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2019 IEEE Visualization Conference (VIS)最新文献

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Data-Driven Colormap Optimization for 2D Scalar Field Visualization 数据驱动的二维标量场可视化颜色图优化
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933764
Qiong Zeng, Yinqiao Wang, Jian Zhang, Wenting Zhang, Changhe Tu, I. Viola, Yunhai Wang
{"title":"Data-Driven Colormap Optimization for 2D Scalar Field Visualization","authors":"Qiong Zeng, Yinqiao Wang, Jian Zhang, Wenting Zhang, Changhe Tu, I. Viola, Yunhai Wang","doi":"10.1109/VISUAL.2019.8933764","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933764","url":null,"abstract":"Colormapping is an effective and popular visual representation to analyze data patterns for 2D scalar fields. Scientists usually adopt a default colormap and adjust it to fit data in a trial-and-error process. Even though a few colormap design rules and measures are proposed, there is no automatic algorithm to directly optimize a default colormap for better revealing spatial patterns hidden in unevenly distributed data, especially the boundary characteristics. To fill this gap, we conduct a pilot study with six domain experts and summarize three requirements for automated colormap adjustment. We formulate the colormap adjustment as a nonlinear constrained optimization problem, and develop an efficient GPU-based implementation accompanying with a few interactions. We demonstrate the usefulness of our method with two case studies.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126049569","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: 9
GalStamps: Analyzing Real and Simulated Galaxy Observations GalStamps:分析真实和模拟的星系观测
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933671
Nina McCurdy, Miriah D. Meyer
{"title":"GalStamps: Analyzing Real and Simulated Galaxy Observations","authors":"Nina McCurdy, Miriah D. Meyer","doi":"10.1109/VISUAL.2019.8933671","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933671","url":null,"abstract":"One way astronomers and astrophysicists study galaxy formation and evolution is by analyzing and comparing real galaxy observations, captured by telescopes, and simulated galaxy observations, generated from theoretical models. They approach this through a combination of statistical and visual analysis, conducted either independently or sequentially. During the first year of an ongoing design study with astronomers and astrophysicists, we explored approaches to integrating statistical and visual analysis to enhance understanding of these data. Contributions from this stage of the study include a data and task abstraction for statistically and visually analyzing real and simulated galaxy observations, as well as an initial design, implemented in a prototype called GalStamps, and evaluated through two case studies with domain experts.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121875914","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
FacIt: Factorizing Tensors into Interpretable and Scrutinizable Patterns 事实:将张量分解为可解释和可仔细检查的模式
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933750
Xidao Wen, K. Pelechrinis, Y. Lin, Xi Liu, Yongsu Ahn, Nan Cao
{"title":"FacIt: Factorizing Tensors into Interpretable and Scrutinizable Patterns","authors":"Xidao Wen, K. Pelechrinis, Y. Lin, Xi Liu, Yongsu Ahn, Nan Cao","doi":"10.1109/VISUAL.2019.8933750","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933750","url":null,"abstract":"Tensor Factorization has been widely used in many fields to discover latent patterns from multidimensional data. Interpreting or scrutinizing the tensor factorization results are, however, by no means easy. We introduce FacIt, a generic visual analytic system that directly factorizes tensor-formatted data into a visual representation of patterns to facilitate result interpretation, scrutinization, information query, as well as model selection. Our design consists of (i) a suite of model scrutinizing and inspection tools that allows efficient tensor model selection (commonly known as rank selection problem) and (ii) an interactive visualization design that empowers users with both characteristics- and content-driven pattern discovery. We demonstrate the effectiveness of our system through usage scenarios with policy adoption analysis.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122026744","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: 0
H-Matrix: Hierarchical Matrix for Visual Analysis of Cross-Linguistic Features in Large Learner Corpora h矩阵:用于大型学习者语料库跨语言特征视觉分析的层次矩阵
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933537
Mariana Shimabukuro, Jessica Zipf, Mennatallah El-Assady, C. Collins
{"title":"H-Matrix: Hierarchical Matrix for Visual Analysis of Cross-Linguistic Features in Large Learner Corpora","authors":"Mariana Shimabukuro, Jessica Zipf, Mennatallah El-Assady, C. Collins","doi":"10.1109/VISUAL.2019.8933537","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933537","url":null,"abstract":"This paper presents a visualization technique for cross-linguistic error analysis in large learner corpora. H-Matrix combines a matrix, which is commonly used by linguists to investigate cross-linguistic patterns, with a tree diagram to aggregate and interactively re-weight the importance of matrix rows to create custom investigative views. Our technique can help experts to perform data operations, such as, feature aggregation, filtering, ordering and language comparison interactively without having to reprocess the data. H-Matrix dynamically links the high-level multi-language overview to the extracted textual examples, and a reading view where linguists can see the detected features in context, confirm and generate hypotheses.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131208837","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
Hybrid Grids for Sparse Volume Rendering 稀疏体渲染的混合网格
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933631
Stefan Zellmann, D. Meurer, U. Lang
{"title":"Hybrid Grids for Sparse Volume Rendering","authors":"Stefan Zellmann, D. Meurer, U. Lang","doi":"10.1109/VISUAL.2019.8933631","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933631","url":null,"abstract":"Shallow k-d trees are an efficient empty space skipping data structure for sparse volume rendering and can be constructed in real-time for moderately sized data sets. Larger volume data sets however require deeper k-d trees that sufficiently cull empty space but take longer to construct. In contrast to k-d trees, uniform grids have inferior culling properties but can be constructed in real-time. We propose a hybrid data structure that employs hierarchical subdivision at the root level and a uniform grid at the leaf level to balance construction and rendering times for sparse volume rendering. We provide a thorough evaluation of this spatial index and compare it to state of the art space skipping data structures.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131496382","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
[Copyright notice] (版权)
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/visual.2019.8933690
{"title":"[Copyright notice]","authors":"","doi":"10.1109/visual.2019.8933690","DOIUrl":"https://doi.org/10.1109/visual.2019.8933690","url":null,"abstract":"","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134207668","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: 0
Time Varying Predominance Tag Maps 时变优势标签图
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933654
Martin Reckziegel, S. Jänicke
{"title":"Time Varying Predominance Tag Maps","authors":"Martin Reckziegel, S. Jänicke","doi":"10.1109/VISUAL.2019.8933654","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933654","url":null,"abstract":"Visually conveying time-dependent changes in tag maps is insufficiently addressed by current approaches. Typically, for each time range a tag map is determined, and the change between tag maps of subsequent time ranges is progressively visualized. Our method compares tag maps locally in order to enable a continuous display of geographical topic changes among subsequent time ranges. We further provide an alternate tag map variant focusing on frequency changes instead of relative frequency values to visualize the geospatial-temporal rise and fall of topics.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"506 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134075388","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
VIS 2019 Committees VIS 2019委员会
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/visual.2019.8933601
{"title":"VIS 2019 Committees","authors":"","doi":"10.1109/visual.2019.8933601","DOIUrl":"https://doi.org/10.1109/visual.2019.8933601","url":null,"abstract":"","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116199805","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: 0
Visual Analysis of the Time Management of Learning Multiple Courses in Online Learning Environment 在线学习环境下多门课程学习时间管理的可视化分析
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933778
Huan He, Bo Dong, Q. Zheng, Dehai Di, Yating Lin
{"title":"Visual Analysis of the Time Management of Learning Multiple Courses in Online Learning Environment","authors":"Huan He, Bo Dong, Q. Zheng, Dehai Di, Yating Lin","doi":"10.1109/VISUAL.2019.8933778","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933778","url":null,"abstract":"Self-paced online learning not only provides the opportunities of learning anytime but also chanllenges students’ time management, especially in the context of learning multiple courses at same time. The inappropriate scheduling of multiple courses may affect student engagement and learning performance, thus how to arrange the study time of multiple courses is a concern of both instructors and students. Existing studies related to student engagement and time management in online learning mainly focus on providing self-regulated learning strategies and evaluating learning performance. However, these methods have limited abilities to gain intuitive understanding of the time management of multi-course learning. To address this issue, we present LearnerVis to help users analyze how students schedule their multi-course learning. LearnerVis visualize the temporal features of learning process, and it enables users to customize student groups to compare the differences in student engagement and time management. A case study is conducted to demonstrate the usefulness of the system with real-word dataset.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129292856","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 Markov Model of Users’ Interactive Behavior in Scatterplots 散点图中用户交互行为的马尔科夫模型
2019 IEEE Visualization Conference (VIS) Pub Date : 2019-10-01 DOI: 10.1109/VISUAL.2019.8933779
Emily Wall, Arup Arcalgud, Kuhu Gupta, Andrew Jo
{"title":"A Markov Model of Users’ Interactive Behavior in Scatterplots","authors":"Emily Wall, Arup Arcalgud, Kuhu Gupta, Andrew Jo","doi":"10.1109/VISUAL.2019.8933779","DOIUrl":"https://doi.org/10.1109/VISUAL.2019.8933779","url":null,"abstract":"Recently, Wall et al. proposed a set of computational metrics for quantifying cognitive bias based on user interaction sequences. The metrics rely on a Markov model to predict a user’s next interaction based on the current interaction. The metrics characterize how a user’s actual interactive behavior deviates from a theoretical baseline, where \"unbiased behavior\" was previously defined to be equal probabilities of all interactions. In this paper, we analyze the assumptions made of these metrics. We conduct a study in which participants, subject to anchoring bias, interact with a scatterplot to complete a categorization task. Our results indicate that, rather than equal probabilities of all interactions, unbiased behavior across both bias conditions can be better approximated by proximity of data points.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123393652","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: 10
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