2011 IEEE Conference on Visual Analytics Science and Technology (VAST)最新文献

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epSpread - Storyboarding for visual analytics epSpread -用于视觉分析的故事板
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102489
L. A. Cenydd, Rick Walker, S. Pop, Helen C. Miles, Chris J. Hughes, W. Teahan, Jonathan C. Roberts
{"title":"epSpread - Storyboarding for visual analytics","authors":"L. A. Cenydd, Rick Walker, S. Pop, Helen C. Miles, Chris J. Hughes, W. Teahan, Jonathan C. Roberts","doi":"10.1109/VAST.2011.6102489","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102489","url":null,"abstract":"We present epSpread, an analysis and storyboarding tool for geolocated microblogging data. Individual time points and ranges are analysed through queries, heatmaps, word clouds and streamgraphs. The underlying narrative is shown on a storyboard-style timeline for discussion, refinement and presentation. The tool was used to analyse data from the VAST Challenge 2011 Mini-Challenge 1, tracking the spread of an epidemic using microblogging data. In this article we describe how the tool was used to identify the origin and track the spread of the epidemic.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133714090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Analysts aren't machines: Inferring frustration through visualization interaction 分析师不是机器:通过可视化交互推断挫败感
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102473
Lane Harrison, Wenwen Dou, Aidong Lu, W. Ribarsky, Xiaoyu Wang
{"title":"Analysts aren't machines: Inferring frustration through visualization interaction","authors":"Lane Harrison, Wenwen Dou, Aidong Lu, W. Ribarsky, Xiaoyu Wang","doi":"10.1109/VAST.2011.6102473","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102473","url":null,"abstract":"Recent work in visual analytics has explored the extent to which information regarding analyst action and reasoning can be inferred from interaction. However, these methods typically rely on humans instead of automatic extraction techniques. Futhermore, there is little discussion regarding the role of user frustration when interacting with a visual interface. We demonstrate that automatic extraction of user frustration is possible given action-level visualization interaction logs. An experiment is described which collects data that accurately reflects user emotion transitions and corresponding interaction sequences. This data is then used in building HiddenMarkov Models (HMMs) which statistically connect interaction events with frustration. The capabilities of HMMs in predicting user frustration are tested using standard machine learning evaluation methods. The resulting classifer serves as a suitable predictor of user frustration that performs similarly across different users and datasets.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121160165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
SAVE: Sensor anomaly visualization engine 保存:传感器异常可视化引擎
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102458
Lei Shi, Qi Liao, Yuan He, Rui Li, A. Striegel, Zhongji Su
{"title":"SAVE: Sensor anomaly visualization engine","authors":"Lei Shi, Qi Liao, Yuan He, Rui Li, A. Striegel, Zhongji Su","doi":"10.1109/VAST.2011.6102458","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102458","url":null,"abstract":"Diagnosing a large-scale sensor network is a crucial but challenging task. Particular challenges include the resource and bandwidth constraints on sensor nodes, the spatiotemporally dynamic network behaviors, and the lack of accurate models to understand such behaviors in a hostile environment. In this paper, we present the Sensor Anomaly Visualization Engine (SAVE), a system that fully leverages the power of both visualization and anomaly detection analytics to guide the user to quickly and accurately diagnose sensor network failures and faults. SAVE combines customized visualizations over separate sensor data facets as multiple coordinated views. Temporal expansion model, correlation graph and dynamic projection views are proposed to effectively interpret the topological, correlational and dimensional sensor data dynamics and their anomalies. Through a case study with real-world sensor network system and administrators, we demonstrate that SAVE is able to help better locate the system problem and further identify the root cause of major sensor network failure scenarios.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124003728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 36
Obvious: A meta-toolkit to encapsulate information visualization toolkits — One toolkit to bind them all 显而易见:一个元工具包来封装信息可视化工具包——一个工具包来绑定它们
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102446
Jean-Daniel Fekete, P. Hemery, Thomas Baudel, J. Wood
{"title":"Obvious: A meta-toolkit to encapsulate information visualization toolkits — One toolkit to bind them all","authors":"Jean-Daniel Fekete, P. Hemery, Thomas Baudel, J. Wood","doi":"10.1109/VAST.2011.6102446","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102446","url":null,"abstract":"This article describes “Obvious”: a meta-toolkit that abstracts and encapsulates information visualization toolkits implemented in the Java language. It intends to unify their use and postpone the choice of which concrete toolkit(s) to use later-on in the development of visual analytics applications. We also report on the lessons we have learned when wrapping popular toolkits with Obvious, namely Prefuse, the InfoVis Toolkit, partly Improvise, JUNG and other data management libraries. We show several examples on the uses of Obvious, how the different toolkits can be combined, for instance sharing their data models. We also show how Weka and Rapid-Miner, two popular machine-learning toolkits, have been wrapped with Obvious and can be used directly with all the other wrapped toolkits. We expect Obvious to start a co-evolution process: Obvious is meant to evolve when more components of Information Visualization systems will become consensual. It is also designed to help information visualization systems adhere to the best practices to provide a higher level of interoperability and leverage the domain of visual analytics.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121866779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 22
Jigsaw to save vastopolis 拼图游戏拯救大都市
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102496
E. Braunstein, C. Görg, Zhicheng Liu, J. Stasko
{"title":"Jigsaw to save vastopolis","authors":"E. Braunstein, C. Görg, Zhicheng Liu, J. Stasko","doi":"10.1109/VAST.2011.6102496","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102496","url":null,"abstract":"This article describes our analytic process and experience of using the Jigsaw system in working on the VAST 2011 Mini Challenge 3. We describe how we extracted and worked with entities from the documents, and how Jigsaw's computational analysis capabilities and visualizations scaffolded the investigation. Based on our experiences, we discuss desirable features that would enhance the analytic power of Jigsaw.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122586436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
How locus of control influences compatibility with visualization style 控制点如何影响视觉风格的兼容性
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102445
Caroline Ziemkiewicz, R. J. Crouser, Ashley Rye Yauilla, S. Su, W. Ribarsky, Remco Chang
{"title":"How locus of control influences compatibility with visualization style","authors":"Caroline Ziemkiewicz, R. J. Crouser, Ashley Rye Yauilla, S. Su, W. Ribarsky, Remco Chang","doi":"10.1109/VAST.2011.6102445","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102445","url":null,"abstract":"Existing research suggests that individual personality differences are correlated with a user's speed and accuracy in solving problems with different types of complex visualization systems. In this paper, we extend this research by isolating factors in personality traits as well as in the visualizations that could have contributed to the observed correlation. We focus on a personality trait known as “locus of control,” which represents a person's tendency to see themselves as controlled by or in control of external events. To isolate variables of the visualization design, we control extraneous factors such as color, interaction, and labeling, and specifically focus on the overall layout style of the visualizations. We conduct a user study with four visualizations that gradually shift from an indentation metaphor to a containment metaphor and compare the participants' speed, accuracy, and preference with their locus of control. Our findings demonstrate that there is indeed a correlation between the two: participants with an internal locus of control perform more poorly with visualizations that employ a containment metaphor, while those with an external locus of control perform well with such visualizations. We discuss a possible explanation for this relationship based in cognitive psychology and propose that these results can be used to better understand how people use visualizations and how to adapt visual analytics design to an individual user's needs.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116871600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 76
Pexel and heatmap visual analysis of multidimensional gun/homicide data 多维枪支/凶杀数据的像素和热图可视化分析
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102482
S. Rothenberger, John E. Wenskovitch, G. Marai
{"title":"Pexel and heatmap visual analysis of multidimensional gun/homicide data","authors":"S. Rothenberger, John E. Wenskovitch, G. Marai","doi":"10.1109/VAST.2011.6102482","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102482","url":null,"abstract":"We present a visual analysis tool for mining correlations in county-level, multidimensional gun/homicide data. The tool uses 2D pexels, heatmaps, linked-views, dynamic queries and details-on-demand to analyze annual county-level data on firearm homicide rates and gun availability, as well as various socio-demographic measures. A statistical significance filter was implemented as a visual means to validate exploratory hypotheses. Results from expert evaluations indicate that our methods outperform typical graphical techniques used by statisticians, such as bar graphs, scatterplots and residual plots, to show spatial and temporal relationships. Our visualization has the potential to convey the impact of gun availability on firearm homicides to the public health arena and the general public.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121827918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Interactive visual comparison of multiple trees 多棵树的交互式视觉比较
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102439
S. Bremm, T. V. Landesberger, Martin Hess, T. Schreck, P. Weil, K. Hamacher
{"title":"Interactive visual comparison of multiple trees","authors":"S. Bremm, T. V. Landesberger, Martin Hess, T. Schreck, P. Weil, K. Hamacher","doi":"10.1109/VAST.2011.6102439","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102439","url":null,"abstract":"Traditionally, the visual analysis of hierarchies, respectively, trees, is conducted by focusing on one given hierarchy. However, in many research areas multiple, differing hierarchies need to be analyzed simultaneously in a comparative way - in particular to highlight differences between them, which sometimes can be subtle. A prominent example is the analysis of so-called phylogenetic trees in biology, reflecting hierarchical evolutionary relationships among a set of organisms. Typically, the analysis considers multiple phylogenetic trees, either to account for statistical significance or for differences in derivation of such evolutionary hierarchies; for example, based on different input data, such as the 16S ribosomal RNA and protein sequences of highly conserved enzymes. The simultaneous analysis of a collection of such trees leads to more insight into the evolutionary process. We introduce a novel visual analytics approach for the comparison of multiple hierarchies focusing on both global and local structures. A new tree comparison score has been elaborated for the identification of interesting patterns. We developed a set of linked hierarchy views showing the results of automatic tree comparison on various levels of details. This combined approach offers detailed assessment of local and global tree similarities. The approach was developed in close cooperation with experts from the evolutionary biology domain. We apply it to a phylogenetic data set on bacterial ancestry, demonstrating its application benefit.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"16 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120922793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 87
MobileAnalymator: Animating data changes on mobile devices MobileAnalymator:显示移动设备上的数据变化
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102490
Victor Y. Chen, Cheryl Z. Qian, Li Zhang
{"title":"MobileAnalymator: Animating data changes on mobile devices","authors":"Victor Y. Chen, Cheryl Z. Qian, Li Zhang","doi":"10.1109/VAST.2011.6102490","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102490","url":null,"abstract":"MobileAnalymator (Mobile Analysis Animator) is a visual analytic system designed to analyze geospatial-temporal data on mobile devices. The system is an Internet based application that allows analysts to work in flexile enviornments at anytime. Its client side is developed by Adobe Flash to animate and interact with data. The server side uses Java and MySQL to query, compute, and serve data. The analyst can run the analytical task from a tablet (or computer) with Internet connection. MobileAnalymator adopted spatial and temporal autocorrelations in the interface design and integrated tangible interaction in the navigation to support analysis process.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125752357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Visualizing an information assurance risk taxonomy 可视化信息保障风险分类
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102477
V. Lemieux, B. Endicott-Popovsky, Karl Eckler, Thomas Dang, A. Jansen
{"title":"Visualizing an information assurance risk taxonomy","authors":"V. Lemieux, B. Endicott-Popovsky, Karl Eckler, Thomas Dang, A. Jansen","doi":"10.1109/VAST.2011.6102477","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102477","url":null,"abstract":"The researchers explore the intersections between Information Assurance and Risk using visual analysis of text mining operations. The methodological approach involves searching for and extracting for analysis those abstracts and keywords groupings that relate to risk within a defined subset of scientific research journals. This analysis is conducted through a triangulated study incorporating visualizations produced using both Starlight and In-Spire visual analysis software. The results are definitional, showing current attitudes within the Information Assurance research community towards risk management strategies, while simultaneously demonstrating the value of visual analysis processes when engaging in sense making of a large body of knowledge.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132466328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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