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 |
|---|---|---|---|---|---|---|---|---|---|---|
VAST | 2,012 | Just-in-time annotation of clusters, outliers, and trends in point-based data visualizations | 10.1109/VAST.2012.6400487 | We introduce the concept of just-in-time descriptive analytics as a novel application of computational and statistical techniques performed at interaction-time to help users easily understand the structure of data as seen in visualizations. Fundamental to just-intime descriptive analytics is (a) identifying visual features, such as clusters, outliers, and trends, user might observe in visualizations automatically, (b) determining the semantics of such features by performing statistical analysis as the user is interacting, and (c) enriching visualizations with annotations that not only describe semantics of visual features but also facilitate interaction to support high-level understanding of data. In this paper, we demonstrate just-in-time descriptive analytics applied to a point-based multi-dimensional visualization technique to identify and describe clusters, outliers, and trends. We argue that it provides a novel user experience of computational techniques working alongside of users allowing them to build faster qualitative mental models of data by demonstrating its application on a few use-cases. Techniques used to facilitate just-in-time descriptive analytics are described in detail along with their runtime performance characteristics. We believe this is just a starting point and much remains to be researched, as we discuss open issues and opportunities in improving accessibility and collaboration. | false | false | [
"Eser Kandogan"
] | [] | [] | [] |
VAST | 2,012 | LeadLine: Interactive visual analysis of text data through event identification and exploration | 10.1109/VAST.2012.6400485 | Text data such as online news and microblogs bear valuable insights regarding important events and responses to such events. Events are inherently temporal, evolving over time. Existing visual text analysis systems have provided temporal views of changes based on topical themes extracted from text data. But few have associated topical themes with events that cause the changes. In this paper, we propose an interactive visual analytics system, LeadLine, to automatically identify meaningful events in news and social media data and support exploration of the events. To characterize events, LeadLine integrates topic modeling, event detection, and named entity recognition techniques to automatically extract information regarding the investigative 4 Ws: who, what, when, and where for each event. To further support analysis of the text corpora through events, LeadLine allows users to interactively examine meaningful events using the 4 Ws to develop an understanding of how and why. Through representing large-scale text corpora in the form of meaningful events, LeadLine provides a concise summary of the corpora. LeadLine also supports the construction of simple narratives through the exploration of events. To demonstrate the efficacy of LeadLine in identifying events and supporting exploration, two case studies were conducted using news and social media data. | false | false | [
"Wenwen Dou",
"Derek Xiaoyu Wang",
"Drew Skau",
"William Ribarsky",
"Michelle X. Zhou"
] | [] | [] | [] |
VAST | 2,012 | LensingWikipedia: Parsing text for the interactive visualization of human history | 10.1109/VAST.2012.6400530 | Extracting information from text is challenging. Most current practices treat text as a bag of words or word clusters, ignoring valuable linguistic information. Leveraging this linguistic information, we propose a novel approach to visualize textual information. The novelty lies in using state-of-the-art Natural Language Processing (NLP) tools to automatically annotate text which provides a basis for new and powerful interactive visualizations. Using NLP tools, we built a web-based interactive visual browser for human history articles from Wikipedia. | false | false | [
"Ravikiran Vadlapudi",
"Maryam Siahbani",
"Anoop Sarkar",
"John Dill"
] | [] | [] | [] |
VAST | 2,012 | Matrix-based visual correlation analysis on large timeseries data | 10.1109/VAST.2012.6400549 | In recent years, the quantity of time series data generated in a wide variety of domains grown consistently. Thus, it is difficult for analysts to process and understand this overwhelming amount of data. In the specific case of time series data another problem arises: time series can be highly interrelated. This problem becomes even more challenging when a set of parameters influences the progression of a time series. However, while most visual analysis techniques support the analysis of short time periods, e.g. one day or one week, they fail to visualize large-scale time series, ranging over one year or more. In our approach we present a time series matrix visualization that tackles this problem. Its primary advantages are that it scales to a large number of time series with different start and end points and allows for the visual comparison / correlation analysis of a set of influencing factors. To evaluate our approach, we applied our technique to a real-world data set, showing the impact of local weather conditions on the efficiency of photovoltaic power plants. | false | false | [
"Michael Behrisch 0001",
"James Davey",
"Tobias Schreck",
"Daniel A. Keim",
"Jörn Kohlhammer"
] | [] | [] | [] |
VAST | 2,012 | Optimizing an SPT-tree for visual analytics | 10.1109/VAST.2012.6400544 | Despite the extensive work done in the scientific visualization community on the creation and optimization of spatial data structures, there has been little adaptation of these structures in visual analytics and information visualization. In this work we present how we modify a space-partioning time (SPT) tree - a structure normally used in direct-volume rendering - for geospatial-temporal visualizations. We also present optimization techniques to improve the traversal speed of our structure through locational codes and bitwise comparisons. Finally, we present the results of an experiment that quantitatively evaluates our modified SPT tree with and without our optimizations. Our results indicate that retrieval was nearly three times faster when using our optimizations, and are consistent across multiple trials. Our finding could have implications for performance in using our modified SPT tree in large-scale geospatial temporal visual analytics software. | false | false | [
"Connor Gramazio",
"Remco Chang"
] | [] | [] | [] |
VAST | 2,012 | Priming Locus of Control to affect performance | 10.1109/VAST.2012.6400535 | Recent research suggests that the personality trait Locus of Control (LOC) can be a reliable predictor of performance when learning a new visualization tool. While these results are compelling and have direct implications to visualization design, the relationship between a user's LOC measure and their performance is not well understood. We hypothesize that there is a dependent relationship between LOC and performance; specifically, a person's orientation on the LOC scale directly influences their performance when learning new visualizations. To test this hypothesis, we conduct an experiment with 300 subjects using Amazon's Mechanical Turk. We adapt techniques from personality psychology to manipulate a user's LOC so that users are either primed to be more internally or externally oriented on the LOC scale. Replicating previous studies investigating the effect of LOC on performance, we measure users' speed and accuracy as they use visualizations with varying visual metaphors. Our findings demonstrate that changing a user's LOC impacts their performance. We find that a change in users' LOC results in performance changes. | false | false | [
"Alvitta Ottley",
"R. Jordan Crouser",
"Caroline Ziemkiewicz",
"Remco Chang"
] | [] | [] | [] |
VAST | 2,012 | Reinventing the Contingency Wheel: Scalable Visual Analytics of Large Categorical Data | 10.1109/TVCG.2012.254 | Contingency tables summarize the relations between categorical variables and arise in both scientific and business domains. Asymmetrically large two-way contingency tables pose a problem for common visualization methods. The Contingency Wheel has been recently proposed as an interactive visual method to explore and analyze such tables. However, the scalability and readability of this method are limited when dealing with large and dense tables. In this paper we present Contingency Wheel++, new visual analytics methods that overcome these major shortcomings: (1) regarding automated methods, a measure of association based on Pearson's residuals alleviates the bias of the raw residuals originally used, (2) regarding visualization methods, a frequency-based abstraction of the visual elements eliminates overlapping and makes analyzing both positive and negative associations possible, and (3) regarding the interactive exploration environment, a multi-level overview+detail interface enables exploring individual data items that are aggregated in the visualization or in the table using coordinated views. We illustrate the applicability of these new methods with a use case and show how they enable discovering and analyzing nontrivial patterns and associations in large categorical data. | false | false | [
"Bilal Alsallakh",
"Wolfgang Aigner",
"Silvia Miksch",
"M. Eduard Gröller"
] | [
"HM"
] | [] | [] |
VAST | 2,012 | Relative N-gram signatures: Document visualization at the level of character N-grams | 10.1109/VAST.2012.6400484 | The Common N-Gram (CNG) classifier is a text classification algorithm based on the comparison of frequencies of character n-grams (strings of characters of length n) that are the most common in the considered documents and classes of documents. We present a text analytic visualization system that employs the CNG approach for text classification and uses the differences in frequency values of common n-grams in order to visually compare documents at the sub-word level. The visualization method provides both an insight into n-gram characteristics of documents or classes of documents and a visual interpretation of the workings of the CNG classifier. | false | false | [
"Magdalena Jankowska",
"Vlado Keselj",
"Evangelos E. Milios"
] | [] | [] | [] |
VAST | 2,012 | Scatter/Gather Clustering: Flexibly Incorporating User Feedback to Steer Clustering Results | 10.1109/TVCG.2012.258 | Significant effort has been devoted to designing clustering algorithms that are responsive to user feedback or that incorporate prior domain knowledge in the form of constraints. However, users desire more expressive forms of interaction to influence clustering outcomes. In our experiences working with diverse application scientists, we have identified an interaction style scatter/gather clustering that helps users iteratively restructure clustering results to meet their expectations. As the names indicate, scatter and gather are dual primitives that describe whether clusters in a current segmentation should be broken up further or, alternatively, brought back together. By combining scatter and gather operations in a single step, we support very expressive dynamic restructurings of data. Scatter/gather clustering is implemented using a nonlinear optimization framework that achieves both locality of clusters and satisfaction of user-supplied constraints. We illustrate the use of our scatter/gather clustering approach in a visual analytic application to study baffle shapes in the bat biosonar (ears and nose) system. We demonstrate how domain experts are adept at supplying scatter/gather constraints, and how our framework incorporates these constraints effectively without requiring numerous instance-level constraints. | false | false | [
"Mahmud Shahriar Hossain",
"Praveen Kumar Reddy Ojili",
"Cindy Grimm",
"Rolf Müller",
"Layne T. Watson",
"Naren Ramakrishnan"
] | [] | [] | [] |
VAST | 2,012 | Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering | 10.1109/TVCG.2012.260 | Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition. | false | false | [
"Alex Endert",
"Patrick Fiaux",
"Chris North 0001"
] | [] | [] | [] |
VAST | 2,012 | Smart super views---A knowledge-assisted interface for medical visualization | 10.1109/VAST.2012.6400555 | Due to the ever growing volume of acquired data and information, users have to be constantly aware of the methods for their exploration and for interaction. Of these, not each might be applicable to the data at hand or might reveal the desired result. Owing to this, innovations may be used inappropriately and users may become skeptical. In this paper we propose a knowledge-assisted interface for medical visualization, which reduces the necessary effort to use new visualization methods, by providing only the most relevant ones in a smart way. Consequently, we are able to expand such a system with innovations without the users to worry about when, where, and especially how they may or should use them. We present an application of our system in the medical domain and give qualitative feedback from domain experts. | false | false | [
"Gabriel Mistelbauer",
"Hamed Bouzari",
"Rüdiger Schernthaner",
"Ivan Baclija",
"Arnold Köchl",
"Stefan Bruckner",
"Milos Srámek",
"M. Eduard Gröller"
] | [] | [] | [] |
VAST | 2,012 | SocialNetSense: Supporting sensemaking of social and structural features in networks with interactive visualization | 10.1109/VAST.2012.6400558 | Increasingly, social network datasets contain social attribute information about actors and their relationship. Analyzing such network with social attributes requires making sense of not only its structural features, but also the relationship between social features in attributes and network structures. Existing social network analysis tools are usually weak in supporting complex analytical tasks involving both structural and social features, and often overlook users' needs for sensemaking tools that help to gather, synthesize, and organize information of these features. To address these challenges, we propose a sensemaking framework of social-network visual analytics in this paper. This framework considers both bottom-up processes, which are about constructing new understandings based on collected information, and top-down processes, which concern using prior knowledge to guide information collection, in analyzing social networks from both social and structural perspectives. The framework also emphasizes the externalization of sensemaking processes through interactive visualization. Guided by the framework, we develop a system, SocialNetSense, to support the sensemaking in visual analytics of social networks with social attributes. The example of using our system to analyze a scholar collaboration network shows that our approach can help users gain insight into social networks both structurally and socially, and enhance their process awareness in visual analytics. | false | false | [
"Liang Gou",
"Xiaolong Zhang 0001",
"Airong Luo",
"Patricia F. Anderson"
] | [] | [] | [] |
VAST | 2,012 | Spatiotemporal social media analytics for abnormal event detection and examination using seasonal-trend decomposition | 10.1109/VAST.2012.6400557 | Recent advances in technology have enabled social media services to support space-time indexed data, and internet users from all over the world have created a large volume of time-stamped, geo-located data. Such spatiotemporal data has immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. In analyzing social media data, researchers have mainly focused on finding temporal trends according to volume-based importance. Hence, a relatively small volume of relevant messages may easily be obscured by a huge data set indicating normal situations. In this paper, we present a visual analytics approach that provides users with scalable and interactive social media data analysis and visualization including the exploration and examination of abnormal topics and events within various social media data sources, such as Twitter, Flickr and YouTube. In order to find and understand abnormal events, the analyst can first extract major topics from a set of selected messages and rank them probabilistically using Latent Dirichlet Allocation. He can then apply seasonal trend decomposition together with traditional control chart methods to find unusual peaks and outliers within topic time series. Our case studies show that situational awareness can be improved by incorporating the anomaly and trend examination techniques into a highly interactive visual analysis process. | false | false | [
"Junghoon Chae",
"Dennis Thom",
"Harald Bosch",
"Yun Jang",
"Ross Maciejewski",
"David S. Ebert",
"Thomas Ertl"
] | [] | [] | [] |
VAST | 2,012 | Subspace search and visualization to make sense of alternative clusterings in high-dimensional data | 10.1109/VAST.2012.6400488 | In explorative data analysis, the data under consideration often resides in a high-dimensional (HD) data space. Currently many methods are available to analyze this type of data. So far, proposed automatic approaches include dimensionality reduction and cluster analysis, whereby visual-interactive methods aim to provide effective visual mappings to show, relate, and navigate HD data. Furthermore, almost all of these methods conduct the analysis from a singular perspective, meaning that they consider the data in either the original HD data space, or a reduced version thereof. Additionally, HD data spaces often consist of combined features that measure different properties, in which case the particular relationships between the various properties may not be clear to the analysts a priori since it can only be revealed if appropriate feature combinations (subspaces) of the data are taken into consideration. Considering just a single subspace is, however, often not sufficient since different subspaces may show complementary, conjointly, or contradicting relations between data items. Useful information may consequently remain embedded in sets of subspaces of a given HD input data space. Relying on the notion of subspaces, we propose a novel method for the visual analysis of HD data in which we employ an interestingness-guided subspace search algorithm to detect a candidate set of subspaces. Based on appropriately defined subspace similarity functions, we visualize the subspaces and provide navigation facilities to interactively explore large sets of subspaces. Our approach allows users to effectively compare and relate subspaces with respect to involved dimensions and clusters of objects. We apply our approach to synthetic and real data sets. We thereby demonstrate its support for understanding HD data from different perspectives, effectively yielding a more complete view on HD data. | false | false | [
"Andrada Tatu",
"Fabian Maass",
"Ines Färber",
"Enrico Bertini",
"Tobias Schreck",
"Thomas Seidl 0001",
"Daniel A. Keim"
] | [] | [] | [] |
VAST | 2,012 | The Deshredder: A visual analytic approach to reconstructing shredded documents | 10.1109/VAST.2012.6400560 | Reconstruction of shredded documents remains a significant challenge. Creating a better document reconstruction system enables not just recovery of information accidentally lost but also understanding our limitations against adversaries' attempts to gain access to information. Existing approaches to reconstructing shredded documents adopt either a predominantly manual (e.g., crowd-sourcing) or a near automatic approach. We describe Deshredder, a visual analytic approach that scales well and effectively incorporates user input to direct the reconstruction process. Deshredder represents shredded pieces as time series and uses nearest neighbor matching techniques that enable matching both the contours of shredded pieces as well as the content of shreds themselves. More importantly, Deshred-der's interface support visual analytics through user interaction with similarity matrices as well as higher level assembly through more complex stitching functions. We identify a functional task taxonomy leading to design considerations for constructing deshredding solutions, and describe how Deshredder applies to problems from the DARPA Shredder Challenge through expert evaluations. | false | false | [
"Patrick Butler",
"Prithwish Chakraborty",
"Naren Ramakrishnan"
] | [] | [] | [] |
VAST | 2,012 | The spatiotemporal multivariate hypercube for discovery of patterns in event data | 10.1109/VAST.2012.6400536 | Event data can hold valuable decision making information, yet detecting interesting patterns in this type of data is not an easy task because the data is usually rich and contains spatial, temporal as well as multivariate dimensions. Research into visual analytics tools to support the discovery of patterns in event data often focuses on the spatiotemporal or spatiomultivariate dimension of the data only. Few research efforts focus on all three dimensions in one framework. An integral view on all three dimensions is, however, required to unlock the full potential of event datasets. In this poster, we present an event visualization, transition, and interaction framework that enables an integral view on all dimensions of spatiotemporal multivariate event data. The framework is built around the notion that the event data space can be considered a spatiotemporal multivariate hypercube. Results of a case study we performed suggest that a visual analytics tool based on the proposed framework is indeed capable to support users in the discovery of multidimensional spatiotemporal multivariate patterns in event data. | false | false | [
"Fred Olislagers",
"Marcel Worring"
] | [] | [] | [] |
VAST | 2,012 | The User Puzzle---Explaining the Interaction with Visual Analytics Systems | 10.1109/TVCG.2012.273 | Visual analytics emphasizes the interplay between visualization, analytical procedures performed by computers and human perceptual and cognitive activities. Human reasoning is an important element in this context. There are several theories in psychology and HCI explaining open-ended and exploratory reasoning. Five of these theories (sensemaking theories, gestalt theories, distributed cognition, graph comprehension theories and skill-rule-knowledge models) are described in this paper. We discuss their relevance for visual analytics. In order to do this more systematically, we developed a schema of categories relevant for visual analytics research and evaluation. All these theories have strengths but also weaknesses in explaining interaction with visual analytics systems. A possibility to overcome the weaknesses would be to combine two or more of these theories. | false | false | [
"Margit Pohl",
"Michael Smuc",
"Eva Mayr"
] | [] | [] | [] |
VAST | 2,012 | Time-oriented visualization and anticipation | 10.1109/VAST.2012.6400546 | Temporal awareness is pivotal to successful real-time dynamic decision making in a wide range of command and control situations; particularly in safety-critical environments. However, little explicit support for operators' temporal awareness is provided by decision support systems (DSS) for time-critical decisions. In the context of functional simulations of naval anti-air warfare and emergency response management, the present study compares operator support provided by two display formats. In both environments, we contrast a baseline condition to a condition in which a temporal display was integrated to the original interface to support operators' temporal awareness. We also wish to establish whether the implementation of time-based DSSs may also come with drawbacks on cognitive functioning and performance. | false | false | [
"Cindy Chamberland",
"François Vachon",
"Jean-François Gagnon",
"Simon P. Banbury",
"Sébastien Tremblay"
] | [] | [] | [] |
VAST | 2,012 | Using translational science in visual analytics | 10.1109/VAST.2012.6400543 | We introduce translational science, a research discipline from medicine, and show how adapting it for visual analytics can improve the design and evaluation of visual analytics interfaces. Translational science “translates” knowledge from the lab to the real-world to “ground truth” by incorporating a 3 phase program of research. Phase 1 & 2 include protocols for research in the lab and field and Phase 3 focuses on dissemination and documentation. We discuss these phases and how they may be applied to visual analytics research. | false | false | [
"Tera Marie Green",
"Brian D. Fisher"
] | [] | [] | [] |
VAST | 2,012 | Using visual analytics to detect problems in datasets collected from photo-sharing services | 10.1109/VAST.2012.6400538 | Datasets that are collected for research often contain millions of records and may carry hidden pitfalls that are hard to detect. This work demonstrates how visual analytics can be used for identifying problems in the spatial distribution of crawled photographic data in different datasets: Picasa Web Albums, Panoramio, Flickr and Geograph, chosen to be potential data sources for ongoing doctoral research. This poster summary describes a number of problems found in the datasets using visual analytics and suggests that greater attention should be paid to assessing the quality of data gathered from user-generated photographic content. This work is the first part of a three-year PhD project aimed at producing a pedestrian-routing system that can suggest attractive pathways extracted from user-generated photographic content. | false | false | [
"Alexander Kachkaev",
"Jo Wood"
] | [] | [] | [] |
VAST | 2,012 | VDQAM: A toolkit for database quality evaluation based on visual morphology | 10.1109/VAST.2012.6400531 | Data quality evaluation is one of the most critical steps during the data mining processes. Data with poor quality often leads to poor performance in data mining, low efficiency in data analysis, wrong decision which bring great economic loss to users and organizations further. Although many researches have been carried out from various aspects of the extracting, transforming, and loading processes in data mining, most researches pay more attention to analysis automation than to data quality evaluation. To address the data quality evaluation issues, we propose an approach to combine human beings' powerful cognitive abilities in data quality evaluation with the high efficiency ability of computer, and develop a visual analysis method for data quality evaluation based on visual morphology. | false | false | [
"Dongxing Teng",
"Haiyan Yang",
"CuiXia Ma",
"Hongan Wang"
] | [] | [] | [] |
VAST | 2,012 | Visual analytics for the big data era---A comparative review of state-of-the-art commercial systems | 10.1109/VAST.2012.6400554 | Visual analytics (VA) system development started in academic research institutions where novel visualization techniques and open source toolkits were developed. Simultaneously, small software companies, sometimes spin-offs from academic research institutions, built solutions for specific application domains. In recent years we observed the following trend: some small VA companies grew exponentially; at the same time some big software vendors such as IBM and SAP started to acquire successful VA companies and integrated the acquired VA components into their existing frameworks. Generally the application domains of VA systems have broadened substantially. This phenomenon is driven by the generation of more and more data of high volume and complexity, which leads to an increasing demand for VA solutions from many application domains. In this paper we survey a selection of state-of-the-art commercial VA frameworks, complementary to an existing survey on open source VA tools. From the survey results we identify several improvement opportunities as future research directions. | false | false | [
"Leishi Zhang",
"Andreas Stoffel",
"Michael Behrisch 0001",
"Sebastian Mittelstädt",
"Tobias Schreck",
"René Pompl",
"Stefan Weber 0004",
"Holger Last",
"Daniel A. Keim"
] | [] | [] | [] |
VAST | 2,012 | Visual Analytics Methodology for Eye Movement Studies | 10.1109/TVCG.2012.276 | Eye movement analysis is gaining popularity as a tool for evaluation of visual displays and interfaces. However, the existing methods and tools for analyzing eye movements and scanpaths are limited in terms of the tasks they can support and effectiveness for large data and data with high variation. We have performed an extensive empirical evaluation of a broad range of visual analytics methods used in analysis of geographic movement data. The methods have been tested for the applicability to eye tracking data and the capability to extract useful knowledge about users' viewing behaviors. This allowed us to select the suitable methods and match them to possible analysis tasks they can support. The paper describes how the methods work in application to eye tracking data and provides guidelines for method selection depending on the analysis tasks. | false | false | [
"Gennady L. Andrienko",
"Natalia V. Andrienko",
"Michael Burch",
"Daniel Weiskopf"
] | [
"BP"
] | [] | [] |
VAST | 2,012 | Visual analytics methods for categoric spatio-temporal data | 10.1109/VAST.2012.6400553 | We focus on visual analysis of space- and time-referenced categorical data, which describe possible states of spatial (geographical) objects or locations and their changes over time. The analysis of these data is difficult as there are only limited possibilities to analyze the three aspects (location, time and category) simultaneously. We present a new approach which interactively combines (a) visualization of categorical changes over time; (b) various spatial data displays; (c) computational techniques for task-oriented selection of time steps. They provide an expressive visualization with regard to either the overall evolution over time or unusual changes. We apply our approach on two use cases demonstrating its usefulness for a wide variety of tasks. We analyze data from movement tracking and meteorologic areas. Using our approach, expected events could be detected and new insights were gained. | false | false | [
"Tatiana von Landesberger",
"Sebastian Bremm",
"Natalia V. Andrienko",
"Gennady L. Andrienko",
"Maria Tekusova"
] | [] | [] | [] |
VAST | 2,012 | Visual Classifier Training for Text Document Retrieval | 10.1109/TVCG.2012.277 | Performing exhaustive searches over a large number of text documents can be tedious, since it is very hard to formulate search queries or define filter criteria that capture an analyst's information need adequately. Classification through machine learning has the potential to improve search and filter tasks encompassing either complex or very specific information needs, individually. Unfortunately, analysts who are knowledgeable in their field are typically not machine learning specialists. Most classification methods, however, require a certain expertise regarding their parametrization to achieve good results. Supervised machine learning algorithms, in contrast, rely on labeled data, which can be provided by analysts. However, the effort for labeling can be very high, which shifts the problem from composing complex queries or defining accurate filters to another laborious task, in addition to the need for judging the trained classifier's quality. We therefore compare three approaches for interactive classifier training in a user study. All of the approaches are potential candidates for the integration into a larger retrieval system. They incorporate active learning to various degrees in order to reduce the labeling effort as well as to increase effectiveness. Two of them encompass interactive visualization for letting users explore the status of the classifier in context of the labeled documents, as well as for judging the quality of the classifier in iterative feedback loops. We see our work as a step towards introducing user controlled classification methods in addition to text search and filtering for increasing recall in analytics scenarios involving large corpora. | false | false | [
"Florian Heimerl",
"Steffen Koch 0001",
"Harald Bosch",
"Thomas Ertl"
] | [] | [] | [] |
VAST | 2,012 | Visual cluster exploration of web clickstream data | 10.1109/VAST.2012.6400494 | Web clickstream data are routinely collected to study how users browse the web or use a service. It is clear that the ability to recognize and summarize user behavior patterns from such data is valuable to e-commerce companies. In this paper, we introduce a visual analytics system to explore the various user behavior patterns reflected by distinct clickstream clusters. In a practical analysis scenario, the system first presents an overview of clickstream clusters using a Self-Organizing Map with Markov chain models. Then the analyst can interactively explore the clusters through an intuitive user interface. He can either obtain summarization of a selected group of data or further refine the clustering result. We evaluated our system using two different datasets from eBay. Analysts who were working on the same data have confirmed the system's effectiveness in extracting user behavior patterns from complex datasets and enhancing their ability to reason. | false | false | [
"Jishang Wei",
"Zeqian Shen",
"Neel Sundaresan",
"Kwan-Liu Ma"
] | [] | [] | [] |
VAST | 2,012 | Visual exploration of local interest points in sets of time series | 10.1109/VAST.2012.6400534 | Visual analysis of time series data is an important, yet challenging task with many application examples in fields such as financial or news stream data analysis. Many visual time series analysis approaches consider a global perspective on the time series. Fewer approaches consider visual analysis of local patterns in time series, and often rely on interactive specification of the local area of interest. We present initial results of an approach that is based on automatic detection of local interest points. We follow an overview-first approach to find useful parameters for the interest point detection, and details-on-demand to relate the found patterns. We present initial results and detail possible extensions of the approach. | false | false | [
"Tobias Schreck",
"Lyubka Sharalieva",
"Franz Wanner",
"Jürgen Bernard",
"Tobias Ruppert",
"Tatiana von Landesberger",
"Benjamin Bustos"
] | [] | [] | [] |
VAST | 2,012 | Visual pattern discovery using random projections | 10.1109/VAST.2012.6400490 | An essential element of exploratory data analysis is the use of revealing low-dimensional projections of high-dimensional data. Projection Pursuit has been an effective method for finding interesting low-dimensional projections of multidimensional spaces by optimizing a score function called a projection pursuit index. However, the technique is not scalable to high-dimensional spaces. Here, we introduce a novel method for discovering noteworthy views of high-dimensional data spaces by using binning and random projections. We define score functions, akin to projection pursuit indices, that characterize visual patterns of the low-dimensional projections that constitute feature subspaces. We also describe an analytic, multivariate visualization platform based on this algorithm that is scalable to extremely large problems. | false | false | [
"Anushka Anand",
"Leland Wilkinson",
"Tommy Dang"
] | [] | [] | [] |
VAST | 2,012 | Visualising variations in household energy consumption | 10.1109/VAST.2012.6400545 | There is limited understanding of the relationship between neighbourhoods, demographic characteristics and domestic energy consumption habits. We report upon research that combines datasets relating to household energy use with geodemographics to enable better understanding of UK energy user types. A novel interactive interface is planned to evaluate the performance of specifically created energy-based data classifications. The research aims to help local governments and the energy industry in targeting households and populations for new energy saving schemes and in improving efforts to promote sustainable energy consumption. The new classifications may also stimulate consumption awareness amongst domestic users. This poster reports on initial visual findings and describes the research methodology, data sources and future visualisation requirements. | false | false | [
"Sarah Goodwin",
"Jason Dykes"
] | [] | [] | [] |
VAST | 2,012 | Visualizing flows of images in social media | 10.1109/VAST.2012.6400539 | Mass and social media provide flows of images for real world events. It is sometimes difficult to represent realities and impressions of events using only text. However, even a single photo might remind us complex events. Along with events in the real world, there are representative images, such as design of products and commercial pictures. We can therefore recognize changes in trends of people's ideas, experiences, and interests through observing the flows of such representative images. This paper presents a novel 3D visualization system to explore temporal changes in trends using images associating with different topics, called Image Bricks. We show case studies using images extracted from our six-year blog archive. We first extract clusters of images as topics related to given keywords. We then visualize them on multiple timelines in a 3D space. Users can visually read stories of topics through exploring visualized images. | false | false | [
"Masahiko Itoh",
"Masashi Toyoda",
"Tetsuya Kamijo",
"Masaru Kitsuregawa"
] | [] | [] | [] |
VAST | 2,012 | Watch this: A taxonomy for dynamic data visualization | 10.1109/VAST.2012.6400552 | Visualizations embody design choices about data access, data transformation, visual representation, and interaction. To interpret a static visualization, a person must identify the correspondences between the visual representation and the underlying data. These correspondences become moving targets when a visualization is dynamic. Dynamics may be introduced in a visualization at any point in the analysis and visualization process. For example, the data itself may be streaming, shifting subsets may be selected, visual representations may be animated, and interaction may modify presentation. In this paper, we focus on the impact of dynamic data. We present a taxonomy and conceptual framework for understanding how data changes influence the interpretability of visual representations. Visualization techniques are organized into categories at various levels of abstraction. The salient characteristics of each category and task suitability are discussed through examples from the scientific literature and popular practices. Examining the implications of dynamically updating visualizations warrants attention because it directly impacts the interpretability (and thus utility) of visualizations. The taxonomy presented provides a reference point for further exploration of dynamic data visualization techniques. | false | false | [
"Joseph A. Cottam",
"Andrew Lumsdaine",
"Chris E. Weaver"
] | [] | [] | [] |
SciVis | 2,012 | A Data-Driven Approach to Hue-Preserving Color-Blending | 10.1109/TVCG.2012.186 | Color mapping and semitransparent layering play an important role in many visualization scenarios, such as information visualization and volume rendering. The combination of color and transparency is still dominated by standard alpha-compositing using the Porter-Duff over operator which can result in false colors with deceiving impact on the visualization. Other more advanced methods have also been proposed, but the problem is still far from being solved. Here we present an alternative to these existing methods specifically devised to avoid false colors and preserve visual depth ordering. Our approach is data driven and follows the recently formulated knowledge-assisted visualization (KAV) paradigm. Preference data, that have been gathered in web-based user surveys, are used to train a support-vector machine model for automatically predicting an optimized hue-preserving blending. We have applied the resulting model to both volume rendering and a specific information visualization technique, illustrative parallel coordinate plots. Comparative renderings show a significant improvement over previous approaches in the sense that false colors are completely removed and important properties such as depth ordering and blending vividness are better preserved. Due to the generality of the defined data-driven blending operator, it can be easily integrated also into other visualization frameworks. | false | false | [
"Lars Kuehne",
"Joachim Giesen",
"Zhiyuan Zhang",
"Sungsoo Ha",
"Klaus Mueller 0001"
] | [] | [] | [] |
SciVis | 2,012 | A Novel Approach to Visualizing Dark Matter Simulations | 10.1109/TVCG.2012.187 | In the last decades cosmological N-body dark matter simulations have enabled ab initio studies of the formation of structure in the Universe. Gravity amplified small density fluctuations generated shortly after the Big Bang, leading to the formation of galaxies in the cosmic web. These calculations have led to a growing demand for methods to analyze time-dependent particle based simulations. Rendering methods for such N-body simulation data usually employ some kind of splatting approach via point based rendering primitives and approximate the spatial distributions of physical quantities using kernel interpolation techniques, common in SPH (Smoothed Particle Hydrodynamics)-codes. This paper proposes three GPU-assisted rendering approaches, based on a new, more accurate method to compute the physical densities of dark matter simulation data. It uses full phase-space information to generate a tetrahedral tessellation of the computational domain, with mesh vertices defined by the simulation's dark matter particle positions. Over time the mesh is deformed by gravitational forces, causing the tetrahedral cells to warp and overlap. The new methods are well suited to visualize the cosmic web. In particular they preserve caustics, regions of high density that emerge, when several streams of dark matter particles share the same location in space, indicating the formation of structures like sheets, filaments and halos. We demonstrate the superior image quality of the new approaches in a comparison with three standard rendering techniques for N-body simulation data. | false | false | [
"Ralf Kähler",
"Oliver Hahn",
"Tom Abel"
] | [] | [
"P"
] | [
{
"name": "Paper Preprint",
"url": "http://arxiv.org/pdf/1208.3206v1",
"icon": "paper"
}
] |
SciVis | 2,012 | A Perceptual-Statistics Shading Model | 10.1109/TVCG.2012.188 | The process of surface perception is complex and based on several influencing factors, e.g., shading, silhouettes, occluding contours, and top down cognition. The accuracy of surface perception can be measured and the influencing factors can be modified in order to decrease the error in perception. This paper presents a novel concept of how a perceptual evaluation of a visualization technique can contribute to its redesign with the aim of improving the match between the distal and the proximal stimulus. During analysis of data from previous perceptual studies, we observed that the slant of 3D surfaces visualized on 2D screens is systematically underestimated. The visible trends in the error allowed us to create a statistical model of the perceived surface slant. Based on this statistical model we obtained from user experiments, we derived a new shading model that uses adjusted surface normals and aims to reduce the error in slant perception. The result is a shape-enhancement of visualization which is driven by an experimentally-founded statistical model. To assess the efficiency of the statistical shading model, we repeated the evaluation experiment and confirmed that the error in perception was decreased. Results of both user experiments are publicly-available datasets. | false | false | [
"Veronika Soltészová",
"Cagatay Turkay",
"Mark C. Price",
"Ivan Viola"
] | [] | [] | [] |
SciVis | 2,012 | A Visual Analysis Concept for the Validation of Geoscientific Simulation Models | 10.1109/TVCG.2012.190 | Geoscientific modeling and simulation helps to improve our understanding of the complex Earth system. During the modeling process, validation of the geoscientific model is an essential step. In validation, it is determined whether the model output shows sufficient agreement with observation data. Measures for this agreement are called goodness of fit. In the geosciences, analyzing the goodness of fit is challenging due to its manifold dependencies: 1) The goodness of fit depends on the model parameterization, whose precise values are not known. 2) The goodness of fit varies in space and time due to the spatio-temporal dimension of geoscientific models. 3) The significance of the goodness of fit is affected by resolution and preciseness of available observational data. 4) The correlation between goodness of fit and underlying modeled and observed values is ambiguous. In this paper, we introduce a visual analysis concept that targets these challenges in the validation of geoscientific models - specifically focusing on applications where observation data is sparse, unevenly distributed in space and time, and imprecise, which hinders a rigorous analytical approach. Our concept, developed in close cooperation with Earth system modelers, addresses the four challenges by four tailored visualization components. The tight linking of these components supports a twofold interactive drill-down in model parameter space and in the set of data samples, which facilitates the exploration of the numerous dependencies of the goodness of fit. We exemplify our visualization concept for geoscientific modeling of glacial isostatic adjustments in the last 100,000 years, validated against sea levels indicators - a prominent example for sparse and imprecise observation data. An initial use case and feedback from Earth system modelers indicate that our visualization concept is a valuable complement to the range of validation methods. | false | false | [
"Andrea Unger",
"Sven Schulte",
"Volker Klemann",
"Doris Dransch"
] | [] | [] | [] |
SciVis | 2,012 | An Adaptive Prediction-Based Approach to Lossless Compression of Floating-Point Volume Data | 10.1109/TVCG.2012.194 | In this work, we address the problem of lossless compression of scientific and medical floating-point volume data. We propose two prediction-based compression methods that share a common framework, which consists of a switched prediction scheme wherein the best predictor out of a preset group of linear predictors is selected. Such a scheme is able to adapt to different datasets as well as to varying statistics within the data. The first method, called APE (Adaptive Polynomial Encoder), uses a family of structured interpolating polynomials for prediction, while the second method, which we refer to as ACE (Adaptive Combined Encoder), combines predictors from previous work with the polynomial predictors to yield a more flexible, powerful encoder that is able to effectively decorrelate a wide range of data. In addition, in order to facilitate efficient visualization of compressed data, our scheme provides an option to partition floating-point values in such a way as to provide a progressive representation. We compare our two compressors to existing state-of-the-art lossless floating-point compressors for scientific data, with our data suite including both computer simulations and observational measurements. The results demonstrate that our polynomial predictor, APE, is comparable to previous approaches in terms of speed but achieves better compression rates on average. ACE, our combined predictor, while somewhat slower, is able to achieve the best compression rate on all datasets, with significantly better rates on most of the datasets. | false | false | [
"Nathaniel Fout",
"Kwan-Liu Ma"
] | [] | [] | [] |
SciVis | 2,012 | Analysis of Streamline Separation at Infinity Using Time-Discrete Markov Chains | 10.1109/TVCG.2012.198 | Existing methods for analyzing separation of streamlines are often restricted to a finite time or a local area. In our paper we introduce a new method that complements them by allowing an infinite-time-evaluation of steady planar vector fields. Our algorithm unifies combinatorial and probabilistic methods and introduces the concept of separation in time-discrete Markov-Chains. We compute particle distributions instead of the streamlines of single particles. We encode the flow into a map and then into a transition matrix for each time direction. Finally, we compare the results of our grid-independent algorithm to the popular Finite-Time-Lyapunov-Exponents and discuss the discrepancies. | false | false | [
"Wieland Reich",
"Gerik Scheuermann"
] | [] | [] | [] |
SciVis | 2,012 | Augmented Topological Descriptors of Pore Networks for Material Science | 10.1109/TVCG.2012.200 | One potential solution to reduce the concentration of carbon dioxide in the atmosphere is the geologic storage of captured CO<sub>2</sub> in underground rock formations, also known as carbon sequestration. There is ongoing research to guarantee that this process is both efficient and safe. We describe tools that provide measurements of media porosity, and permeability estimates, including visualization of pore structures. Existing standard algorithms make limited use of geometric information in calculating permeability of complex microstructures. This quantity is important for the analysis of biomineralization, a subsurface process that can affect physical properties of porous media. This paper introduces geometric and topological descriptors that enhance the estimation of material permeability. Our analysis framework includes the processing of experimental data, segmentation, and feature extraction and making novel use of multiscale topological analysis to quantify maximum flow through porous networks. We illustrate our results using synchrotron-based X-ray computed microtomography of glass beads during biomineralization. We also benchmark the proposed algorithms using simulated data sets modeling jammed packed bead beds of a monodispersive material. | false | false | [
"Daniela Ushizima",
"Dmitriy Morozov",
"Gunther H. Weber",
"Andrea G. C. Bianchi",
"James A. Sethian",
"E. Wes Bethel"
] | [] | [] | [] |
SciVis | 2,012 | Automatic Detection and Visualization of Qualitative Hemodynamic Characteristics in Cerebral Aneurysms | 10.1109/TVCG.2012.202 | Cerebral aneurysms are a pathological vessel dilatation that bear a high risk of rupture. For the understanding and evaluation of the risk of rupture, the analysis of hemodynamic information plays an important role. Besides quantitative hemodynamic information, also qualitative flow characteristics, e.g., the inflow jet and impingement zone are correlated with the risk of rupture. However, the assessment of these two characteristics is currently based on an interactive visual investigation of the flow field, obtained by computational fluid dynamics (CFD) or blood flow measurements. We present an automatic and robust detection as well as an expressive visualization of these characteristics. The detection can be used to support a comparison, e.g., of simulation results reflecting different treatment options. Our approach utilizes local streamline properties to formalize the inflow jet and impingement zone. We extract a characteristic seeding curve on the ostium, on which an inflow jet boundary contour is constructed. Based on this boundary contour we identify the impingement zone. Furthermore, we present several visualization techniques to depict both characteristics expressively. Thereby, we consider accuracy and robustness of the extracted characteristics, minimal visual clutter and occlusions. An evaluation with six domain experts confirms that our approach detects both hemodynamic characteristics reasonably. | false | false | [
"Rocco Gasteiger",
"Dirk J. Lehmann",
"Roy van Pelt",
"Gábor Janiga",
"Oliver Beuing",
"Anna Vilanova",
"Holger Theisel",
"Bernhard Preim"
] | [] | [] | [] |
SciVis | 2,012 | Automatic Tuning of Spatially Varying Transfer Functions for Blood Vessel Visualization | 10.1109/TVCG.2012.203 | Computed Tomography Angiography (CTA) is commonly used in clinical routine for diagnosing vascular diseases. The procedure involves the injection of a contrast agent into the blood stream to increase the contrast between the blood vessels and the surrounding tissue in the image data. CTA is often visualized with Direct Volume Rendering (DVR) where the enhanced image contrast is important for the construction of Transfer Functions (TFs). For increased efficiency, clinical routine heavily relies on preset TFs to simplify the creation of such visualizations for a physician. In practice, however, TF presets often do not yield optimal images due to variations in mixture concentration of contrast agent in the blood stream. In this paper we propose an automatic, optimization-based method that shifts TF presets to account for general deviations and local variations of the intensity of contrast enhanced blood vessels. Some of the advantages of this method are the following. It computationally automates large parts of a process that is currently performed manually. It performs the TF shift locally and can thus optimize larger portions of the image than is possible with manual interaction. The method is based on a well known vesselness descriptor in the definition of the optimization criterion. The performance of the method is illustrated by clinically relevant CT angiography datasets displaying both improved structural overviews of vessel trees and improved adaption to local variations of contrast concentration. | false | false | [
"Gunnar Läthén",
"Stefan Lindholm",
"Reiner Lenz",
"Anders Persson",
"Magnus Borga"
] | [] | [] | [] |
SciVis | 2,012 | Coherency-Based Curve Compression for High-Order finite Element Model Visualization | 10.1109/TVCG.2012.206 | Finite element (FE) models are frequently used in engineering and life sciences within time-consuming simulations. In contrast with the regular grid structure facilitated by volumetric data sets, as used in medicine or geosciences, FE models are defined over a non-uniform grid. Elements can have curved faces and their interior can be defined through high-order basis functions, which pose additional challenges when visualizing these models. During ray-casting, the uniformly distributed sample points along each viewing ray must be transformed into the material space defined within each element. The computational complexity of this transformation makes a straightforward approach inadequate for interactive data exploration. In this paper, we introduce a novel coherency-based method which supports the interactive exploration of FE models by decoupling the expensive world-to-material space transformation from the rendering stage, thereby allowing it to be performed within a precomputation stage. Therefore, our approach computes view-independent proxy rays in material space, which are clustered to facilitate data reduction. During rendering, these proxy rays are accessed, and it becomes possible to visually analyze high-order FE models at interactive frame rates, even when they are time-varying or consist of multiple modalities. Within this paper, we provide the necessary background about the FE data, describe our decoupling method, and introduce our interactive rendering algorithm. Furthermore, we provide visual results and analyze the error introduced by the presented approach. | false | false | [
"Alexander Bock 0002",
"Erik Sundén",
"Bingchen Liu",
"Burkhard Wünsche",
"Timo Ropinski"
] | [] | [] | [] |
SciVis | 2,012 | Computing Morse-Smale Complexes with Accurate Geometry | 10.1109/TVCG.2012.209 | Topological techniques have proven highly successful in analyzing and visualizing scientific data. As a result, significant efforts have been made to compute structures like the Morse-Smale complex as robustly and efficiently as possible. However, the resulting algorithms, while topologically consistent, often produce incorrect connectivity as well as poor geometry. These problems may compromise or even invalidate any subsequent analysis. Moreover, such techniques may fail to improve even when the resolution of the domain mesh is increased, thus producing potentially incorrect results even for highly resolved functions. To address these problems we introduce two new algorithms: (i) a randomized algorithm to compute the discrete gradient of a scalar field that converges under refinement; and (ii) a deterministic variant which directly computes accurate geometry and thus correct connectivity of the MS complex. The first algorithm converges in the sense that on average it produces the correct result and its standard deviation approaches zero with increasing mesh resolution. The second algorithm uses two ordered traversals of the function to integrate the probabilities of the first to extract correct (near optimal) geometry and connectivity. We present an extensive empirical study using both synthetic and real-world data and demonstrates the advantages of our algorithms in comparison with several popular approaches. | false | false | [
"Attila Gyulassy",
"Peer-Timo Bremer",
"Valerio Pascucci"
] | [] | [] | [] |
SciVis | 2,012 | Cumulative Heat Diffusion Using Volume Gradient Operator for Volume Analysis | 10.1109/TVCG.2012.210 | We introduce a simple, yet powerful method called the Cumulative Heat Diffusion for shape-based volume analysis, while drastically reducing the computational cost compared to conventional heat diffusion. Unlike the conventional heat diffusion process, where the diffusion is carried out by considering each node separately as the source, we simultaneously consider all the voxels as sources and carry out the diffusion, hence the term cumulative heat diffusion. In addition, we introduce a new operator that is used in the evaluation of cumulative heat diffusion called the Volume Gradient Operator (VGO). VGO is a combination of the LBO and a data-driven operator which is a function of the half gradient. The half gradient is the absolute value of the difference between the voxel intensities. The VGO by its definition captures the local shape information and is used to assign the initial heat values. Furthermore, VGO is also used as the weighting parameter for the heat diffusion process. We demonstrate that our approach can robustly extract shape-based features and thus forms the basis for an improved classification and exploration of features based on shape. | false | false | [
"Krishna Chaitanya Gurijala",
"Lei Wang 0024",
"Arie E. Kaufman"
] | [] | [] | [] |
SciVis | 2,012 | Derived Metric Tensors for Flow Surface Visualization | 10.1109/TVCG.2012.211 | Integral flow surfaces constitute a widely used flow visualization tool due to their capability to convey important flow information such as fluid transport, mixing, and domain segmentation. Current flow surface rendering techniques limit their expressiveness, however, by focusing virtually exclusively on displacement visualization, visually neglecting the more complex notion of deformation such as shearing and stretching that is central to the field of continuum mechanics. To incorporate this information into the flow surface visualization and analysis process, we derive a metric tensor field that encodes local surface deformations as induced by the velocity gradient of the underlying flow field. We demonstrate how properties of the resulting metric tensor field are capable of enhancing present surface visualization and generation methods and develop novel surface querying, sampling, and visualization techniques. The provided results show how this step towards unifying classic flow visualization and more advanced concepts from continuum mechanics enables more detailed and improved flow analysis. | false | false | [
"Harald Obermaier",
"Kenneth I. Joy"
] | [] | [] | [] |
SciVis | 2,012 | Effects of Stereo and Screen Size on the Legibility of Three-Dimensional Streamtube Visualization | 10.1109/TVCG.2012.216 | We report the impact of display characteristics (stereo and size) on task performance in diffusion magnetic resonance imaging (DMRI) in a user study with 12 participants. The hypotheses were that (1) adding stereo and increasing display size would improve task accuracy and reduce completion time, and (2) the greater the complexity of a spatial task, the greater the benefits of an improved display. Thus we expected to see greater performance gains when detailed visual reasoning was required. Participants used dense streamtube visualizations to perform five representative tasks: (1) determine the higher average fractional anisotropy (FA) values between two regions, (2) find the endpoints of fiber tracts, (3) name a bundle, (4) mark a brain lesion, and (5) judge if tracts belong to the same bundle. Contrary to our hypotheses, we found the task completion time was not improved by the use of the larger display and that performance accuracy was hurt rather than helped by the introduction of stereo in our study with dense DMRI data. Bigger was not always better. Thus cautious should be taken when selecting displays for scientific visualization applications. We explored the results further using the body-scale unit and subjective size and stereo experiences. | false | false | [
"Jian Chen 0006",
"Haipeng Cai",
"Alexander P. Auchus",
"David H. Laidlaw"
] | [] | [] | [] |
SciVis | 2,012 | Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input | 10.1109/TVCG.2012.217 | Data selection is a fundamental task in visualization because it serves as a pre-requisite to many follow-up interactions. Efficient spatial selection in 3D point cloud datasets consisting of thousands or millions of particles can be particularly challenging. We present two new techniques, TeddySelection and CloudLasso, that support the selection of subsets in large particle 3D datasets in an interactive and visually intuitive manner. Specifically, we describe how to spatially select a subset of a 3D particle cloud by simply encircling the target particles on screen using either the mouse or direct-touch input. Based on the drawn lasso, our techniques automatically determine a bounding selection surface around the encircled particles based on their density. This kind of selection technique can be applied to particle datasets in several application domains. TeddySelection and CloudLasso reduce, and in some cases even eliminate, the need for complex multi-step selection processes involving Boolean operations. This was confirmed in a formal, controlled user study in which we compared the more flexible CloudLasso technique to the standard cylinder-based selection technique. This study showed that the former is consistently more efficient than the latter - in several cases the CloudLasso selection time was half that of the corresponding cylinder-based selection. | false | false | [
"Lingyun Yu 0001",
"Konstantinos Efstathiou 0001",
"Petra Isenberg",
"Tobias Isenberg 0001"
] | [
"TT",
"HM"
] | [] | [] |
SciVis | 2,012 | ElVis: A System for the Accurate and Interactive Visualization of High-Order finite Element Solutions | 10.1109/TVCG.2012.218 | This paper presents the Element Visualizer (ElVis), a new, open-source scientific visualization system for use with high-order finite element solutions to PDEs in three dimensions. This system is designed to minimize visualization errors of these types of fields by querying the underlying finite element basis functions (e.g., high-order polynomials) directly, leading to pixel-exact representations of solutions and geometry. The system interacts with simulation data through runtime plugins, which only require users to implement a handful of operations fundamental to finite element solvers. The data in turn can be visualized through the use of cut surfaces, contours, isosurfaces, and volume rendering. These visualization algorithms are implemented using NVIDIA's OptiX GPU-based ray-tracing engine, which provides accelerated ray traversal of the high-order geometry, and CUDA, which allows for effective parallel evaluation of the visualization algorithms. The direct interface between ElVis and the underlying data differentiates it from existing visualization tools. Current tools assume the underlying data is composed of linear primitives; high-order data must be interpolated with linear functions as a result. In this work, examples drawn from aerodynamic simulations-high-order discontinuous Galerkin finite element solutions of aerodynamic flows in particular-will demonstrate the superiority of ElVis' pixel-exact approach when compared with traditional linear-interpolation methods. Such methods can introduce a number of inaccuracies in the resulting visualization, making it unclear if visual artifacts are genuine to the solution data or if these artifacts are the result of interpolation errors. Linear methods additionally cannot properly visualize curved geometries (elements or boundaries) which can greatly inhibit developers' debugging efforts. As we will show, pixel-exact visualization exhibits none of these issues, removing the visualization scheme as a source of uncertainty for engineers using ElVis. | false | false | [
"Blake Nelson",
"Eric Liu",
"Robert M. Kirby",
"Robert Haimes"
] | [] | [] | [] |
SciVis | 2,012 | Evaluation of Fast-Forward Video Visualization | 10.1109/TVCG.2012.222 | We evaluate and compare video visualization techniques based on fast-forward. A controlled laboratory user study (n = 24) was conducted to determine the trade-off between support of object identification and motion perception, two properties that have to be considered when choosing a particular fast-forward visualization. We compare four different visualizations: two representing the state-of-the-art and two new variants of visualization introduced in this paper. The two state-of-the-art methods we consider are frame-skipping and temporal blending of successive frames. Our object trail visualization leverages a combination of frame-skipping and temporal blending, whereas predictive trajectory visualization supports motion perception by augmenting the video frames with an arrow that indicates the future object trajectory. Our hypothesis was that each of the state-of-the-art methods satisfies just one of the goals: support of object identification or motion perception. Thus, they represent both ends of the visualization design. The key findings of the evaluation are that object trail visualization supports object identification, whereas predictive trajectory visualization is most useful for motion perception. However, frame-skipping surprisingly exhibits reasonable performance for both tasks. Furthermore, we evaluate the subjective performance of three different playback speed visualizations for adaptive fast-forward, a subdomain of video fast-forward. | false | false | [
"Markus Höferlin",
"Kuno Kurzhals",
"Benjamin Höferlin",
"Gunther Heidemann",
"Daniel Weiskopf"
] | [] | [] | [] |
SciVis | 2,012 | Evaluation of Multivariate Visualization on a Multivariate Task | 10.1109/TVCG.2012.223 | Multivariate visualization techniques have attracted great interest as the dimensionality of data sets grows. One premise of such techniques is that simultaneous visual representation of multiple variables will enable the data analyst to detect patterns amongst multiple variables. Such insights could lead to development of new techniques for rigorous (numerical) analysis of complex relationships hidden within the data. Two natural questions arise from this premise: Which multivariate visualization techniques are the most effective for high-dimensional data sets? How does the analysis task change this utility ranking? We present a user study with a new task to answer the first question. We provide some insights to the second question based on the results of our study and results available in the literature. Our task led to significant differences in error, response time, and subjective workload ratings amongst four visualization techniques. We implemented three integrated techniques (Data-driven Spots, Oriented Slivers, and Attribute Blocks), as well as a baseline case of separate grayscale images. The baseline case fared poorly on all three measures, whereas Datadriven Spots yielded the best accuracy and was among the best in response time. These results differ from comparisons of similar techniques with other tasks, and we review all the techniques, tasks, and results (from our work and previous work) to understand the reasons for this discrepancy. | false | false | [
"Mark A. Livingston",
"Jonathan W. Decker",
"Zhuming Ai"
] | [] | [] | [] |
SciVis | 2,012 | Fuzzy Volume Rendering | 10.1109/TVCG.2012.227 | In order to assess the reliability of volume rendering, it is necessary to consider the uncertainty associated with the volume data and how it is propagated through the volume rendering algorithm, as well as the contribution to uncertainty from the rendering algorithm itself. In this work, we show how to apply concepts from the field of reliable computing in order to build a framework for management of uncertainty in volume rendering, with the result being a self-validating computational model to compute a posteriori uncertainty bounds. We begin by adopting a coherent, unifying possibility-based representation of uncertainty that is able to capture the various forms of uncertainty that appear in visualization, including variability, imprecision, and fuzziness. Next, we extend the concept of the fuzzy transform in order to derive rules for accumulation and propagation of uncertainty. This representation and propagation of uncertainty together constitute an automated framework for management of uncertainty in visualization, which we then apply to volume rendering. The result, which we call fuzzy volume rendering, is an uncertainty-aware rendering algorithm able to produce more complete depictions of the volume data, thereby allowing more reliable conclusions and informed decisions. Finally, we compare approaches for self-validated computation in volume rendering, demonstrating that our chosen method has the ability to handle complex uncertainty while maintaining efficiency. | false | false | [
"Nathaniel Fout",
"Kwan-Liu Ma"
] | [] | [] | [] |
SciVis | 2,012 | Generalized Topological Simplification of Scalar fields on Surfaces | 10.1109/TVCG.2012.228 | We present a combinatorial algorithm for the general topological simplification of scalar fields on surfaces. Given a scalar field f, our algorithm generates a simplified field g that provably admits only critical points from a constrained subset of the singularities of f, while guaranteeing a small distance ||f - g||∞for data-fitting purpose. In contrast to previous algorithms, our approach is oblivious to the strategy used for selecting features of interest and allows critical points to be removed arbitrarily. When topological persistence is used to select the features of interest, our algorithm produces a standard ϵ-simplification. Our approach is based on a new iterative algorithm for the constrained reconstruction of sub- and sur-level sets. Extensive experiments show that the number of iterations required for our algorithm to converge is rarely greater than 2 and never greater than 5, yielding O(n log(n)) practical time performances. The algorithm handles triangulated surfaces with or without boundary and is robust to the presence of multi-saddles in the input. It is simple to implement, fast in practice and more general than previous techniques. Practically, our approach allows a user to arbitrarily simplify the topology of an input function and robustly generate the corresponding simplified function. An appealing application area of our algorithm is in scalar field design since it enables, without any threshold parameter, the robust pruning of topological noise as selected by the user. This is needed for example to get rid of inaccuracies introduced by numerical solvers, thereby providing topological guarantees needed for certified geometry processing. Experiments show this ability to eliminate numerical noise as well as validate the time efficiency and accuracy of our algorithm. We provide a lightweight C++ implementation as supplemental material that can be used for topological cleaning on surface meshes. | false | false | [
"Julien Tierny",
"Valerio Pascucci"
] | [] | [] | [] |
SciVis | 2,012 | Hierarchical Exploration of Volumes Using Multilevel Segmentation of the Intensity-Gradient Histograms | 10.1109/TVCG.2012.231 | Visual exploration of volumetric datasets to discover the embedded features and spatial structures is a challenging and tedious task. In this paper we present a semi-automatic approach to this problem that works by visually segmenting the intensity-gradient 2D histogram of a volumetric dataset into an exploration hierarchy. Our approach mimics user exploration behavior by analyzing the histogram with the normalized-cut multilevel segmentation technique. Unlike previous work in this area, our technique segments the histogram into a reasonable set of intuitive components that are mutually exclusive and collectively exhaustive. We use information-theoretic measures of the volumetric data segments to guide the exploration. This provides a data-driven coarse-to-fine hierarchy for a user to interactively navigate the volume in a meaningful manner. | false | false | [
"Cheuk Yiu Ip",
"Amitabh Varshney",
"Joseph F. JáJá"
] | [
"BP"
] | [] | [] |
SciVis | 2,012 | Historygrams: Enabling Interactive Global Illumination in Direct Volume Rendering using Photon Mapping | 10.1109/TVCG.2012.232 | In this paper, we enable interactive volumetric global illumination by extending photon mapping techniques to handle interactive transfer function (TF) and material editing in the context of volume rendering. We propose novel algorithms and data structures for finding and evaluating parts of a scene affected by these parameter changes, and thus support efficient updates of the photon map. In direct volume rendering (DVR) the ability to explore volume data using parameter changes, such as editable TFs, is of key importance. Advanced global illumination techniques are in most cases computationally too expensive, as they prevent the desired interactivity. Our technique decreases the amount of computation caused by parameter changes, by introducing Historygrams which allow us to efficiently reuse previously computed photon media interactions. Along the viewing rays, we utilize properties of the light transport equations to subdivide a view-ray into segments and independently update them when invalid. Unlike segments of a view-ray, photon scattering events within the volumetric medium needs to be sequentially updated. Using our Historygram approach, we can identify the first invalid photon interaction caused by a property change, and thus reuse all valid photon interactions. Combining these two novel concepts, supports interactive editing of parameters when using volumetric photon mapping in the context of DVR. As a consequence, we can handle arbitrarily shaped and positioned light sources, arbitrary phase functions, bidirectional reflectance distribution functions and multiple scattering which has previously not been possible in interactive DVR. | false | false | [
"Daniel Jönsson",
"Joel Kronander",
"Timo Ropinski",
"Anders Ynnerman"
] | [] | [] | [] |
SciVis | 2,012 | Human Computation in Visualization: Using Purpose Driven Games for Robust Evaluation of Visualization Algorithms | 10.1109/TVCG.2012.234 | Due to the inherent characteristics of the visualization process, most of the problems in this field have strong ties with human cognition and perception. This makes the human brain and sensory system the only truly appropriate evaluation platform for evaluating and fine-tuning a new visualization method or paradigm. However, getting humans to volunteer for these purposes has always been a significant obstacle, and thus this phase of the development process has traditionally formed a bottleneck, slowing down progress in visualization research. We propose to take advantage of the newly emerging field of Human Computation (HC) to overcome these challenges. HC promotes the idea that rather than considering humans as users of the computational system, they can be made part of a hybrid computational loop consisting of traditional computation resources and the human brain and sensory system. This approach is particularly successful in cases where part of the computational problem is considered intractable using known computer algorithms but is trivial to common sense human knowledge. In this paper, we focus on HC from the perspective of solving visualization problems and also outline a framework by which humans can be easily seduced to volunteer their HC resources. We introduce a purpose-driven game titled “Disguise” which serves as a prototypical example for how the evaluation of visualization algorithms can be mapped into a fun and addicting activity, allowing this task to be accomplished in an extensive yet cost effective way. Finally, we sketch out a framework that transcends from the pure evaluation of existing visualization methods to the design of a new one. | false | false | [
"Nafees U. Ahmed",
"Ziyi Zheng",
"Klaus Mueller 0001"
] | [] | [] | [] |
SciVis | 2,012 | Interactive Retro-Deformation of Terrain for Reconstructing 3D Fault Displacements | 10.1109/TVCG.2012.239 | Planetary topography is the result of complex interactions between geological processes, of which faulting is a prominent component. Surface-rupturing earthquakes cut and move landforms which develop across active faults, producing characteristic surface displacements across the fault. Geometric models of faults and their associated surface displacements are commonly applied to reconstruct these offsets to enable interpretation of the observed topography. However, current 2D techniques are limited in their capability to convey both the three-dimensional kinematics of faulting and the incremental sequence of events required by a given reconstruction. Here we present a real-time system for interactive retro-deformation of faulted topography to enable reconstruction of fault displacement within a high-resolution (sub 1m/pixel) 3D terrain visualization. We employ geometry shaders on the GPU to intersect the surface mesh with fault-segments interactively specified by the user and transform the resulting surface blocks in realtime according to a kinematic model of fault motion. Our method facilitates a human-in-the-loop approach to reconstruction of fault displacements by providing instant visual feedback while exploring the parameter space. Thus, scientists can evaluate the validity of traditional point-to-point reconstructions by visually examining a smooth interpolation of the displacement in 3D. We show the efficacy of our approach by using it to reconstruct segments of the San Andreas fault, California as well as a graben structure in the Noctis Labyrinthus region on Mars. | false | false | [
"Rolf Westerteiger",
"Tracy Compton",
"Tony Bernardin",
"Eric S. Cowgill",
"Klaus Gwinner",
"Bernd Hamann",
"Andreas Gerndt",
"Hans Hagen"
] | [] | [] | [] |
SciVis | 2,012 | Interactive Volume Exploration of Petascale Microscopy Data Streams Using a Visualization-Driven Virtual Memory Approach | 10.1109/TVCG.2012.240 | This paper presents the first volume visualization system that scales to petascale volumes imaged as a continuous stream of high-resolution electron microscopy images. Our architecture scales to dense, anisotropic petascale volumes because it: (1) decouples construction of the 3D multi-resolution representation required for visualization from data acquisition, and (2) decouples sample access time during ray-casting from the size of the multi-resolution hierarchy. Our system is designed around a scalable multi-resolution virtual memory architecture that handles missing data naturally, does not pre-compute any 3D multi-resolution representation such as an octree, and can accept a constant stream of 2D image tiles from the microscopes. A novelty of our system design is that it is visualization-driven: we restrict most computations to the visible volume data. Leveraging the virtual memory architecture, missing data are detected during volume ray-casting as cache misses, which are propagated backwards for on-demand out-of-core processing. 3D blocks of volume data are only constructed from 2D microscope image tiles when they have actually been accessed during ray-casting. We extensively evaluate our system design choices with respect to scalability and performance, compare to previous best-of-breed systems, and illustrate the effectiveness of our system for real microscopy data from neuroscience. | false | false | [
"Markus Hadwiger",
"Johanna Beyer",
"Won-Ki Jeong",
"Hanspeter Pfister"
] | [
"HM"
] | [] | [] |
SciVis | 2,012 | KnotPad: Visualizing and Exploring Knot Theory with Fluid Reidemeister Moves | 10.1109/TVCG.2012.242 | We present KnotPad, an interactive paper-like system for visualizing and exploring mathematical knots; we exploit topological drawing and math-aware deformation methods in particular to enable and enrich our interactions with knot diagrams. Whereas most previous efforts typically employ physically based modeling to simulate the 3D dynamics of knots and ropes, our tool offers a Reidemeister move based interactive environment that is much closer to the topological problems being solved in knot theory, yet without interfering with the traditional advantages of paper-based analysis and manipulation of knot diagrams. Drawing knot diagrams with many crossings and producing their equivalent is quite challenging and error-prone. KnotPad can restrict user manipulations to the three types of Reidemeister moves, resulting in a more fluid yet mathematically correct user experience with knots. For our principal test case of mathematical knots, KnotPad permits us to draw and edit their diagrams empowered by a family of interactive techniques. Furthermore, we exploit supplementary interface elements to enrich the user experiences. For example, KnotPad allows one to pull and drag on knot diagrams to produce mathematically valid moves. Navigation enhancements in KnotPad provide still further improvement: by remembering and displaying the sequence of valid moves applied during the entire interaction, KnotPad allows a much cleaner exploratory interface for the user to analyze and study knot equivalence. All these methods combine to reveal the complex spatial relationships of knot diagrams with a mathematically true and rich user experience. | false | false | [
"Hui Zhang 0006",
"Jianguang Weng",
"Lin Jing",
"Yiwen Zhong"
] | [] | [] | [] |
SciVis | 2,012 | Lagrangian Coherent Structures for Design Analysis of Revolving Doors | 10.1109/TVCG.2012.243 | Room air flow and air exchange are important aspects for the design of energy-efficient buildings. As a result, simulations are increasingly used prior to construction to achieve an energy-efficient design. We present a visual analysis of air flow generated at building entrances, which uses a combination of revolving doors and air curtains. The resulting flow pattern is challenging because of two interacting flow patterns: On the one hand, the revolving door acts as a pump, on the other hand, the air curtain creates a layer of uniformly moving warm air between the interior of the building and the revolving door. Lagrangian coherent structures (LCS), which by definition are flow barriers, are the method of choice for visualizing the separation and recirculation behavior of warm and cold air flow. The extraction of LCS is based on the finite-time Lyapunov exponent (FTLE) and makes use of a ridge definition which is consistent with the concept of weak LCS. Both FTLE computation and ridge extraction are done in a robust and efficient way by making use of the fast Fourier transform for computing scale-space derivatives. | false | false | [
"Benjamin Schindler",
"Raphael Fuchs",
"Stefan Barp",
"Jürgen Waser",
"Armin Pobitzer",
"Robert Carnecky",
"Kresimir Matkovic",
"Ronald Peikert"
] | [] | [] | [] |
SciVis | 2,012 | Multivariate Data Analysis Using Persistence-Based filtering and Topological Signatures | 10.1109/TVCG.2012.248 | The extraction of significant structures in arbitrary high-dimensional data sets is a challenging task. Moreover, classifying data points as noise in order to reduce a data set bears special relevance for many application domains. Standard methods such as clustering serve to reduce problem complexity by providing the user with classes of similar entities. However, they usually do not highlight relations between different entities and require a stopping criterion, e.g. the number of clusters to be detected. In this paper, we present a visualization pipeline based on recent advancements in algebraic topology. More precisely, we employ methods from persistent homology that enable topological data analysis on high-dimensional data sets. Our pipeline inherently copes with noisy data and data sets of arbitrary dimensions. It extracts central structures of a data set in a hierarchical manner by using a persistence-based filtering algorithm that is theoretically well-founded. We furthermore introduce persistence rings, a novel visualization technique for a class of topological features-the persistence intervals-of large data sets. Persistence rings provide a unique topological signature of a data set, which helps in recognizing similarities. In addition, we provide interactive visualization techniques that assist the user in evaluating the parameter space of our method in order to extract relevant structures. We describe and evaluate our analysis pipeline by means of two very distinct classes of data sets: First, a class of synthetic data sets containing topological objects is employed to highlight the interaction capabilities of our method. Second, in order to affirm the utility of our technique, we analyse a class of high-dimensional real-world data sets arising from current research in cultural heritage. | false | false | [
"Bastian Rieck",
"Hubert Mara",
"Heike Leitte"
] | [] | [] | [] |
SciVis | 2,012 | On the Interpolation of Data with Normally Distributed Uncertainty for Visualization | 10.1109/TVCG.2012.249 | In many fields of science or engineering, we are confronted with uncertain data. For that reason, the visualization of uncertainty received a lot of attention, especially in recent years. In the majority of cases, Gaussian distributions are used to describe uncertain behavior, because they are able to model many phenomena encountered in science. Therefore, in most applications uncertain data is (or is assumed to be) Gaussian distributed. If such uncertain data is given on fixed positions, the question of interpolation arises for many visualization approaches. In this paper, we analyze the effects of the usual linear interpolation schemes for visualization of Gaussian distributed data. In addition, we demonstrate that methods known in geostatistics and machine learning have favorable properties for visualization purposes in this case. | false | false | [
"Steven Schlegel",
"Nico Korn",
"Gerik Scheuermann"
] | [] | [] | [] |
SciVis | 2,012 | SeiVis: An Interactive Visual Subsurface Modeling Application | 10.1109/TVCG.2012.259 | The most important resources to fulfill today's energy demands are fossil fuels, such as oil and natural gas. When exploiting hydrocarbon reservoirs, a detailed and credible model of the subsurface structures is crucial in order to minimize economic and ecological risks. Creating such a model is an inverse problem: reconstructing structures from measured reflection seismics. The major challenge here is twofold: First, the structures in highly ambiguous seismic data are interpreted in the time domain. Second, a velocity model has to be built from this interpretation to match the model to depth measurements from wells. If it is not possible to obtain a match at all positions, the interpretation has to be updated, going back to the first step. This results in a lengthy back and forth between the different steps, or in an unphysical velocity model in many cases. This paper presents a novel, integrated approach to interactively creating subsurface models from reflection seismics. It integrates the interpretation of the seismic data using an interactive horizon extraction technique based on piecewise global optimization with velocity modeling. Computing and visualizing the effects of changes to the interpretation and velocity model on the depth-converted model on the fly enables an integrated feedback loop that enables a completely new connection of the seismic data in time domain and well data in depth domain. Using a novel joint time/depth visualization, depicting side-by-side views of the original and the resulting depth-converted data, domain experts can directly fit their interpretation in time domain to spatial ground truth data. We have conducted a domain expert evaluation, which illustrates that the presented workflow enables the creation of exact subsurface models much more rapidly than previous approaches. | false | false | [
"Thomas Höllt",
"Wolfgang Freiler",
"Fritz Gschwantner",
"Helmut Doleisch",
"Gabor Heinemann",
"Markus Hadwiger"
] | [] | [] | [] |
SciVis | 2,012 | Sketching Uncertainty into Simulations | 10.1109/TVCG.2012.261 | In a variety of application areas, the use of simulation steering in decision making is limited at best. Research focusing on this problem suggests that most user interfaces are too complex for the end user. Our goal is to let users create and investigate multiple, alternative scenarios without the need for special simulation expertise. To simplify the specification of parameters, we move from a traditional manipulation of numbers to a sketch-based input approach. Users steer both numeric parameters and parameters with a spatial correspondence by sketching a change onto the rendering. Special visualizations provide immediate visual feedback on how the sketches are transformed into boundary conditions of the simulation models. Since uncertainty with respect to many intertwined parameters plays an important role in planning, we also allow the user to intuitively setup complete value ranges, which are then automatically transformed into ensemble simulations. The interface and the underlying system were developed in collaboration with experts in the field of flood management. The real-world data they have provided has allowed us to construct scenarios used to evaluate the system. These were presented to a variety of flood response personnel, and their feedback is discussed in detail in the paper. The interface was found to be intuitive and relevant, although a certain amount of training might be necessary. | false | false | [
"Hrvoje Ribicic",
"Jürgen Waser",
"Roman Gurbat",
"Bernhard Sadransky",
"M. Eduard Gröller"
] | [] | [] | [] |
SciVis | 2,012 | Structure-Aware Lighting Design for Volume Visualization | 10.1109/TVCG.2012.267 | Lighting design is a complex, but fundamental, problem in many fields. In volume visualization, direct volume rendering generates an informative image without external lighting, as each voxel itself emits radiance. However, external lighting further improves the shape and detail perception of features, and it also determines the effectiveness of the communication of feature information. The human visual system is highly effective in extracting structural information from images, and to assist it further, this paper presents an approach to structure-aware automatic lighting design by measuring the structural changes between the images with and without external lighting. Given a transfer function and a viewpoint, the optimal lighting parameters are those that provide the greatest enhancement to structural information - the shape and detail information of features are conveyed most clearly by the optimal lighting parameters. Besides lighting goodness, the proposed metric can also be used to evaluate lighting similarity and stability between two sets of lighting parameters. Lighting similarity can be used to optimize the selection of multiple light sources so that different light sources can reveal distinct structural information. Our experiments with several volume data sets demonstrate the effectiveness of the structure-aware lighting design approach. It is well suited to use by novices as it requires little technical understanding of the rendering parameters associated with direct volume rendering. | false | false | [
"Yubo Tao",
"Hai Lin 0003",
"Feng Dong 0005",
"Chao Wang 0063",
"Gordon Clapworthy",
"Hujun Bao"
] | [] | [] | [] |
SciVis | 2,012 | Surface-Based Structure Analysis and Visualization for Multifield Time-Varying Datasets | 10.1109/TVCG.2012.269 | This paper introduces a new feature analysis and visualization method for multifield datasets. Our approach applies a surface-centric model to characterize salient features and form an effective, schematic representation of the data. We propose a simple, geometrically motivated, multifield feature definition. This definition relies on an iterative algorithm that applies existing theory of skeleton derivation to fuse the structures from the constitutive fields into a coherent data description, while addressing noise and spurious details. This paper also presents a new method for non-rigid surface registration between the surfaces of consecutive time steps. This matching is used in conjunction with clustering to discover the interaction patterns between the different fields and their evolution over time. We document the unified visual analysis achieved by our method in the context of several multifield problems from large-scale time-varying simulations. | false | false | [
"Samer S. Barakat",
"Markus Rütten",
"Xavier Tricoche"
] | [] | [] | [] |
SciVis | 2,012 | Turbulence Visualization at the Terascale on Desktop PCs | 10.1109/TVCG.2012.274 | Despite the ongoing efforts in turbulence research, the universal properties of the turbulence small-scale structure and the relationships between small- and large-scale turbulent motions are not yet fully understood. The visually guided exploration of turbulence features, including the interactive selection and simultaneous visualization of multiple features, can further progress our understanding of turbulence. Accomplishing this task for flow fields in which the full turbulence spectrum is well resolved is challenging on desktop computers. This is due to the extreme resolution of such fields, requiring memory and bandwidth capacities going beyond what is currently available. To overcome these limitations, we present a GPU system for feature-based turbulence visualization that works on a compressed flow field representation. We use a wavelet-based compression scheme including run-length and entropy encoding, which can be decoded on the GPU and embedded into brick-based volume ray-casting. This enables a drastic reduction of the data to be streamed from disk to GPU memory. Our system derives turbulence properties directly from the velocity gradient tensor, and it either renders these properties in turn or generates and renders scalar feature volumes. The quality and efficiency of the system is demonstrated in the visualization of two unsteady turbulence simulations, each comprising a spatio-temporal resolution of 10244. On a desktop computer, the system can visualize each time step in 5 seconds, and it achieves about three times this rate for the visualization of a scalar feature volume. | false | false | [
"Marc Treib",
"Kai Bürger",
"Florian Reichl",
"Charles Meneveau",
"Alex Szalay",
"Rüdiger Westermann"
] | [] | [] | [] |
SciVis | 2,012 | Visual Data Analysis as an Integral Part of Environmental Management | 10.1109/TVCG.2012.278 | The U.S. Department of Energy's (DOE) Office of Environmental Management (DOE/EM) currently supports an effort to understand and predict the fate of nuclear contaminants and their transport in natural and engineered systems. Geologists, hydrologists, physicists and computer scientists are working together to create models of existing nuclear waste sites, to simulate their behavior and to extrapolate it into the future. We use visualization as an integral part in each step of this process. In the first step, visualization is used to verify model setup and to estimate critical parameters. High-performance computing simulations of contaminant transport produces massive amounts of data, which is then analyzed using visualization software specifically designed for parallel processing of large amounts of structured and unstructured data. Finally, simulation results are validated by comparing simulation results to measured current and historical field data. We describe in this article how visual analysis is used as an integral part of the decision-making process in the planning of ongoing and future treatment options for the contaminated nuclear waste sites. Lessons learned from visually analyzing our large-scale simulation runs will also have an impact on deciding on treatment measures for other contaminated sites. | false | false | [
"Jörg Meyer",
"E. Wes Bethel",
"Jennifer L. Horsman",
"Susan S. Hubbard",
"Harinarayan Krishnan",
"Alexandru Romosan",
"Elizabeth H. Keating",
"Laura Monroe",
"Richard Strelitz",
"Phil Moore",
"Glenn Taylor",
"Ben Torkian",
"Timothy C. Johnson",
"Ian Gorton"
] | [] | [] | [] |
SciVis | 2,012 | Visual Steering and Verification of Mass Spectrometry Data Factorization in Air Quality Research | 10.1109/TVCG.2012.280 | The study of aerosol composition for air quality research involves the analysis of high-dimensional single particle mass spectrometry data. We describe, apply, and evaluate a novel interactive visual framework for dimensionality reduction of such data. Our framework is based on non-negative matrix factorization with specifically defined regularization terms that aid in resolving mass spectrum ambiguity. Thereby, visualization assumes a key role in providing insight into and allowing to actively control a heretofore elusive data processing step, and thus enabling rapid analysis meaningful to domain scientists. In extending existing black box schemes, we explore design choices for visualizing, interacting with, and steering the factorization process to produce physically meaningful results. A domain-expert evaluation of our system performed by the air quality research experts involved in this effort has shown that our method and prototype admits the finding of unambiguous and physically correct lower-dimensional basis transformations of mass spectrometry data at significantly increased speed and a higher degree of ease. | false | false | [
"Daniel Engel",
"Klaus Greff",
"Christoph Garth",
"Keith Bein",
"Anthony S. Wexler",
"Bernd Hamann",
"Hans Hagen"
] | [] | [] | [] |
SciVis | 2,012 | Visualization of Astronomical Nebulae via Distributed Multi-GPU Compressed Sensing Tomography | 10.1109/TVCG.2012.281 | The 3D visualization of astronomical nebulae is a challenging problem since only a single 2D projection is observable from our fixed vantage point on Earth. We attempt to generate plausible and realistic looking volumetric visualizations via a tomographic approach that exploits the spherical or axial symmetry prevalent in some relevant types of nebulae. Different types of symmetry can be implemented by using different randomized distributions of virtual cameras. Our approach is based on an iterative compressed sensing reconstruction algorithm that we extend with support for position-dependent volumetric regularization and linear equality constraints. We present a distributed multi-GPU implementation that is capable of reconstructing high-resolution datasets from arbitrary projections. Its robustness and scalability are demonstrated for astronomical imagery from the Hubble Space Telescope. The resulting volumetric data is visualized using direct volume rendering. Compared to previous approaches, our method preserves a much higher amount of detail and visual variety in the 3D visualization, especially for objects with only approximate symmetry. | false | false | [
"Stephan Wenger",
"Marco Ament",
"Stefan Guthe",
"Dirk A. Lorenz",
"Andreas M. Tillmann",
"Daniel Weiskopf",
"Marcus A. Magnor"
] | [] | [] | [] |
SciVis | 2,012 | Visualization of Electrostatic Dipoles in Molecular Dynamics of Metal Oxides | 10.1109/TVCG.2012.282 | Metal oxides are important for many technical applications. For example alumina (aluminum oxide) is the most commonly-used ceramic in microelectronic devices thanks to its excellent properties. Experimental studies of these materials are increasingly supplemented with computer simulations. Molecular dynamics (MD) simulations can reproduce the material behavior very well and are now reaching time scales relevant for interesting processes like crack propagation. In this work we focus on the visualization of induced electric dipole moments on oxygen atoms in crack propagation simulations. The straightforward visualization using glyphs for the individual atoms, simple shapes like spheres or arrows, is insufficient for providing information about the data set as a whole. As our contribution we show for the first time that fractional anisotropy values computed from the local neighborhood of individual atoms of MD simulation data depict important information about relevant properties of the field of induced electric dipole moments. Iso surfaces in the field of fractional anisotropy as well as adjustments of the glyph representation allow the user to identify regions of correlated orientation. We present novel and relevant findings for the application domain resulting from these visualizations, like the influence of mechanical forces on the electrostatic properties. | false | false | [
"Sebastian Grottel",
"Philipp Beck",
"Christoph Müller 0001",
"Guido Reina",
"Johannes Roth",
"Hans-Rainer Trebin",
"Thomas Ertl"
] | [] | [] | [] |
SciVis | 2,012 | Visualization of Flow Behavior in Earth Mantle Convection | 10.1109/TVCG.2012.283 | A fundamental characteristic of fluid flow is that it causes mixing: introduce a dye into a flow, and it will disperse. Mixing can be used as a method to visualize and characterize flow. Because mixing is a process that occurs over time, it is a 4D problem that presents a challenge for computation, visualization, and analysis. Motivated by a mixing problem in geophysics, we introduce a combination of methods to analyze, transform, and finally visualize mixing in simulations of convection in a self-gravitating 3D spherical shell representing convection in the Earth's mantle. Geophysicists use tools such as the finite element model CitcomS to simulate convection, and introduce massless, passive tracers to model mixing. The output of geophysical flow simulation is hard to analyze for domain experts because of overall data size and complexity. In addition, information overload and occlusion are problems when visualizing a whole-earth model. To address the large size of the data, we rearrange the simulation data using intelligent indexing for fast file access and efficient caching. To address information overload and interpret mixing, we compute tracer concentration statistics, which are used to characterize mixing in mantle convection models. Our visualization uses a specially tailored version of Direct Volume Rendering. The most important adjustment is the use of constant opacity. Because of this special area of application, i. e. the rendering of a spherical shell, many computations for volume rendering can be optimized. These optimizations are essential to a smooth animation of the time-dependent simulation data. Our results show how our system can be used to quickly assess the simulation output and test hypotheses regarding Earth's mantle convection. The integrated processing pipeline helps geoscientists to focus on their main task of analyzing mantle homogenization. | false | false | [
"Simon Schröder",
"John A. Peterson",
"Harald Obermaier",
"Louise H. Kellogg",
"Kenneth I. Joy",
"Hans Hagen"
] | [] | [] | [] |
SciVis | 2,012 | Visualization of Temporal Similarity in field Data | 10.1109/TVCG.2012.284 | This paper presents a visualization approach for detecting and exploring similarity in the temporal variation of field data. We provide an interactive technique for extracting correlations from similarity matrices which capture temporal similarity of univariate functions. We make use of the concept to extract periodic and quasiperiodic behavior at single (spatial) points as well as similarity between different locations within a field and also between different data sets. The obtained correlations are utilized for visual exploration of both temporal and spatial relationships in terms of temporal similarity. Our entire pipeline offers visual interaction and inspection, allowing for the flexibility that in particular time-dependent data analysis techniques require. We demonstrate the utility and versatility of our approach by applying our implementation to data from both simulation and measurement. | false | false | [
"Steffen Frey",
"Filip Sadlo",
"Thomas Ertl"
] | [] | [] | [] |
SciVis | 2,012 | Visualizing Nuclear Scission through a Multifield Extension of Topological Analysis | 10.1109/TVCG.2012.287 | In nuclear science, density functional theory (DFT) is a powerful tool to model the complex interactions within the atomic nucleus, and is the primary theoretical approach used by physicists seeking a better understanding of fission. However DFT simulations result in complex multivariate datasets in which it is difficult to locate the crucial `scission' point at which one nucleus fragments into two, and to identify the precursors to scission. The Joint Contour Net (JCN) has recently been proposed as a new data structure for the topological analysis of multivariate scalar fields, analogous to the contour tree for univariate fields. This paper reports the analysis of DFT simulations using the JCN, the first application of the JCN technique to real data. It makes three contributions to visualization: (i) a set of practical methods for visualizing the JCN, (ii) new insight into the detection of nuclear scission, and (iii) an analysis of aesthetic criteria to drive further work on representing the JCN. | false | false | [
"David J. Duke",
"Hamish A. Carr",
"Aaron Knoll",
"Nicolas Schunck",
"Hai Ah Nam",
"Andrzej Staszczak"
] | [] | [] | [] |
SciVis | 2,012 | WYSIWYP: What You See Is What You Pick | 10.1109/TVCG.2012.292 | Scientists, engineers and physicians are used to analyze 3D data with slice-based visualizations. Radiologists for example are trained to read slices of medical imaging data. Despite the numerous examples of sophisticated 3D rendering techniques, domain experts, who still prefer slice-based visualization do not consider these to be very useful. Since 3D renderings have the advantage of providing an overview at a glance, while 2D depictions better serve detailed analyses, it is of general interest to better combine these methods. Recently there have been attempts to bridge this gap between 2D and 3D renderings. These attempts include specialized techniques for volume picking in medical imaging data that result in repositioning slices. In this paper, we present a new volume picking technique called WYSIWYP (“what you see is what you pick”) that, in contrast to previous work, does not require pre-segmented data or metadata and thus is more generally applicable. The positions picked by our method are solely based on the data itself, the transfer function, and the way the volumetric rendering is perceived by the user. To demonstrate the utility of the proposed method, we apply it to automated positioning of slices in volumetric scalar fields from various application areas. Finally, we present results of a user study in which 3D locations selected by users are compared to those resulting from WYSIWYP. The user study confirms our claim that the resulting positions correlate well with those perceived by the user. | false | false | [
"Alexander Wiebel",
"Frans Vos",
"David Foerster",
"Hans-Christian Hege"
] | [] | [] | [] |
InfoVis | 2,012 | A User Study on Curved Edges in Graph Visualization | 10.1109/TVCG.2012.189 | Recently there has been increasing research interest in displaying graphs with curved edges to produce more readable visualizations. While there are several automatic techniques, little has been done to evaluate their effectiveness empirically. In this paper we present two experiments studying the impact of edge curvature on graph readability. The goal is to understand the advantages and disadvantages of using curved edges for common graph tasks compared to straight line segments, which are the conventional choice for showing edges in node-link diagrams. We included several edge variations: straight edges, edges with different curvature levels, and mixed straight and curved edges. During the experiments, participants were asked to complete network tasks including determination of connectivity, shortest path, node degree, and common neighbors. We also asked the participants to provide subjective ratings of the aesthetics of different edge types. The results show significant performance differences between the straight and curved edges and clear distinctions between variations of curved edges. | false | false | [
"Kai Xu 0003",
"Chris Rooney",
"Peter J. Passmore",
"Dong-Han Ham",
"Phong Hai Nguyen"
] | [] | [] | [] |
InfoVis | 2,012 | Adaptive Composite Map Projections | 10.1109/TVCG.2012.192 | All major web mapping services use the web Mercator projection. This is a poor choice for maps of the entire globe or areas of the size of continents or larger countries because the Mercator projection shows medium and higher latitudes with extreme areal distortion and provides an erroneous impression of distances and relative areas. The web Mercator projection is also not able to show the entire globe, as polar latitudes cannot be mapped. When selecting an alternative projection for information visualization, rivaling factors have to be taken into account, such as map scale, the geographic area shown, the map's height-to-width ratio, and the type of cartographic visualization. It is impossible for a single map projection to meet the requirements for all these factors. The proposed composite map projection combines several projections that are recommended in cartographic literature and seamlessly morphs map space as the user changes map scale or the geographic region displayed. The composite projection adapts the map's geometry to scale, to the map's height-to-width ratio, and to the central latitude of the displayed area by replacing projections and adjusting their parameters. The composite projection shows the entire globe including poles; it portrays continents or larger countries with less distortion (optionally without areal distortion); and it can morph to the web Mercator projection for maps showing small regions. | false | false | [
"Bernhard Jenny"
] | [] | [] | [] |
InfoVis | 2,012 | Algorithms for Labeling Focus Regions | 10.1109/TVCG.2012.193 | In this paper, we investigate the problem of labeling point sites in focus regions of maps or diagrams. This problem occurs, for example, when the user of a mapping service wants to see the names of restaurants or other POIs in a crowded downtown area but keep the overview over a larger area. Our approach is to place the labels at the boundary of the focus region and connect each site with its label by a linear connection, which is called a leader. In this way, we move labels from the focus region to the less valuable context region surrounding it. In order to make the leader layout well readable, we present algorithms that rule out crossings between leaders and optimize other characteristics such as total leader length and distance between labels. This yields a new variant of the boundary labeling problem, which has been studied in the literature. Other than in traditional boundary labeling, where leaders are usually schematized polylines, we focus on leaders that are either straight-line segments or Bezier curves. Further, we present algorithms that, given the sites, find a position of the focus region that optimizes the above characteristics. We also consider a variant of the problem where we have more sites than space for labels. In this situation, we assume that the sites are prioritized by the user. Alternatively, we take a new facility-location perspective which yields a clustering of the sites. We label one representative of each cluster. If the user wishes, we apply our approach to the sites within a cluster, giving details on demand. | false | false | [
"Martin Fink 0001",
"Jan-Henrik Haunert",
"André Schulz 0001",
"Joachim Spoerhase",
"Alexander Wolff 0001"
] | [] | [] | [] |
InfoVis | 2,012 | An Empirical Model of Slope Ratio Comparisons | 10.1109/TVCG.2012.196 | Comparing slopes is a fundamental graph reading task and the aspect ratio chosen for a plot influences how easy these comparisons are to make. According to Banking to 45°, a classic design guideline first proposed and studied by Cleveland et al., aspect ratios that center slopes around 45° minimize errors in visual judgments of slope ratios. This paper revisits this earlier work. Through exploratory pilot studies that expand Cleveland et al.'s experimental design, we develop an empirical model of slope ratio estimation that fits more extreme slope ratio judgments and two common slope ratio estimation strategies. We then run two experiments to validate our model. In the first, we show that our model fits more generally than the one proposed by Cleveland et al. and we find that, in general, slope ratio errors are not minimized around 45°. In the second experiment, we explore a novel hypothesis raised by our model: that visible baselines can substantially mitigate errors made in slope judgments. We conclude with an application of our model to aspect ratio selection. | false | false | [
"Justin Talbot",
"John Gerth",
"Pat Hanrahan"
] | [] | [] | [] |
InfoVis | 2,012 | An Empirical Study on Using Visual Embellishments in Visualization | 10.1109/TVCG.2012.197 | In written and spoken communications, figures of speech (e.g., metaphors and synecdoche) are often used as an aid to help convey abstract or less tangible concepts. However, the benefits of using rhetorical illustrations or embellishments in visualization have so far been inconclusive. In this work, we report an empirical study to evaluate hypotheses that visual embellishments may aid memorization, visual search and concept comprehension. One major departure from related experiments in the literature is that we make use of a dual-task methodology in our experiment. This design offers an abstraction of typical situations where viewers do not have their full attention focused on visualization (e.g., in meetings and lectures). The secondary task introduces “divided attention”, and makes the effects of visual embellishments more observable. In addition, it also serves as additional masking in memory-based trials. The results of this study show that visual embellishments can help participants better remember the information depicted in visualization. On the other hand, visual embellishments can have a negative impact on the speed of visual search. The results show a complex pattern as to the benefits of visual embellishments in helping participants grasp key concepts from visualization. | false | false | [
"Rita Borgo",
"Alfie Abdul-Rahman",
"Farhan Mohamed",
"Phil W. Grant",
"Irene Reppa",
"Luciano Floridi",
"Min Chen 0001"
] | [] | [] | [] |
InfoVis | 2,012 | Assessing the Effect of Visualizations on Bayesian Reasoning through Crowdsourcing | 10.1109/TVCG.2012.199 | People have difficulty understanding statistical information and are unaware of their wrong judgments, particularly in Bayesian reasoning. Psychology studies suggest that the way Bayesian problems are represented can impact comprehension, but few visual designs have been evaluated and only populations with a specific background have been involved. In this study, a textual and six visual representations for three classic problems were compared using a diverse subject pool through crowdsourcing. Visualizations included area-proportional Euler diagrams, glyph representations, and hybrid diagrams combining both. Our study failed to replicate previous findings in that subjects' accuracy was remarkably lower and visualizations exhibited no measurable benefit. A second experiment confirmed that simply adding a visualization to a textual Bayesian problem is of little help, even when the text refers to the visualization, but suggests that visualizations are more effective when the text is given without numerical values. We discuss our findings and the need for more such experiments to be carried out on heterogeneous populations of non-experts. | false | false | [
"Luana Micallef",
"Pierre Dragicevic",
"Jean-Daniel Fekete"
] | [
"HM"
] | [] | [] |
InfoVis | 2,012 | Beyond Mouse and Keyboard: Expanding Design Considerations for Information Visualization Interactions | 10.1109/TVCG.2012.204 | The importance of interaction to Information Visualization (InfoVis) and, in particular, of the interplay between interactivity and cognition is widely recognized [12, 15, 32, 55, 70]. This interplay, combined with the demands from increasingly large and complex datasets, is driving the increased significance of interaction in InfoVis. In parallel, there have been rapid advances in many facets of interaction technologies. However, InfoVis interactions have yet to take full advantage of these new possibilities in interaction technologies, as they largely still employ the traditional desktop, mouse, and keyboard setup of WIMP (Windows, Icons, Menus, and a Pointer) interfaces. In this paper, we reflect more broadly about the role of more “natural” interactions for InfoVis and provide opportunities for future research. We discuss and relate general HCI interaction models to existing InfoVis interaction classifications by looking at interactions from a novel angle, taking into account the entire spectrum of interactions. Our discussion of InfoVis-specific interaction design considerations helps us identify a series of underexplored attributes of interaction that can lead to new, more “natural,” interaction techniques for InfoVis. | false | false | [
"Bongshin Lee",
"Petra Isenberg",
"Nathalie Henry Riche",
"Sheelagh Carpendale"
] | [] | [] | [] |
InfoVis | 2,012 | Capturing the Design Space of Sequential Space-filling Layouts | 10.1109/TVCG.2012.205 | We characterize the design space of the algorithms that sequentially tile a rectangular area with smaller, fixed-surface, rectangles. This space consist of five independent dimensions: Order, Size, Score, Recurse and Phrase. Each of these dimensions describe a particular aspect of such layout tasks. This class of layouts is interesting, because, beyond encompassing simple grids, tables and trees, it also includes all kinds of treemaps involving the placement of rectangles. For instance, Slice and dice, Squarified, Strip and Pivot layouts are various points in this five dimensional space. Many classic statistics visualizations, such as 100% stacked bar charts, mosaic plots and dimensional stacking, are also instances of this class. A few new and potentially interesting points in this space are introduced, such as spiral treemaps and variations on the strip layout. The core algorithm is implemented as a JavaScript prototype that can be used as a layout component in a variety of InfoViz toolkits. | false | false | [
"Thomas Baudel",
"Bertjan Broeksema"
] | [] | [] | [] |
InfoVis | 2,012 | Comparing Clusterings Using Bertin's Idea | 10.1109/TVCG.2012.207 | Classifying a set of objects into clusters can be done in numerous ways, producing different results. They can be visually compared using contingency tables [27], mosaicplots [13], fluctuation diagrams [15], tableplots [20] , (modified) parallel coordinates plots [28], Parallel Sets plots [18] or circos diagrams [19]. Unfortunately the interpretability of all these graphical displays decreases rapidly with the numbers of categories and clusterings. In his famous book A Semiology of Graphics [5] Bertin writes “the discovery of an ordered concept appears as the ultimate point in logical simplification since it permits reducing to a single instant the assimilation of series which previously required many instants of study”. Or in more everyday language, if you use good orderings you can see results immediately that with other orderings might take a lot of effort. This is also related to the idea of effect ordering [12], that data should be organised to reflect the effect you want to observe. This paper presents an efficient algorithm based on Bertin's idea and concepts related to Kendall's t [17], which finds informative joint orders for two or more nominal classification variables. We also show how these orderings improve the various displays and how groups of corresponding categories can be detected using a top-down partitioning algorithm. Different clusterings based on data on the environmental performance of cars sold in Germany are used for illustration. All presented methods are available in the R package extracat which is used to compute the optimized orderings for the example dataset. | false | false | [
"Alexander Pilhofer",
"Alexander Gribov",
"Antony Unwin"
] | [] | [] | [] |
InfoVis | 2,012 | Compressed Adjacency Matrices: Untangling Gene Regulatory Networks | 10.1109/TVCG.2012.208 | We present a novel technique-Compressed Adjacency Matrices-for visualizing gene regulatory networks. These directed networks have strong structural characteristics: out-degrees with a scale-free distribution, in-degrees bound by a low maximum, and few and small cycles. Standard visualization techniques, such as node-link diagrams and adjacency matrices, are impeded by these network characteristics. The scale-free distribution of out-degrees causes a high number of intersecting edges in node-link diagrams. Adjacency matrices become space-inefficient due to the low in-degrees and the resulting sparse network. Compressed adjacency matrices, however, exploit these structural characteristics. By cutting open and rearranging an adjacency matrix, we achieve a compact and neatly-arranged visualization. Compressed adjacency matrices allow for easy detection of subnetworks with a specific structure, so-called motifs, which provide important knowledge about gene regulatory networks to domain experts. We summarize motifs commonly referred to in the literature, and relate them to network analysis tasks common to the visualization domain. We show that a user can easily find the important motifs in compressed adjacency matrices, and that this is hard in standard adjacency matrix and node-link diagrams. We also demonstrate that interaction techniques for standard adjacency matrices can be used for our compressed variant. These techniques include rearrangement clustering, highlighting, and filtering. | false | false | [
"Kasper Dinkla",
"Michel A. Westenberg",
"Jarke J. van Wijk"
] | [] | [] | [] |
InfoVis | 2,012 | Design Considerations for Optimizing Storyline Visualizations | 10.1109/TVCG.2012.212 | Storyline visualization is a technique used to depict the temporal dynamics of social interactions. This visualization technique was first introduced as a hand-drawn illustration in XKCD's “Movie Narrative Charts” [21]. If properly constructed, the visualization can convey both global trends and local interactions in the data. However, previous methods for automating storyline visualizations are overly simple, failing to achieve some of the essential principles practiced by professional illustrators. This paper presents a set of design considerations for generating aesthetically pleasing and legible storyline visualizations. Our layout algorithm is based on evolutionary computation, allowing us to effectively incorporate multiple objective functions. We show that the resulting visualizations have significantly improved aesthetics and legibility compared to existing techniques. | false | false | [
"Yuzuru Tanahashi",
"Kwan-Liu Ma"
] | [] | [] | [] |
InfoVis | 2,012 | Design Study Methodology: Reflections from the Trenches and the Stacks | 10.1109/TVCG.2012.213 | Design studies are an increasingly popular form of problem-driven visualization research, yet there is little guidance available about how to do them effectively. In this paper we reflect on our combined experience of conducting twenty-one design studies, as well as reading and reviewing many more, and on an extensive literature review of other field work methods and methodologies. Based on this foundation we provide definitions, propose a methodological framework, and provide practical guidance for conducting design studies. We define a design study as a project in which visualization researchers analyze a specific real-world problem faced by domain experts, design a visualization system that supports solving this problem, validate the design, and reflect about lessons learned in order to refine visualization design guidelines. We characterize two axes - a task clarity axis from fuzzy to crisp and an information location axis from the domain expert's head to the computer - and use these axes to reason about design study contributions, their suitability, and uniqueness from other approaches. The proposed methodological framework consists of 9 stages: learn, winnow, cast, discover, design, implement, deploy, reflect, and write. For each stage we provide practical guidance and outline potential pitfalls. We also conducted an extensive literature survey of related methodological approaches that involve a significant amount of qualitative field work, and compare design study methodology to that of ethnography, grounded theory, and action research. | false | false | [
"Michael Sedlmair",
"Miriah D. Meyer",
"Tamara Munzner"
] | [
"HM"
] | [] | [] |
InfoVis | 2,012 | Different Strokes for Different Folks: Visual Presentation Design between Disciplines | 10.1109/TVCG.2012.214 | We present an ethnographic study of design differences in visual presentations between academic disciplines. Characterizing design conventions between users and data domains is an important step in developing hypotheses, tools, and design guidelines for information visualization. In this paper, disciplines are compared at a coarse scale between four groups of fields: social, natural, and formal sciences; and the humanities. Two commonplace presentation types were analyzed: electronic slideshows and whiteboard “chalk talks”. We found design differences in slideshows using two methods - coding and comparing manually-selected features, like charts and diagrams, and an image-based analysis using PCA called eigenslides. In whiteboard talks with controlled topics, we observed design behaviors, including using representations and formalisms from a participant's own discipline, that suggest authors might benefit from novel assistive tools for designing presentations. Based on these findings, we discuss opportunities for visualization ethnography and human-centered authoring tools for visual information. | false | false | [
"Steven R. Gomez",
"Radu Jianu",
"Caroline Ziemkiewicz",
"Hua Guo",
"David H. Laidlaw"
] | [] | [] | [] |
InfoVis | 2,012 | Does an Eye Tracker Tell the Truth about Visualizations?: findings while Investigating Visualizations for Decision Making | 10.1109/TVCG.2012.215 | For information visualization researchers, eye tracking has been a useful tool to investigate research participants' underlying cognitive processes by tracking their eye movements while they interact with visual techniques. We used an eye tracker to better understand why participants with a variant of a tabular visualization called `SimulSort' outperformed ones with a conventional table and typical one-column sorting feature (i.e., Typical Sorting). The collected eye-tracking data certainly shed light on the detailed cognitive processes of the participants; SimulSort helped with decision-making tasks by promoting efficient browsing behavior and compensatory decision-making strategies. However, more interestingly, we also found unexpected eye-tracking patterns with Simul- Sort. We investigated the cause of the unexpected patterns through a crowdsourcing-based study (i.e., Experiment 2), which elicited an important limitation of the eye tracking method: incapability of capturing peripheral vision. This particular result would be a caveat for other visualization researchers who plan to use an eye tracker in their studies. In addition, the method to use a testing stimulus (i.e., influential column) in Experiment 2 to verify the existence of such limitations would be useful for researchers who would like to verify their eye tracking results. | false | false | [
"Sung-Hee Kim",
"Zhihua Dong",
"Hanjun Xian",
"Benjavan Upatising",
"Ji Soo Yi"
] | [] | [] | [] |
InfoVis | 2,012 | Evaluating Sketchiness as a Visual Variable for the Depiction of Qualitative Uncertainty | 10.1109/TVCG.2012.220 | We report on results of a series of user studies on the perception of four visual variables that are commonly used in the literature to depict uncertainty. To the best of our knowledge, we provide the first formal evaluation of the use of these variables to facilitate an easier reading of uncertainty in visualizations that rely on line graphical primitives. In addition to blur, dashing and grayscale, we investigate the use of `sketchiness' as a visual variable because it conveys visual impreciseness that may be associated with data quality. Inspired by work in non-photorealistic rendering and by the features of hand-drawn lines, we generate line trajectories that resemble hand-drawn strokes of various levels of proficiency-ranging from child to adult strokes-where the amount of perturbations in the line corresponds to the level of uncertainty in the data. Our results show that sketchiness is a viable alternative for the visualization of uncertainty in lines and is as intuitive as blur; although people subjectively prefer dashing style over blur, grayscale and sketchiness. We discuss advantages and limitations of each technique and conclude with design considerations on how to deploy these visual variables to effectively depict various levels of uncertainty for line marks. | false | false | [
"Nadia Boukhelifa",
"Anastasia Bezerianos",
"Tobias Isenberg 0001",
"Jean-Daniel Fekete"
] | [] | [] | [] |
InfoVis | 2,012 | Evaluating the Effect of Style in Information Visualization | 10.1109/TVCG.2012.221 | This paper reports on a between-subject, comparative online study of three information visualization demonstrators that each displayed the same dataset by way of an identical scatterplot technique, yet were different in style in terms of visual and interactive embellishment. We validated stylistic adherence and integrity through a separate experiment in which a small cohort of participants assigned our three demonstrators to predefined groups of stylistic examples, after which they described the styles with their own words. From the online study, we discovered significant differences in how participants execute specific interaction operations, and the types of insights that followed from them. However, in spite of significant differences in apparent usability, enjoyability and usefulness between the style demonstrators, no variation was found on the self-reported depth, expert-rated depth, confidence or difficulty of the resulting insights. Three different methods of insight analysis have been applied, revealing how style impacts the creation of insights, ranging from higher-level pattern seeking to a more reflective and interpretative engagement with content, which is what underlies the patterns. As this study only forms the first step in determining how the impact of style in information visualization could be best evaluated, we propose several guidelines and tips on how to gather, compare and categorize insights through an online evaluation study, particularly in terms of analyzing the concise, yet wide variety of insights and observations in a trustworthy and reproducable manner. | false | false | [
"Andrew Vande Moere",
"Martin Tomitsch",
"Christoph Wimmer",
"Christoph M. Bösch",
"Thomas Grechenig"
] | [] | [] | [] |
InfoVis | 2,012 | Exploring Flow, Factors, and Outcomes of Temporal Event Sequences with the Outflow Visualization | 10.1109/TVCG.2012.225 | Event sequence data is common in many domains, ranging from electronic medical records (EMRs) to sports events. Moreover, such sequences often result in measurable outcomes (e.g., life or death, win or loss). Collections of event sequences can be aggregated together to form event progression pathways. These pathways can then be connected with outcomes to model how alternative chains of events may lead to different results. This paper describes the Outflow visualization technique, designed to (1) aggregate multiple event sequences, (2) display the aggregate pathways through different event states with timing and cardinality, (3) summarize the pathways' corresponding outcomes, and (4) allow users to explore external factors that correlate with specific pathway state transitions. Results from a user study with twelve participants show that users were able to learn how to use Outflow easily with limited training and perform a range of tasks both accurately and rapidly. | false | false | [
"Krist Wongsuphasawat",
"David Gotz"
] | [] | [] | [] |
InfoVis | 2,012 | Facilitating Discourse Analysis with Interactive Visualization | 10.1109/TVCG.2012.226 | A discourse parser is a natural language processing system which can represent the organization of a document based on a rhetorical structure tree-one of the key data structures enabling applications such as text summarization, question answering and dialogue generation. Computational linguistics researchers currently rely on manually exploring and comparing the discourse structures to get intuitions for improving parsing algorithms. In this paper, we present DAViewer, an interactive visualization system for assisting computational linguistics researchers to explore, compare, evaluate and annotate the results of discourse parsers. An iterative user-centered design process with domain experts was conducted in the development of DAViewer. We report the results of an informal formative study of the system to better understand how the proposed visualization and interaction techniques are used in the real research environment. | false | false | [
"Jian Zhao 0010",
"Fanny Chevalier",
"Christopher Collins 0001",
"Ravin Balakrishnan"
] | [] | [] | [] |
InfoVis | 2,012 | Graphical Overlays: Using Layered Elements to Aid Chart Reading | 10.1109/TVCG.2012.229 | Reading a visualization can involve a number of tasks such as extracting, comparing or aggregating numerical values. Yet, most of the charts that are published in newspapers, reports, books, and on the Web only support a subset of these tasks. In this paper we introduce graphical overlays-visual elements that are layered onto charts to facilitate a larger set of chart reading tasks. These overlays directly support the lower-level perceptual and cognitive processes that viewers must perform to read a chart. We identify five main types of overlays that support these processes; the overlays can provide (1) reference structures such as gridlines, (2) highlights such as outlines around important marks, (3) redundant encodings such as numerical data labels, (4) summary statistics such as the mean or max and (5) annotations such as descriptive text for context. We then present an automated system that applies user-chosen graphical overlays to existing chart bitmaps. Our approach is based on the insight that generating most of these graphical overlays only requires knowing the properties of the visual marks and axes that encode the data, but does not require access to the underlying data values. Thus, our system analyzes the chart bitmap to extract only the properties necessary to generate the desired overlay. We also discuss techniques for generating interactive overlays that provide additional controls to viewers. We demonstrate several examples of each overlay type for bar, pie and line charts. | false | false | [
"Nicholas Kong",
"Maneesh Agrawala"
] | [] | [] | [] |
InfoVis | 2,012 | Graphical Tests for Power Comparison of Competing Designs | 10.1109/TVCG.2012.230 | Lineups [4, 28] have been established as tools for visual testing similar to standard statistical inference tests, allowing us to evaluate the validity of graphical findings in an objective manner. In simulation studies [12] lineups have been shown as being efficient: the power of visual tests is comparable to classical tests while being much less stringent in terms of distributional assumptions made. This makes lineups versatile, yet powerful, tools in situations where conditions for regular statistical tests are not or cannot be met. In this paper we introduce lineups as a tool for evaluating the power of competing graphical designs. We highlight some of the theoretical properties and then show results from two studies evaluating competing designs: both studies are designed to go to the limits of our perceptual abilities to highlight differences between designs. We use both accuracy and speed of evaluation as measures of a successful design. The first study compares the choice of coordinate system: polar versus cartesian coordinates. The results show strong support in favor of cartesian coordinates in finding fast and accurate answers to spotting patterns. The second study is aimed at finding shift differences between distributions. Both studies are motivated by data problems that we have recently encountered, and explore using simulated data to evaluate the plot designs under controlled conditions. Amazon Mechanical Turk (MTurk) is used to conduct the studies. The lineups provide an effective mechanism for objectively evaluating plot designs. | false | false | [
"Heike Hofmann",
"Lendie Follett",
"Mahbubul Majumder",
"Dianne Cook"
] | [] | [] | [] |
InfoVis | 2,012 | How Capacity Limits of Attention Influence Information Visualization Effectiveness | 10.1109/TVCG.2012.233 | In this paper, we explore how the capacity limits of attention influence the effectiveness of information visualizations. We conducted a series of experiments to test how visual feature type (color vs. motion), layout, and variety of visual elements impacted user performance. The experiments tested users' abilities to (1) determine if a specified target is on the screen, (2) detect an odd-ball, deviant target, different from the other visible objects, and (3) gain a qualitative overview by judging the number of unique categories on the screen. Our results show that the severe capacity limits of attention strongly modulate the effectiveness of information visualizations, particularly the ability to detect unexpected information. Keeping in mind these capacity limits, we conclude with a set of design guidelines which depend on a visualization's intended use. | false | false | [
"Steve Haroz",
"David Whitney"
] | [
"BP"
] | [] | [] |
InfoVis | 2,012 | Intelligent Graph Layout Using Many Users' Input | 10.1109/TVCG.2012.236 | In this paper, we propose a new strategy for graph drawing utilizing layouts of many sub-graphs supplied by a large group of people in a crowd sourcing manner. We developed an algorithm based on Laplacian constrained distance embedding to merge subgraphs submitted by different users, while attempting to maintain the topological information of the individual input layouts. To facilitate collection of layouts from many people, a light-weight interactive system has been designed to enable convenient dynamic viewing, modification and traversing between layouts. Compared with other existing graph layout algorithms, our approach can achieve more aesthetic and meaningful layouts with high user preference. | false | false | [
"Xiaoru Yuan",
"Limei Che",
"Yifan Hu 0001",
"Xin Zhang"
] | [] | [] | [] |
InfoVis | 2,012 | Interaction Support for Visual Comparison Inspired by Natural Behavior | 10.1109/TVCG.2012.237 | Visual comparison is an intrinsic part of interactive data exploration and analysis. The literature provides a large body of existing solutions that help users accomplish comparison tasks. These solutions are mostly of visual nature and custom-made for specific data. We ask the question if a more general support is possible by focusing on the interaction aspect of comparison tasks. As an answer to this question, we propose a novel interaction concept that is inspired by real-world behavior of people comparing information printed on paper. In line with real-world interaction, our approach supports users (1) in interactively specifying pieces of graphical information to be compared, (2) in flexibly arranging these pieces on the screen, and (3) in performing the actual comparison of side-by-side and overlapping arrangements of the graphical information. Complementary visual cues and add-ons further assist users in carrying out comparison tasks. Our concept and the integrated interaction techniques are generally applicable and can be coupled with different visualization techniques. We implemented an interactive prototype and conducted a qualitative user study to assess the concept's usefulness in the context of three different visualization techniques. The obtained feedback indicates that our interaction techniques mimic the natural behavior quite well, can be learned quickly, and are easy to apply to visual comparison tasks. | false | false | [
"Christian Tominski",
"Camilla Forsell",
"Jimmy Johansson 0001"
] | [] | [] | [] |
InfoVis | 2,012 | Interactive Level-of-Detail Rendering of Large Graphs | 10.1109/TVCG.2012.238 | We propose a technique that allows straight-line graph drawings to be rendered interactively with adjustable level of detail. The approach consists of a novel combination of edge cumulation with density-based node aggregation and is designed to exploit common graphics hardware for speed. It operates directly on graph data and does not require precomputed hierarchies or meshes. As proof of concept, we present an implementation that scales to graphs with millions of nodes and edges, and discuss several example applications. | false | false | [
"Michael Zinsmaier",
"Ulrik Brandes",
"Oliver Deussen",
"Hendrik Strobelt"
] | [] | [] | [] |
InfoVis | 2,012 | Living Liquid: Design and Evaluation of an Exploratory Visualization Tool for Museum Visitors | 10.1109/TVCG.2012.244 | Interactive visualizations can allow science museum visitors to explore new worlds by seeing and interacting with scientific data. However, designing interactive visualizations for informal learning environments, such as museums, presents several challenges. First, visualizations must engage visitors on a personal level. Second, visitors often lack the background to interpret visualizations of scientific data. Third, visitors have very limited time at individual exhibits in museums. This paper examines these design considerations through the iterative development and evaluation of an interactive exhibit as a visualization tool that gives museumgoers access to scientific data generated and used by researchers. The exhibit prototype, Living Liquid, encourages visitors to ask and answer their own questions while exploring the time-varying global distribution of simulated marine microbes using a touchscreen interface. Iterative development proceeded through three rounds of formative evaluations using think-aloud protocols and interviews, each round informing a key visualization design decision: (1) what to visualize to initiate inquiry, (2) how to link data at the microscopic scale to global patterns, and (3) how to include additional data that allows visitors to pursue their own questions. Data from visitor evaluations suggests that, when designing visualizations for public audiences, one should (1) avoid distracting visitors from data that they should explore, (2) incorporate background information into the visualization, (3) favor understandability over scientific accuracy, and (4) layer data accessibility to structure inquiry. Lessons learned from this case study add to our growing understanding of how to use visualizations to actively engage learners with scientific data. | false | false | [
"Joyce Ma",
"Isaac Liao",
"Kwan-Liu Ma",
"Jennifer Frazier"
] | [] | [] | [] |
InfoVis | 2,012 | Memorability of Visual Features in Network Diagrams | 10.1109/TVCG.2012.245 | We investigate the cognitive impact of various layout features-symmetry, alignment, collinearity, axis alignment and orthogonality - on the recall of network diagrams (graphs). This provides insight into how people internalize these diagrams and what features should or shouldn't be utilised when designing static and interactive network-based visualisations. Participants were asked to study, remember, and draw a series of small network diagrams, each drawn to emphasise a particular visual feature. The visual features were based on existing theories of perception, and the task enabled visual processing at the visceral level only. Our results strongly support the importance of visual features such as symmetry, collinearity and orthogonality, while not showing any significant impact for node-alignment or parallel edges. | false | false | [
"Kim Marriott",
"Helen C. Purchase",
"Michael Wybrow",
"Cagatay Goncu"
] | [] | [] | [] |
InfoVis | 2,012 | Organizing Search Results with a Reference Map | 10.1109/TVCG.2012.250 | We propose a method to highlight query hits in hierarchically clustered collections of interrelated items such as digital libraries or knowledge bases. The method is based on the idea that organizing search results similarly to their arrangement on a fixed reference map facilitates orientation and assessment by preserving a user's mental map. Here, the reference map is built from an MDS layout of the items in a Voronoi treemap representing their hierarchical clustering, and we use techniques from dynamic graph layout to align query results with the map. The approach is illustrated on an archive of newspaper articles. | false | false | [
"Arlind Nocaj",
"Ulrik Brandes"
] | [] | [] | [] |
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