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

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Visual analysis of route diversity 路线多样性的可视化分析
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102455
He Liu, Yuan Gao, Lu Lu, Siyuan Liu, Huamin Qu, L. Ni
{"title":"Visual analysis of route diversity","authors":"He Liu, Yuan Gao, Lu Lu, Siyuan Liu, Huamin Qu, L. Ni","doi":"10.1109/VAST.2011.6102455","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102455","url":null,"abstract":"Route suggestion is an important feature of GPS navigation systems. Recently, Microsoft T-drive has been enabled to suggest routes chosen by experienced taxi drivers for given source/destination pairs in given time periods, which often take less time than the routes calculated according to distance. However, in real environments, taxi drivers may use different routes to reach the same destination, which we call route diversity. In this paper we first propose a trajectory visualization method that examines the regions where the diversity exists and then develop several novel visualization techniques to display the high dimensional attributes and statistics associated with different routes to help users analyze diversity patterns. Our techniques have been applied to the real trajectory data of thousands of taxis and some interesting findings about route diversity have been obtained. We further demonstrate that our system can be used not only to suggest better routes for drivers but also to analyze traffic bottlenecks for transportation management.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"10 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":"116930522","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: 121
Exploring proportions: Comparative visualization of categorical data 探索比例:分类数据的比较可视化
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102481
H. Piringer, M. Buchetics
{"title":"Exploring proportions: Comparative visualization of categorical data","authors":"H. Piringer, M. Buchetics","doi":"10.1109/VAST.2011.6102481","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102481","url":null,"abstract":"This poster describes an approach to facilitate comparisons in multi-dimensional categorical data. The key idea is to represent over- or under-proportional relationships explicitly. On an overview level, the visualization of various measures conveys pair-wise relationships between categorical dimensions. For more details, interaction supports to relate a single category to all categories of multiple dimensions. We discuss methods for representing relationships and visualization-driven strategies for ordering dimensions and categories, and we illustrate the approach by means of data from a social survey.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"35 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":"127471794","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: 4
Evaluation of large display interaction using smart phones 使用智能手机的大屏幕交互评估
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102466
J. Bauer, S. Thelen, A. Ebert
{"title":"Evaluation of large display interaction using smart phones","authors":"J. Bauer, S. Thelen, A. Ebert","doi":"10.1109/VAST.2011.6102466","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102466","url":null,"abstract":"Visual analytics, “the science of analytical reasoning facilitated by visual interactive interfaces” [5], puts high demands on the applications visualization as well as interaction capabilities. Due to their size large high-resolution screens have become popular display devices, especially when used in collaborative data analysis scenarios. However, traditional interaction methods based on combinations of computer mice and keyboards often do not scale to the number of users or the size of the display. Modern smart phones featuring multi-modal input/output and considerable memory offer a way to address these issues. In the last couple of years they have become common everyday life gadgets. In this paper we conduct an extensive user study comparing the experience of test candidates when using traditional input devices and metaphors with the one when using new smart phone based techniques, like multi-modal drag and tilt. Candidates were asked to complete various interaction tasks relevant for most applications on a large, monitor-based, high-resolution tiled wall system. Our study evaluates both user performance and satisfaction, identifying strengths and weaknesses of the researched interaction methods in specific tasks. Results reveal good performance of users in certain tasks when using the new interaction techniques. Even first-time users were able to complete a task faster with the smart phone than with traditional devices.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"111 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":"125196617","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
Visual analytics decision support environment for epidemic modeling and response evaluation 可视化分析决策支持环境的流行病建模和响应评估
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102457
S. Afzal, Ross Maciejewski, D. Ebert
{"title":"Visual analytics decision support environment for epidemic modeling and response evaluation","authors":"S. Afzal, Ross Maciejewski, D. Ebert","doi":"10.1109/VAST.2011.6102457","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102457","url":null,"abstract":"In modeling infectious diseases, scientists are studying the mechanisms by which diseases spread, predicting the future course of the outbreak, and evaluating strategies applied to control an epidemic. While recent work has focused on accurately modeling disease spread, less work has been performed in developing interactive decision support tools for analyzing the future course of the outbreak and evaluating potential disease mitigation strategies. The absence of such tools makes it difficult for researchers, analysts and public health officials to evaluate response measures within outbreak scenarios. As such, our research focuses on the development of an interactive decision support environment in which users can explore epidemic models and their impact. This environment provides a spatiotemporal view where users can interactively utilize mitigative response measures and observe the impact of their decision over time. Our system also provides users with a linked decision history visualization and navigation tool that support the simultaneous comparison of mortality and infection rates corresponding to different response measures at different points in time.","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":"130954985","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: 95
PORGY: Interactive and visual reasoning with graph rewriting systems 与图形重写系统的交互和视觉推理
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102480
Bruno Pinaud, Jonathan Dubois, G. Melançon
{"title":"PORGY: Interactive and visual reasoning with graph rewriting systems","authors":"Bruno Pinaud, Jonathan Dubois, G. Melançon","doi":"10.1109/VAST.2011.6102480","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102480","url":null,"abstract":"Graph rewriting systems are easily described and explained. They can be seen as a game where one iterates transformation rules on an initial graph, until some condition is met. A rule describes a local pattern (i.e. a subgraph) that must be identified in a graph and specifies how to transform this subgraph. The graph rewriting formalism is at the same time extremely rich and complex, making the study of a model expressed in terms of graph rewriting quite challenging. For instance, predicting whether rules can be applied in any order is often difficult. When modelling complex systems, graphical formalisms have clear advantages: they are more intuitive and make it easier to visualize a system and convey intuitions about it. This work focuses on the design of an interactive visual graph rewriting system which supports graphical manipulations and computation to reason and simulate on a system. PORGY has been designed based on regular exchanges with graph rewriting systems experts and users over the past three years. The design choices relied on a careful methodology inspired from Munzner's nested process model for visualization design and validation [4].","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"34 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":"130254840","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: 4
Find distance function, hide model inference 查找距离函数,隐藏模型推理
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102478
Jingjing Liu, Eli T. Brown, Remco Chang
{"title":"Find distance function, hide model inference","authors":"Jingjing Liu, Eli T. Brown, Remco Chang","doi":"10.1109/VAST.2011.6102478","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102478","url":null,"abstract":"Faced with a large, high-dimensional dataset, many turn to data analysis approaches that they understand less well than the domain of their data. An expert's knowledge can be leveraged into many types of analysis via a domain-specific distance function, but creating such a function is not intuitive to do by hand. We have created a system that shows an initial visualization, adapts to user feedback, and produces a distance function as a result. Specifically, we present a multidimensional scaling (MDS) visualization and an iterative feedback mechanism for a user to affect the distance function that informs the visualization without having to adjust the parameters of the visualization directly. An encouraging experimental result suggests that using this tool, data attributes with useless data are given low importance in the distance function.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"196 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":"115152854","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: 5
A state transition approach to understanding users' interactions 用于理解用户交互的状态转换方法
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102476
D. Jeong, Soo-Yeon Ji, W. Ribarsky, Remco Chang
{"title":"A state transition approach to understanding users' interactions","authors":"D. Jeong, Soo-Yeon Ji, W. Ribarsky, Remco Chang","doi":"10.1109/VAST.2011.6102476","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102476","url":null,"abstract":"Understanding users' interactions is considered as one of the important research topics in visual analytics. Although numerous empirical user studies have been performed to understand a user's interaction, a limited study has been successful in connecting the user's interaction to his/her reasoning. In this paper, we present an approach of understanding experts' interactive analysis by connecting their interactions to conclusions (i.e. findings) through a state transition approach.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"106 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":"121854736","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
Network-based visual analysis of tabular data 基于网络的表格数据可视化分析
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102440
Zhicheng Liu, S. Navathe, J. Stasko
{"title":"Network-based visual analysis of tabular data","authors":"Zhicheng Liu, S. Navathe, J. Stasko","doi":"10.1109/VAST.2011.6102440","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102440","url":null,"abstract":"Tabular data are pervasive. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look at multiple networks from different perspectives, at different levels of abstraction, and with different edge semantics. We present a system called Ploceus that offers a general approach for performing multi-dimensional and multi-level network-based visual analysis on multivariate tabular data. Powered by an underlying relational algebraic framework, Ploceus supports flexible construction and transformation of networks through a direct manipulation interface, and integrates dynamic network manipulation with visual exploration for a seamless analytic experience.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"40 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":"122013925","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: 63
Visual analytic roadblocks for novice investigators 新手调查人员的视觉分析障碍
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102435
B. Kwon, Brian D. Fisher, Ji Soo Yi
{"title":"Visual analytic roadblocks for novice investigators","authors":"B. Kwon, Brian D. Fisher, Ji Soo Yi","doi":"10.1109/VAST.2011.6102435","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102435","url":null,"abstract":"We have observed increasing interest in visual analytics tools and their applications in investigative analysis. Despite the growing interest and substantial studies regarding the topic, understanding the major roadblocks of using such tools from novice users' perspectives is still limited. Therefore, we attempted to identify such “visual analytic roadblocks” for novice users in an investigative analysis scenario. To achieve this goal, we reviewed the existing models, theories, and frameworks that could explain the cognitive processes of human-visualization interaction in investigative analysis. Then, we conducted a qualitative experiment with six novice participants, using a slightly modified version of pair analytics, and analyzed the results through the open-coding method. As a result, we came up with four visual analytic roadblocks and explained these roadblocks using existing cognitive models and theories. We also provided design suggestions to overcome these roadblocks.","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":"127120974","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: 44
Using random projections to identify class-separating variables in high-dimensional spaces 利用随机投影识别高维空间中的类分离变量
2011 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2011-12-15 DOI: 10.1109/VAST.2011.6102465
Anushka Anand, Leland Wilkinson, Dang Tuan Nhon
{"title":"Using random projections to identify class-separating variables in high-dimensional spaces","authors":"Anushka Anand, Leland Wilkinson, Dang Tuan Nhon","doi":"10.1109/VAST.2011.6102465","DOIUrl":"https://doi.org/10.1109/VAST.2011.6102465","url":null,"abstract":"Projection Pursuit has been an effective method for finding interesting low-dimensional (usually 2D) projections in multidimensional spaces. Unfortunately, projection pursuit is not scalable to high-dimensional spaces. We introduce a novel method for approximating the results of projection pursuit to find class-separating views by using random projections. We build an analytic visualization platform based on this algorithm that is scalable to extremely large problems. Then, we discuss its extension to the recognition of other noteworthy configurations in high-dimensional spaces.","PeriodicalId":103998,"journal":{"name":"2011 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"62 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":"134147320","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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