve treatments in orthopedics, where 3D anatomical information is essential. | false | false | [
"Moritz Ehlke",
"Heiko Ramm",
"Hans Lamecker",
"Hans-Christian Hege",
"Stefan Zachow"
] | [] | [] | [] |
SciVis | 2,013 | GRACE: A Visual Comparison Framework for Integrated Spatial and Non-Spatial Geriatric Data | 10.1109/TVCG.2013.161 | We present the design of a novel framework for the visual integration, comparison, and exploration of correlations in spatial and non-spatial geriatric research data. These data are in general high-dimensional and span both the spatial, volumetric domain - through magnetic resonance imaging volumes - and the non-spatial domain, through variables such as age, gender, or walking speed. The visual analysis framework blends medical imaging, mathematical analysis and interactive visualization techniques, and includes the adaptation of Sparse Partial Least Squares and iterated Tikhonov Regularization algorithms to quantify potential neurologymobility connections. A linked-view design geared specifically at interactive visual comparison integrates spatial and abstract visual representations to enable the users to effectively generate and refine hypotheses in a large, multidimensional, and fragmented space. In addition to the domain analysis and design description, we demonstrate the usefulness of this approach on two case studies. Last, we report the lessons learned through the iterative design and evaluation of our approach, in particular those relevant to the design of comparative visualization of spatial and non-spatial data. | false | false | [
"Adrian Maries",
"Nathan Mays",
"MeganOlson Hunt",
"Kim F. Wong",
"William J. Layton",
"Robert Boudreau",
"Caterina Rosano",
"G. Elisabeta Marai"
] | [] | [] | [] |
SciVis | 2,013 | Interactive Patient-Specific Vascular Modeling with Sweep Surfaces | 10.1109/TVCG.2013.169 | The precise modeling of vascular structures plays a key role in medical imaging applications, such as diagnosis, therapy planning and blood flow simulations. For the simulation of blood flow in particular, high-precision models are required to produce accurate results. It is thus common practice to perform extensive manual data polishing on vascular segmentations prior to simulation. This usually involves a complex tool chain which is highly impractical for clinical on-site application. To close this gap in current blood flow simulation pipelines, we present a novel technique for interactive vascular modeling which is based on implicit sweep surfaces. Our method is able to generate and correct smooth high-quality models based on geometric centerline descriptions on the fly. It supports complex vascular free-form contours and consequently allows for an accurate and fast modeling of pathological structures such as aneurysms or stenoses. We extend the concept of implicit sweep surfaces to achieve increased robustness and applicability as required in the medical field. We finally compare our method to existing techniques and provide case studies that confirm its contribution to current simulation pipelines. | false | false | [
"Jan Kretschmer",
"Christian Godenschwager",
"Bernhard Preim",
"Marc Stamminger"
] | [] | [] | [] |
SciVis | 2,013 | Lighting Design for Globally Illuminated Volume Rendering | 10.1109/TVCG.2013.172 | With the evolution of graphics hardware, high quality global illumination becomes available for real-time volume rendering. Compared to local illumination, global illumination can produce realistic shading effects which are closer to real world scenes, and has proven useful for enhancing volume data visualization to enable better depth and shape perception. However, setting up optimal lighting could be a nontrivial task for average users. There were lighting design works for volume visualization but they did not consider global light transportation. In this paper, we present a lighting design method for volume visualization employing global illumination. The resulting system takes into account view and transfer-function dependent content of the volume data to automatically generate an optimized three-point lighting environment. Our method fully exploits the back light which is not used by previous volume visualization systems. By also including global shadow and multiple scattering, our lighting system can effectively enhance the depth and shape perception of volumetric features of interest. In addition, we propose an automatic tone mapping operator which recovers visual details from overexposed areas while maintaining sufficient contrast in the dark areas. We show that our method is effective for visualizing volume datasets with complex structures. The structural information is more clearly and correctly presented under the automatically generated light sources. | false | false | [
"Yubo Zhang 0001",
"Kwan-Liu Ma"
] | [] | [] | [] |
SciVis | 2,013 | ManyVis: Multiple Applications in an Integrated Visualization Environment | 10.1109/TVCG.2013.174 | As the visualization field matures, an increasing number of general toolkits are developed to cover a broad range of applications. However, no general tool can incorporate the latest capabilities for all possible applications, nor can the user interfaces and workflows be easily adjusted to accommodate all user communities. As a result, users will often chose either substandard solutions presented in familiar, customized tools or assemble a patchwork of individual applications glued through ad-hoc scripts and extensive, manual intervention. Instead, we need the ability to easily and rapidly assemble the best-in-task tools into custom interfaces and workflows to optimally serve any given application community. Unfortunately, creating such meta-applications at the API or SDK level is difficult, time consuming, and often infeasible due to the sheer variety of data models, design philosophies, limits in functionality, and the use of closed commercial systems. In this paper, we present the ManyVis framework which enables custom solutions to be built both rapidly and simply by allowing coordination and communication across existing unrelated applications. ManyVis allows users to combine software tools with complementary characteristics into one virtual application driven by a single, custom-designed interface. | false | false | [
"Atul Rungta",
"Brian Summa",
"Dogan Demir",
"Peer-Timo Bremer",
"Valerio Pascucci"
] | [] | [] | [] |
SciVis | 2,013 | MObjects--A Novel Method for the Visualization and Interactive Exploration of Defects in Industrial XCT Data | 10.1109/TVCG.2013.177 | This paper describes an advanced visualization method for the analysis of defects in industrial 3D X-Ray Computed Tomography (XCT) data. We present a novel way to explore a high number of individual objects in a dataset, e.g., pores, inclusions, particles, fibers, and cracks demonstrated on the special application area of pore extraction in carbon fiber reinforced polymers (CFRP). After calculating the individual object properties volume, dimensions and shape factors, all objects are clustered into a mean object (MObject). The resulting MObject parameter space can be explored interactively. To do so, we introduce the visualization of mean object sets (MObject Sets) in a radial and a parallel arrangement. Each MObject may be split up into sub-classes by selecting a specific property, e.g., volume or shape factor, and the desired number of classes. Applying this interactive selection iteratively leads to the intended classifications and visualizations of MObjects along the selected analysis path. Hereby the given different scaling factors of the MObjects down the analysis path are visualized through a visual linking approach. Furthermore the representative MObjects are exported as volumetric datasets to serve as input for successive calculations and simulations. In the field of porosity determination in CFRP non-destructive testing practitioners use representative MObjects to improve ultrasonic calibration curves. Representative pores also serve as input for heat conduction simulations in active thermography. For a fast overview of the pore properties in a dataset we propose a local MObjects visualization in combination with a color-coded homogeneity visualization of cells. The advantages of our novel approach are demonstrated using real world CFRP specimens. The results were evaluated through a questionnaire in order to determine the practicality of the MObjects visualization as a supportive tool for domain specialists. | false | false | [
"Andreas Reh",
"Christian Gusenbauer",
"Johann Kastner",
"M. Eduard Gröller",
"Christoph Heinzl"
] | [] | [] | [] |
SciVis | 2,013 | Noise-Based Volume Rendering for the Visualization of Multivariate Volumetric Data | 10.1109/TVCG.2013.180 | Analysis of multivariate data is of great importance in many scientific disciplines. However, visualization of 3D spatially-fixed multivariate volumetric data is a very challenging task. In this paper we present a method that allows simultaneous real-time visualization of multivariate data. We redistribute the opacity within a voxel to improve the readability of the color defined by a regular transfer function, and to maintain the see-through capabilities of volume rendering. We use predictable procedural noise - random-phase Gabor noise - to generate a high-frequency redistribution pattern and construct an opacity mapping function, which allows to partition the available space among the displayed data attributes. This mapping function is appropriately filtered to avoid aliasing, while maintaining transparent regions. We show the usefulness of our approach on various data sets and with different example applications. Furthermore, we evaluate our method by comparing it to other visualization techniques in a controlled user study. Overall, the results of our study indicate that users are much more accurate in determining exact data values with our novel 3D volume visualization method. Significantly lower error rates for reading data values and high subjective ranking of our method imply that it has a high chance of being adopted for the purpose of visualization of multivariate 3D data. | false | false | [
"Rostislav Khlebnikov",
"Bernhard Kainz",
"Markus Steinberger",
"Dieter Schmalstieg"
] | [] | [] | [] |
SciVis | 2,013 | Semi-Automatic Vortex Extraction in 4D PC-MRI Cardiac Blood Flow Data using Line Predicates | 10.1109/TVCG.2013.189 | Cardiovascular diseases (CVD) are the leading cause of death worldwide. Their initiation and evolution depends strongly on the blood flow characteristics. In recent years, advances in 4D PC-MRI acquisition enable reliable and time-resolved 3D flow measuring, which allows a qualitative and quantitative analysis of the patient-specific hemodynamics. Currently, medical researchers investigate the relation between characteristic flow patterns like vortices and different pathologies. The manual extraction and evaluation is tedious and requires expert knowledge. Standardized, (semi-)automatic and reliable techniques are necessary to make the analysis of 4D PC-MRI applicable for the clinical routine. In this work, we present an approach for the extraction of vortex flow in the aorta and pulmonary artery incorporating line predicates. We provide an extensive comparison of existent vortex extraction methods to determine the most suitable vortex criterion for cardiac blood flow and apply our approach to ten datasets with different pathologies like coarctations, Tetralogy of Fallot and aneurysms. For two cases we provide a detailed discussion how our results are capable to complement existent diagnosis information. To ensure real-time feedback for the domain experts we implement our method completely on the GPU. | false | false | [
"Benjamin Köhler 0001",
"Rocco Gasteiger",
"Uta Preim",
"Holger Theisel",
"Matthias Gutberlet",
"Bernhard Preim"
] | [] | [] | [] |
SciVis | 2,013 | Uncertainty Quantification in Linear Interpolation for Isosurface Extraction | 10.1109/TVCG.2013.208 | We present a study of linear interpolation when applied to uncertain data. Linear interpolation is a key step for isosurface extraction algorithms, and the uncertainties in the data lead to non-linear variations in the geometry of the extracted isosurface. We present an approach for deriving the probability density function of a random variable modeling the positional uncertainty in the isosurface extraction. When the uncertainty is quantified by a uniform distribution, our approach provides a closed-form characterization of the mentioned random variable. This allows us to derive, in closed form, the expected value as well as the variance of the level-crossing position. While the former quantity is used for constructing a stable isosurface for uncertain data, the latter is used for visualizing the positional uncertainties in the expected isosurface level crossings on the underlying grid. | false | false | [
"Tushar M. Athawale",
"Alireza Entezari"
] | [] | [] | [] |
SciVis | 2,013 | Vessel Visualization using Curved Surface Reformation | 10.1109/TVCG.2013.215 | Visualizations of vascular structures are frequently used in radiological investigations to detect and analyze vascular diseases. Obstructions of the blood flow through a vessel are one of the main interests of physicians, and several methods have been proposed to aid the visual assessment of calcifications on vessel walls. Curved Planar Reformation (CPR) is a wide-spread method that is designed for peripheral arteries which exhibit one dominant direction. To analyze the lumen of arbitrarily oriented vessels, Centerline Reformation (CR) has been proposed. Both methods project the vascular structures into 2D image space in order to reconstruct the vessel lumen. In this paper, we propose Curved Surface Reformation (CSR), a technique that computes the vessel lumen fully in 3D. This offers high-quality interactive visualizations of vessel lumina and does not suffer from problems of earlier methods such as ambiguous visibility cues or premature discretization of centerline data. Our method maintains exact visibility information until the final query of the 3D lumina data. We also present feedback from several domain experts. | false | false | [
"Thomas Auzinger",
"Gabriel Mistelbauer",
"Ivan Baclija",
"Rüdiger Schernthaner",
"Arnold Köchl",
"Michael Wimmer 0001",
"M. Eduard Gröller",
"Stefan Bruckner"
] | [] | [] | [] |
SciVis | 2,013 | Visualization of Morse Connection Graphs for Topologically Rich 2D Vector fields | 10.1109/TVCG.2013.229 | Recent advances in vector field topologymake it possible to compute its multi-scale graph representations for autonomous 2D vector fields in a robust and efficient manner. One of these representations is a Morse Connection Graph (MCG), a directed graph whose nodes correspond to Morse sets, generalizing stationary points and periodic trajectories, and arcs - to trajectories connecting them. While being useful for simple vector fields, the MCG can be hard to comprehend for topologically rich vector fields, containing a large number of features. This paper describes a visual representation of the MCG, inspired by previous work on graph visualization. Our approach aims to preserve the spatial relationships between the MCG arcs and nodes and highlight the coherent behavior of connecting trajectories. Using simulations of ocean flow, we show that it can provide useful information on the flow structure. This paper focuses specifically on MCGs computed for piecewise constant (PC) vector fields. In particular, we describe extensions of the PC framework that make it more flexible and better suited for analysis of data on complex shaped domains with a boundary. We also describe a topology simplification scheme that makes our MCG visualizations less ambiguous. Despite the focus on the PC framework, our approach could also be applied to graph representations or topological skeletons computed using different methods. | false | false | [
"Andrzej Szymczak",
"Levente Sipeki"
] | [] | [] | [] |
InfoVis | 2,013 | A Deeper Understanding of Sequence in Narrative Visualization | 10.1109/TVCG.2013.119 | Conveying a narrative with visualizations often requires choosing an order in which to present visualizations. While evidence exists that narrative sequencing in traditional stories can affect comprehension and memory, little is known about how sequencing choices affect narrative visualization. We consider the forms and reactions to sequencing in narrative visualization presentations to provide a deeper understanding with a focus on linear, 'slideshow-style' presentations. We conduct a qualitative analysis of 42 professional narrative visualizations to gain empirical knowledge on the forms that structure and sequence take. Based on the results of this study we propose a graph-driven approach for automatically identifying effective sequences in a set of visualizations to be presented linearly. Our approach identifies possible transitions in a visualization set and prioritizes local (visualization-to-visualization) transitions based on an objective function that minimizes the cost of transitions from the audience perspective. We conduct two studies to validate this function. We also expand the approach with additional knowledge of user preferences for different types of local transitions and the effects of global sequencing strategies on memory, preference, and comprehension. Our results include a relative ranking of types of visualization transitions by the audience perspective and support for memory and subjective rating benefits of visualization sequences that use parallelism as a structural device. We discuss how these insights can guide the design of narrative visualization and systems that support optimization of visualization sequence. | false | false | [
"Jessica Hullman",
"Steven Mark Drucker",
"Nathalie Henry Riche",
"Bongshin Lee",
"Danyel Fisher",
"Eytan Adar"
] | [] | [] | [] |
InfoVis | 2,013 | A Design Space of Visualization Tasks | 10.1109/TVCG.2013.120 | Knowledge about visualization tasks plays an important role in choosing or building suitable visual representations to pursue them. Yet, tasks are a multi-faceted concept and it is thus not surprising that the many existing task taxonomies and models all describe different aspects of tasks, depending on what these task descriptions aim to capture. This results in a clear need to bring these different aspects together under the common hood of a general design space of visualization tasks, which we propose in this paper. Our design space consists of five design dimensions that characterize the main aspects of tasks and that have so far been distributed across different task descriptions. We exemplify its concrete use by applying our design space in the domain of climate impact research. To this end, we propose interfaces to our design space for different user roles (developers, authors, and end users) that allow users of different levels of expertise to work with it. | false | false | [
"Hans-Jörg Schulz",
"Thomas Nocke",
"Magnus Heitzler",
"Heidrun Schumann"
] | [] | [] | [] |
InfoVis | 2,013 | A Model for Structure-Based Comparison of Many Categories in Small-Multiple Displays | 10.1109/TVCG.2013.122 | Many application domains deal with multi-variate data that consist of both categorical and numerical information. Small-multiple displays are a powerful concept for comparing such data by juxtaposition. For comparison by overlay or by explicit encoding of computed differences, however, a specification of references is necessary. In this paper, we present a formal model for defining semantically meaningful comparisons between many categories in a small-multiple display. Based on pivotized data that are hierarchically partitioned by the categories assigned to the x and y axis of the display, we propose two alternatives for structure-based comparison within this hierarchy. With an absolute reference specification, categories are compared to a fixed reference category. With a relative reference specification, in contrast, a semantic ordering of the categories is considered when comparing them either to the previous or subsequent category each. Both reference specifications can be defined at multiple levels of the hierarchy (including aggregated summaries), enabling a multitude of useful comparisons. We demonstrate the general applicability of our model in several application examples using different visualizations that compare data by overlay or explicit encoding of differences. | false | false | [
"Johannes Kehrer",
"Harald Piringer",
"Wolfgang Berger",
"M. Eduard Gröller"
] | [] | [] | [] |
InfoVis | 2,013 | A Multi-Level Typology of Abstract Visualization Tasks | 10.1109/TVCG.2013.124 | The considerable previous work characterizing visualization usage has focused on low-level tasks or interactions and high-level tasks, leaving a gap between them that is not addressed. This gap leads to a lack of distinction between the ends and means of a task, limiting the potential for rigorous analysis. We contribute a multi-level typology of visualization tasks to address this gap, distinguishing why and how a visualization task is performed, as well as what the task inputs and outputs are. Our typology allows complex tasks to be expressed as sequences of interdependent simpler tasks, resulting in concise and flexible descriptions for tasks of varying complexity and scope. It provides abstract rather than domain-specific descriptions of tasks, so that useful comparisons can be made between visualization systems targeted at different application domains. This descriptive power supports a level of analysis required for the generation of new designs, by guiding the translation of domain-specific problems into abstract tasks, and for the qualitative evaluation of visualization usage. We demonstrate the benefits of our approach in a detailed case study, comparing task descriptions from our typology to those derived from related work. We also discuss the similarities and differences between our typology and over two dozen extant classification systems and theoretical frameworks from the literatures of visualization, human-computer interaction, information retrieval, communications, and cartography. | false | false | [
"Matthew Brehmer",
"Tamara Munzner"
] | [
"TT"
] | [] | [] |
InfoVis | 2,013 | An Empirically-Derived Taxonomy of Interaction Primitives for Interactive Cartography and Geovisualization | 10.1109/TVCG.2013.130 | Proposals to establish a 'science of interaction' have been forwarded from Information Visualization and Visual Analytics, as well as Cartography, Geovisualization, and GIScience. This paper reports on two studies to contribute to this call for an interaction science, with the goal of developing a functional taxonomy of interaction primitives for map-based visualization. A semi-structured interview study first was conducted with 21 expert interactive map users to understand the way in which map-based visualizations currently are employed. The interviews were transcribed and coded to identify statements representative of either the task the user wished to accomplish (i.e., objective primitives) or the interactive functionality included in the visualization to achieve this task (i.e., operator primitives). A card sorting study then was conducted with 15 expert interactive map designers to organize these example statements into logical structures based on their experience translating client requests into interaction designs. Example statements were supplemented with primitive definitions in the literature and were separated into two sorting exercises: objectives and operators. The objective sort suggested five objectives that increase in cognitive sophistication (identify, compare, rank, associate, & delineate), but exhibited a large amount of variation across participants due to consideration of broader user goals (procure, predict, & prescribe) and interaction operands (space-alone, attributes-in-space, & space-in-time; elementary & general). The operator sort suggested five enabling operators (import, export, save, edit, & annotate) and twelve work operators (reexpress, arrange, sequence, resymbolize, overlay, pan, zoom, reproject, search, filter, retrieve, & calculate). This taxonomy offers an empirically-derived and ecologically-valid structure to inform future research and design on interaction. | false | false | [
"Robert E. Roth"
] | [] | [] | [] |
InfoVis | 2,013 | An Interaction Model for Visualizations Beyond The Desktop | 10.1109/TVCG.2013.134 | We present an interaction model for beyond-desktop visualizations that combines the visualization reference model with the instrumental interaction paradigm. Beyond-desktop visualizations involve a wide range of emerging technologies such as wall-sized displays, 3D and shape-changing displays, touch and tangible input, and physical information visualizations. While these technologies allow for new forms of interaction, they are often studied in isolation. New conceptual models are needed to build a coherent picture of what has been done and what is possible. We describe a modified pipeline model where raw data is processed into a visualization and then rendered into the physical world. Users can explore or change data by directly manipulating visualizations or through the use of instruments. Interactions can also take place in the physical world outside the visualization system, such as when using locomotion to inspect a large scale visualization. Through case studies we illustrate how this model can be used to describe both conventional and unconventional interactive visualization systems, and compare different design alternatives. | false | false | [
"Yvonne Jansen",
"Pierre Dragicevic"
] | [] | [] | [] |
InfoVis | 2,013 | Automatic Layout of Structured Hierarchical Reports | 10.1109/TVCG.2013.137 | Domain-specific database applications tend to contain a sizable number of table-, form-, and report-style views that must each be designed and maintained by a software developer. A significant part of this job is the necessary tweaking of low-level presentation details such as label placements, text field dimensions, list or table styles, and so on. In this paper, we present a horizontally constrained layout management algorithm that automates the display of structured hierarchical data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. We compare our system with pure outline and nested table layouts with respect to space efficiency and readability, the latter with an online user study on 27 subjects. Our layouts are 3.9 and 1.6 times more compact on average than outline layouts and horizontally unconstrained table layouts, respectively, and are as readable as table layouts even for large datasets. | false | false | [
"Eirik Bakke",
"David R. Karger",
"Rob Miller 0001"
] | [] | [] | [] |
InfoVis | 2,013 | Common Angle Plots as Perception-True Visualizations of Categorical Associations | 10.1109/TVCG.2013.140 | Visualizations are great tools of communications-they summarize findings and quickly convey main messages to our audience. As designers of charts we have to make sure that information is shown with a minimum of distortion. We have to also consider illusions and other perceptual limitations of our audience. In this paper we discuss the effect and strength of the line width illusion, a Muller-Lyer type illusion, on designs related to displaying associations between categorical variables. Parallel sets and hammock plots are both affected by line width illusions. We introduce the common-angle plot as an alternative method for displaying categorical data in a manner that minimizes the effect from perceptual illusions. Results from user studies both highlight the need for addressing line-width illusions in displays and provide evidence that common angle charts successfully resolve this issue. | false | false | [
"Heike Hofmann",
"Marie Vendettuoli"
] | [] | [] | [] |
InfoVis | 2,013 | Creative User-Centered Visualization Design for Energy Analysts and Modelers | 10.1109/TVCG.2013.145 | We enhance a user-centered design process with techniques that deliberately promote creativity to identify opportunities for the visualization of data generated by a major energy supplier. Visualization prototypes developed in this way prove effective in a situation whereby data sets are largely unknown and requirements open - enabling successful exploration of possibilities for visualization in Smart Home data analysis. The process gives rise to novel designs and design metaphors including data sculpting. It suggests: that the deliberate use of creativity techniques with data stakeholders is likely to contribute to successful, novel and effective solutions; that being explicit about creativity may contribute to designers developing creative solutions; that using creativity techniques early in the design process may result in a creative approach persisting throughout the process. The work constitutes the first systematic visualization design for a data rich source that will be increasingly important to energy suppliers and consumers as Smart Meter technology is widely deployed. It is novel in explicitly employing creativity techniques at the requirements stage of visualization design and development, paving the way for further use and study of creativity methods in visualization design. | false | false | [
"Sarah Goodwin",
"Jason Dykes",
"Sara Jones 0001",
"Iain Dillingham",
"Graham Dove",
"Alison Duffy",
"Alexander Kachkaev",
"Aidan Slingsby",
"Jo Wood"
] | [] | [] | [] |
InfoVis | 2,013 | DiffAni: Visualizing Dynamic Graphs with a Hybrid of Difference Maps and Animation | 10.1109/TVCG.2013.149 | Visualization of dynamically changing networks (graphs) is a significant challenge for researchers. Previous work has experimentally compared animation, small multiples, and other techniques, and found trade-offs between these. One potential way to avoid such trade-offs is to combine previous techniques in a hybrid visualization. We present two taxonomies of visualizations of dynamic graphs: one of non-hybrid techniques, and one of hybrid techniques. We also describe a prototype, called DiffAni, that allows a graph to be visualized as a sequence of three kinds of tiles: diff tiles that show difference maps over some time interval, animation tiles that show the evolution of the graph over some time interval, and small multiple tiles that show the graph state at an individual time slice. This sequence of tiles is ordered by time and covers all time slices in the data. An experimental evaluation of DiffAni shows that our hybrid approach has advantages over non-hybrid techniques in certain cases. | false | false | [
"Sébastien Rufiange",
"Michael J. McGuffin"
] | [] | [] | [] |
InfoVis | 2,013 | Dimension Projection Matrix/Tree: Interactive Subspace Visual Exploration and Analysis of High Dimensional Data | 10.1109/TVCG.2013.150 | For high-dimensional data, this work proposes two novel visual exploration methods to gain insights into the data aspect and the dimension aspect of the data. The first is a Dimension Projection Matrix, as an extension of a scatterplot matrix. In the matrix, each row or column represents a group of dimensions, and each cell shows a dimension projection (such as MDS) of the data with the corresponding dimensions. The second is a Dimension Projection Tree, where every node is either a dimension projection plot or a Dimension Projection Matrix. Nodes are connected with links and each child node in the tree covers a subset of the parent node's dimensions or a subset of the parent node's data items. While the tree nodes visualize the subspaces of dimensions or subsets of the data items under exploration, the matrix nodes enable cross-comparison between different combinations of subspaces. Both Dimension Projection Matrix and Dimension Project Tree can be constructed algorithmically through automation, or manually through user interaction. Our implementation enables interactions such as drilling down to explore different levels of the data, merging or splitting the subspaces to adjust the matrix, and applying brushing to select data clusters. Our method enables simultaneously exploring data correlation and dimension correlation for data with high dimensions. | false | false | [
"Xiaoru Yuan",
"Donghao Ren",
"Zuchao Wang",
"Cong Guo 0004"
] | [] | [] | [] |
InfoVis | 2,013 | Edge Compression Techniques for Visualization of Dense Directed Graphs | 10.1109/TVCG.2013.151 | We explore the effectiveness of visualizing dense directed graphs by replacing individual edges with edges connected to 'modules'-or groups of nodes-such that the new edges imply aggregate connectivity. We only consider techniques that offer a lossless compression: that is, where the entire graph can still be read from the compressed version. The techniques considered are: a simple grouping of nodes with identical neighbor sets; Modular Decomposition which permits internal structure in modules and allows them to be nested; and Power Graph Analysis which further allows edges to cross module boundaries. These techniques all have the same goal-to compress the set of edges that need to be rendered to fully convey connectivity-but each successive relaxation of the module definition permits fewer edges to be drawn in the rendered graph. Each successive technique also, we hypothesize, requires a higher degree of mental effort to interpret. We test this hypothetical trade-off with two studies involving human participants. For Power Graph Analysis we propose a novel optimal technique based on constraint programming. This enables us to explore the parameter space for the technique more precisely than could be achieved with a heuristic. Although applicable to many domains, we are motivated by-and discuss in particular-the application to software dependency analysis. | false | false | [
"Tim Dwyer",
"Nathalie Henry Riche",
"Kim Marriott",
"Christopher Mears"
] | [] | [] | [] |
InfoVis | 2,013 | Empirical Guidance on Scatterplot and Dimension Reduction Technique Choices | 10.1109/TVCG.2013.153 | To verify cluster separation in high-dimensional data, analysts often reduce the data with a dimension reduction (DR) technique, and then visualize it with 2D Scatterplots, interactive 3D Scatterplots, or Scatterplot Matrices (SPLOMs). With the goal of providing guidance between these visual encoding choices, we conducted an empirical data study in which two human coders manually inspected a broad set of 816 scatterplots derived from 75 datasets, 4 DR techniques, and the 3 previously mentioned scatterplot techniques. Each coder scored all color-coded classes in each scatterplot in terms of their separability from other classes. We analyze the resulting quantitative data with a heatmap approach, and qualitatively discuss interesting scatterplot examples. Our findings reveal that 2D scatterplots are often 'good enough', that is, neither SPLOM nor interactive 3D adds notably more cluster separability with the chosen DR technique. If 2D is not good enough, the most promising approach is to use an alternative DR technique in 2D. Beyond that, SPLOM occasionally adds additional value, and interactive 3D rarely helps but often hurts in terms of poorer class separation and usability. We summarize these results as a workflow model and implications for design. Our results offer guidance to analysts during the DR exploration process. | false | false | [
"Michael Sedlmair",
"Tamara Munzner",
"Melanie Tory"
] | [] | [] | [] |
InfoVis | 2,013 | Entourage: Visualizing Relationships between Biological Pathways using Contextual Subsets | 10.1109/TVCG.2013.154 | Biological pathway maps are highly relevant tools for many tasks in molecular biology. They reduce the complexity of the overall biological network by partitioning it into smaller manageable parts. While this reduction of complexity is their biggest strength, it is, at the same time, their biggest weakness. By removing what is deemed not important for the primary function of the pathway, biologists lose the ability to follow and understand cross-talks between pathways. Considering these cross-talks is, however, critical in many analysis scenarios, such as judging effects of drugs. In this paper we introduce Entourage, a novel visualization technique that provides contextual information lost due to the artificial partitioning of the biological network, but at the same time limits the presented information to what is relevant to the analyst's task. We use one pathway map as the focus of an analysis and allow a larger set of contextual pathways. For these context pathways we only show the contextual subsets, i.e., the parts of the graph that are relevant to a selection. Entourage suggests related pathways based on similarities and highlights parts of a pathway that are interesting in terms of mapped experimental data. We visualize interdependencies between pathways using stubs of visual links, which we found effective yet not obtrusive. By combining this approach with visualization of experimental data, we can provide domain experts with a highly valuable tool. We demonstrate the utility of Entourage with case studies conducted with a biochemist who researches the effects of drugs on pathways. We show that the technique is well suited to investigate interdependencies between pathways and to analyze, understand, and predict the effect that drugs have on different cell types. | false | false | [
"Alexander Lex",
"Christian Partl",
"Denis Kalkofen",
"Marc Streit",
"Samuel Gratzl",
"Anne Mai Wassermann",
"Dieter Schmalstieg",
"Hanspeter Pfister"
] | [] | [] | [] |
InfoVis | 2,013 | Evaluation of filesystem Provenance Visualization Tools | 10.1109/TVCG.2013.155 | Having effective visualizations of filesystem provenance data is valuable for understanding its complex hierarchical structure. The most common visual representation of provenance data is the node-link diagram. While effective for understanding local activity, the node-link diagram fails to offer a high-level summary of activity and inter-relationships within the data. We present a new tool, InProv, which displays filesystem provenance with an interactive radial-based tree layout. The tool also utilizes a new time-based hierarchical node grouping method for filesystem provenance data we developed to match the user's mental model and make data exploration more intuitive. We compared InProv to a conventional node-link based tool, Orbiter, in a quantitative evaluation with real users of filesystem provenance data including provenance data experts, IT professionals, and computational scientists. We also compared in the evaluation our new node grouping method to a conventional method. The results demonstrate that InProv results in higher accuracy in identifying system activity than Orbiter with large complex data sets. The results also show that our new time-based hierarchical node grouping method improves performance in both tools, and participants found both tools significantly easier to use with the new time-based node grouping method. Subjective measures show that participants found InProv to require less mental activity, less physical activity, less work, and is less stressful to use. Our study also reveals one of the first cases of gender differences in visualization; both genders had comparable performance with InProv, but women had a significantly lower average accuracy (56%) compared to men (70%) with Orbiter. | false | false | [
"Michelle Borkin",
"Chelsea S. Yeh",
"Madelaine Boyd",
"Peter Macko",
"Krzysztof Z. Gajos",
"Margo I. Seltzer",
"Hanspeter Pfister"
] | [] | [] | [] |
InfoVis | 2,013 | GPLOM: The Generalized Plot Matrix for Visualizing Multidimensional Multivariate Data | 10.1109/TVCG.2013.160 | Scatterplot matrices (SPLOMs), parallel coordinates, and glyphs can all be used to visualize the multiple continuous variables (i.e., dependent variables or measures) in multidimensional multivariate data. However, these techniques are not well suited to visualizing many categorical variables (i.e., independent variables or dimensions). To visualize multiple categorical variables, 'hierarchical axes' that 'stack dimensions' have been used in systems like Polaris and Tableau. However, this approach does not scale well beyond a small number of categorical variables. Emerson et al. [8] extend the matrix paradigm of the SPLOM to simultaneously visualize several categorical and continuous variables, displaying many kinds of charts in the matrix depending on the kinds of variables involved. We propose a variant of their technique, called the Generalized Plot Matrix (GPLOM). The GPLOM restricts Emerson et al.'s technique to only three kinds of charts (scatterplots for pairs of continuous variables, heatmaps for pairs of categorical variables, and barcharts for pairings of categorical and continuous variable), in an effort to make it easier to understand. At the same time, the GPLOM extends Emerson et al.'s work by demonstrating interactive techniques suited to the matrix of charts. We discuss the visual design and interactive features of our GPLOM prototype, including a textual search feature allowing users to quickly locate values or variables by name. We also present a user study that compared performance with Tableau and our GPLOM prototype, that found that GPLOM is significantly faster in certain cases, and not significantly slower in other cases. | false | false | [
"Jean-François Im",
"Michael J. McGuffin",
"Rock Leung"
] | [] | [] | [] |
InfoVis | 2,013 | Hybrid-Image Visualization for Large Viewing Environments | 10.1109/TVCG.2013.163 | We present a first investigation into hybrid-image visualization for data analysis in large-scale viewing environments. Hybrid-image visualizations blend two different visual representations into a single static view, such that each representation can be perceived at a different viewing distance. Our work is motivated by data analysis scenarios that incorporate one or more displays with sufficiently large size and resolution to be comfortably viewed by different people from various distances. Hybrid-image visualizations can be used, in particular, to enhance overview tasks from a distance and detail-in-context tasks when standing close to the display. By using a perception-based blending approach, hybrid-image visualizations make two full-screen visualizations accessible without tracking viewers in front of a display. We contribute a design space, discuss the perceptual rationale for our work, provide examples, and introduce a set of techniques and tools to aid the design of hybrid-image visualizations. | false | false | [
"Petra Isenberg",
"Pierre Dragicevic",
"Wesley Willett",
"Anastasia Bezerianos",
"Jean-Daniel Fekete"
] | [] | [] | [] |
InfoVis | 2,013 | Information Visualization and Proxemics: Design Opportunities and Empirical findings | 10.1109/TVCG.2013.166 | People typically interact with information visualizations using a mouse. Their physical movement, orientation, and distance to visualizations are rarely used as input. We explore how to use such spatial relations among people and visualizations (i.e., proxemics) to drive interaction with visualizations, focusing here on the spatial relations between a single user and visualizations on a large display. We implement interaction techniques that zoom and pan, query and relate, and adapt visualizations based on tracking of users' position in relation to a large high-resolution display. Alternative prototypes are tested in three user studies and compared with baseline conditions that use a mouse. Our aim is to gain empirical data on the usefulness of a range of design possibilities and to generate more ideas. Among other things, the results show promise for changing zoom level or visual representation with the user's physical distance to a large display. We discuss possible benefits and potential issues to avoid when designing information visualizations that use proxemics. | false | false | [
"Mikkel Rønne Jakobsen",
"Yonas Sahlemariam Haile",
"Søren Knudsen",
"Kasper Hornbæk"
] | [] | [] | [] |
InfoVis | 2,013 | Interactive Visualizations on Large and Small Displays: The Interrelation of Display Size, Information Space, and Scale | 10.1109/TVCG.2013.170 | In controlled experiments on the relation of display size (i.e., the number of pixels) and the usability of visualizations, the size of the information space can either be kept constant or varied relative to display size. Both experimental approaches have limitations. If the information space is kept constant then the scale ratio between an overview of the entire information space and the lowest zoom level varies, which can impact performance; if the information space is varied then the scale ratio is kept constant, but performance cannot be directly compared. In other words, display size, information space, and scale ratio are interrelated variables. We investigate this relation in two experiments with interfaces that implement classic information visualization techniques-focus+context, overview+detail, and zooming-for multi-scale navigation in maps. Display size varied between 0.17, 1.5, and 13.8 megapixels. Information space varied relative to display size in one experiment and was constant in the other. Results suggest that for tasks where users navigate targets that are visible at all map scales the interfaces do not benefit from a large display: With a constant map size, a larger display does not improve performance with the interfaces; with map size varied relative to display size, participants found interfaces harder to use with a larger display and task completion times decrease only when they are normalized to compensate for the increase in map size. The two experimental approaches show different interaction effects between display size and interface. In particular, focus+context performs relatively worse at a large display size with variable map size, and relatively worse at a small display size with a fixed map size. Based on a theoretical analysis of the interaction with the visualization techniques, we examine individual task actions empirically so as to understand the relative impact of display size and scale ratio on the visualization techniques' performance and to discuss differences between the two experimental approaches. | false | false | [
"Mikkel Rønne Jakobsen",
"Kasper Hornbæk"
] | [] | [] | [] |
InfoVis | 2,013 | LineUp: Visual Analysis of Multi-Attribute Rankings | 10.1109/TVCG.2013.173 | Rankings are a popular and universal approach to structuring otherwise unorganized collections of items by computing a rank for each item based on the value of one or more of its attributes. This allows us, for example, to prioritize tasks or to evaluate the performance of products relative to each other. While the visualization of a ranking itself is straightforward, its interpretation is not, because the rank of an item represents only a summary of a potentially complicated relationship between its attributes and those of the other items. It is also common that alternative rankings exist which need to be compared and analyzed to gain insight into how multiple heterogeneous attributes affect the rankings. Advanced visual exploration tools are needed to make this process efficient. In this paper we present a comprehensive analysis of requirements for the visualization of multi-attribute rankings. Based on these considerations, we propose LineUp - a novel and scalable visualization technique that uses bar charts. This interactive technique supports the ranking of items based on multiple heterogeneous attributes with different scales and semantics. It enables users to interactively combine attributes and flexibly refine parameters to explore the effect of changes in the attribute combination. This process can be employed to derive actionable insights as to which attributes of an item need to be modified in order for its rank to change. Additionally, through integration of slope graphs, LineUp can also be used to compare multiple alternative rankings on the same set of items, for example, over time or across different attribute combinations. We evaluate the effectiveness of the proposed multi-attribute visualization technique in a qualitative study. The study shows that users are able to successfully solve complex ranking tasks in a short period of time. | false | false | [
"Samuel Gratzl",
"Alexander Lex",
"Nils Gehlenborg",
"Hanspeter Pfister",
"Marc Streit"
] | [
"BP"
] | [] | [] |
InfoVis | 2,013 | Nanocubes for Real-Time Exploration of Spatiotemporal Datasets | 10.1109/TVCG.2013.179 | 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. | false | false | [
"Lauro Didier Lins",
"James T. Klosowski",
"Carlos Scheidegger"
] | [
"HM"
] | [] | [] |
InfoVis | 2,013 | Orthographic Star Coordinates | 10.1109/TVCG.2013.182 | 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. | false | false | [
"Dirk J. Lehmann",
"Holger Theisel"
] | [] | [] | [] |
InfoVis | 2,013 | Perception of Average Value in Multiclass Scatterplots | 10.1109/TVCG.2013.183 | 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. | false | false | [
"Michael Gleicher",
"Michael Correll",
"Christine Nothelfer",
"Steven Franconeri"
] | [] | [] | [] |
InfoVis | 2,013 | Radial Sets: Interactive Visual Analysis of Large Overlapping Sets | 10.1109/TVCG.2013.184 | 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. | false | false | [
"Bilal Alsallakh",
"Wolfgang Aigner",
"Silvia Miksch",
"Helwig Hauser"
] | [] | [] | [] |
InfoVis | 2,013 | Selecting the Aspect Ratio of a Scatter Plot Based on Its Delaunay Triangulation | 10.1109/TVCG.2013.187 | 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. | false | false | [
"Martin Fink 0001",
"Jan-Henrik Haunert",
"Joachim Spoerhase",
"Alexander Wolff 0001"
] | [] | [] | [] |
InfoVis | 2,013 | SketchStory: Telling More Engaging Stories with Data through Freeform Sketching | 10.1109/TVCG.2013.191 | 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. | false | false | [
"Bongshin Lee",
"Rubaiat Habib Kazi",
"Greg Smith"
] | [] | [] | [] |
InfoVis | 2,013 | SoccerStories: A Kick-off for Visual Soccer Analysis | 10.1109/TVCG.2013.192 | 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. | false | false | [
"Charles Perin",
"Romain Vuillemot",
"Jean-Daniel Fekete"
] | [
"HM"
] | [] | [] |
InfoVis | 2,013 | StoryFlow: Tracking the Evolution of Stories | 10.1109/TVCG.2013.196 | 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. | false | false | [
"Shixia Liu",
"Yingcai Wu",
"Enxun Wei",
"Mengchen Liu",
"Yang Liu 0014"
] | [] | [] | [] |
InfoVis | 2,013 | Understanding Interfirm Relationships in Business Ecosystems with Interactive Visualization | 10.1109/TVCG.2013.209 | 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. | false | false | [
"Rahul C. Basole",
"Trustin A. Clear",
"Mengdie Hu",
"Harshit Mehrotra",
"John T. Stasko"
] | [] | [] | [] |
InfoVis | 2,013 | Using Concrete Scales: A Practical Framework for Effective Visual Depiction of Complex Measures | 10.1109/TVCG.2013.210 | 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. | false | false | [
"Fanny Chevalier",
"Romain Vuillemot",
"Guia Gali"
] | [] | [] | [] |
InfoVis | 2,013 | Variant View: Visualizing Sequence Variants in their Gene Context | 10.1109/TVCG.2013.214 | 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. | false | false | [
"Joel A. Ferstay",
"Cydney B. Nielsen",
"Tamara Munzner"
] | [] | [] | [] |
InfoVis | 2,013 | Visual Compression of Workflow Visualizations with Automated Detection of Macro Motifs | 10.1109/TVCG.2013.225 | 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. | false | false | [
"Eamonn Maguire",
"Philippe Rocca-Serra",
"Susanna-Assunta Sansone",
"Jim Davies",
"Min Chen 0001"
] | [] | [] | [] |
InfoVis | 2,013 | Visual Sedimentation | 10.1109/TVCG.2013.227 | 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. | false | false | [
"Samuel Huron",
"Romain Vuillemot",
"Jean-Daniel Fekete"
] | [] | [] | [] |
InfoVis | 2,013 | Visualization of Shape Motions in Shape Space | 10.1109/TVCG.2013.230 | 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. | false | false | [
"Vahid Taimouri",
"Jing Hua 0001"
] | [] | [] | [] |
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