Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00035
Tyson Neuroth, K. Ma
The distance plot (or unthresholded recurrence plot) has been shown to be a useful tool for analyzing spatiotemporal patterns in high-dimensional phase space trajectories. We incorporate this technique into an interactive visualization with multiple linked phase plots, and extend the distance plot to also visualize marker particle weights from particle-in-cell (PIC) simulations together with the phase space trajectories. By linking the distance plot with phase plots, one can more easily investigate the spatiotemporal patterns, and by extending the plot to visualize particle weights in conjunction with the phase space trajectories, the visualization better supports the needs of domain experts studying particle-in-cell simulations. We demonstrate our resulting visualization design using particles from an XGC Tokamak fusion simulation.
{"title":"Interactive Spatiotemporal Visualization of Phase Space Particle Trajectories Using Distance Plots","authors":"Tyson Neuroth, K. Ma","doi":"10.1109/PacificVis.2019.00035","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00035","url":null,"abstract":"The distance plot (or unthresholded recurrence plot) has been shown to be a useful tool for analyzing spatiotemporal patterns in high-dimensional phase space trajectories. We incorporate this technique into an interactive visualization with multiple linked phase plots, and extend the distance plot to also visualize marker particle weights from particle-in-cell (PIC) simulations together with the phase space trajectories. By linking the distance plot with phase plots, one can more easily investigate the spatiotemporal patterns, and by extending the plot to visualize particle weights in conjunction with the phase space trajectories, the visualization better supports the needs of domain experts studying particle-in-cell simulations. We demonstrate our resulting visualization design using particles from an XGC Tokamak fusion simulation.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127373775","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00022
Yalong Yang, Sarah Goodwin
In this paper, we present our analysis of five expert interviews, each from a different application domain. Such analysis is crucial to understanding the real-world scenarios of analysing geographically-embedded flow data. The results of our analysis show that similar high-level tasks were conducted in different domains. To better describe the targets of these tasks, we proposed three flow-targets for analysing geographically-embedded flow data: single flow, total flow and regional flow.
{"title":"What-Why Analysis of Expert Interviews: Analysing Geographically-Embedded Flow Data","authors":"Yalong Yang, Sarah Goodwin","doi":"10.1109/PacificVis.2019.00022","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00022","url":null,"abstract":"In this paper, we present our analysis of five expert interviews, each from a different application domain. Such analysis is crucial to understanding the real-world scenarios of analysing geographically-embedded flow data. The results of our analysis show that similar high-level tasks were conducted in different domains. To better describe the targets of these tasks, we proposed three flow-targets for analysing geographically-embedded flow data: single flow, total flow and regional flow.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134346142","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00044
Chanhee Park, Jina Lee, Hyunwoo Han, Kyungwon Lee
Performance analysis is essential for improving classification models. However, existing performance analysis tools do not provide actionable insights such as the cause of misclassification. Machine learning practitioners face difficulties such as prioritizing model, looking over confusion between classes. In addition, existing performance analysis tools that provide feature-level analysis are difficult to apply to image classification problems. This study has been proposed to solve these difficulties. In this paper, we present an interactive visual analytics system for diagnosing the performance of multiclass classification models. Our system is able to compare multiple models, find weaknesses, and obtain actionable insights for improving models. Our visualization consists of three views for analyzing performance at the class, confusion, and instance levels. We demonstrate our system using MNIST handwritten digits data.
{"title":"ComDia+: An Interactive Visual Analytics System for Comparing, Diagnosing, and Improving Multiclass Classifiers","authors":"Chanhee Park, Jina Lee, Hyunwoo Han, Kyungwon Lee","doi":"10.1109/PacificVis.2019.00044","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00044","url":null,"abstract":"Performance analysis is essential for improving classification models. However, existing performance analysis tools do not provide actionable insights such as the cause of misclassification. Machine learning practitioners face difficulties such as prioritizing model, looking over confusion between classes. In addition, existing performance analysis tools that provide feature-level analysis are difficult to apply to image classification problems. This study has been proposed to solve these difficulties. In this paper, we present an interactive visual analytics system for diagnosing the performance of multiclass classification models. Our system is able to compare multiple models, find weaknesses, and obtain actionable insights for improving models. Our visualization consists of three views for analyzing performance at the class, confusion, and instance levels. We demonstrate our system using MNIST handwritten digits data.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114206341","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00040
Maksim Gomov, Tarik Crnovrsanin, Keshav Dasu, K. Ma
Wildfires cause immense costs to human life, property, and the environment. As the impact of climate change increases the frequency and severity of wildfires, a renewed effort to understand these phenomena and their catalysts has increased. In this paper, we introduce a system that couples multiple sources of data and visualization to enable analysts to study historical fire data. We show two use cases to demonstrate the effectiveness of our system.
{"title":"An Interactive System for Exploring Historical Fire Data","authors":"Maksim Gomov, Tarik Crnovrsanin, Keshav Dasu, K. Ma","doi":"10.1109/PacificVis.2019.00040","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00040","url":null,"abstract":"Wildfires cause immense costs to human life, property, and the environment. As the impact of climate change increases the frequency and severity of wildfires, a renewed effort to understand these phenomena and their catalysts has increased. In this paper, we introduce a system that couples multiple sources of data and visualization to enable analysts to study historical fire data. We show two use cases to demonstrate the effectiveness of our system.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132875428","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00020
Ricardo Colasanti, R. Borgo, Mark W. Jones
We seek to answer the question on whether different geometrical attributes within a glyph can bias interpretation of data. We focus on a specific visual encoding, the Emoji, and evaluate its effectiveness at encoding multidimensional features. Given the anthropomorphic nature of the encoding we seek to quantify the amount of bias the encoding itself introduces, and use this to balance the Emoji glyph to remove that bias. We perform our analysis by comparing Emoji with Chernoff faces, of which they can be seen as direct descendant. Results shed light on how this new approach of feature-tuning in glyph design can influence overall effectiveness of novel multidimensional encodings.
{"title":"Emoji and Chernoff - A Fine Balancing Act or are we Biased?","authors":"Ricardo Colasanti, R. Borgo, Mark W. Jones","doi":"10.1109/PacificVis.2019.00020","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00020","url":null,"abstract":"We seek to answer the question on whether different geometrical attributes within a glyph can bias interpretation of data. We focus on a specific visual encoding, the Emoji, and evaluate its effectiveness at encoding multidimensional features. Given the anthropomorphic nature of the encoding we seek to quantify the amount of bias the encoding itself introduces, and use this to balance the Emoji glyph to remove that bias. We perform our analysis by comparing Emoji with Chernoff faces, of which they can be seen as direct descendant. Results shed light on how this new approach of feature-tuning in glyph design can influence overall effectiveness of novel multidimensional encodings.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123786346","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00028
Chanhee Park, S. Do, Eunjeong Lee, Hanna Jang, Sungchan Jung, Hyunwoo Han, Kyungwon Lee
This study proposes a visualization that can assist computer scientists and data scientists to make decisions by exploring technology trends. While it is important for them to understand the technology trends in the rapidly changing computer science and data science fields, it takes considerable time and knowledge to acquire good information about these trends. Particularly, data/computer scientists with little experience in the field find it difficult to obtain information on such trends. Therefore, we propose a visualization system that can easily and quickly explore the technology trends in computer and data science. This study aims to identify the key technologies and developers in a specific field, and other technologies deeply related to specific technologies, and explore the changes in popularity of technologies, languages, and libraries over time. This study includes two case studies to obtain information using the proposed visualization. We demonstrate our system with GitHub repositories data.
{"title":"GitViz: An Interactive Visualization System for Analyzing Development Trends in the Open-Source Software Community","authors":"Chanhee Park, S. Do, Eunjeong Lee, Hanna Jang, Sungchan Jung, Hyunwoo Han, Kyungwon Lee","doi":"10.1109/PacificVis.2019.00028","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00028","url":null,"abstract":"This study proposes a visualization that can assist computer scientists and data scientists to make decisions by exploring technology trends. While it is important for them to understand the technology trends in the rapidly changing computer science and data science fields, it takes considerable time and knowledge to acquire good information about these trends. Particularly, data/computer scientists with little experience in the field find it difficult to obtain information on such trends. Therefore, we propose a visualization system that can easily and quickly explore the technology trends in computer and data science. This study aims to identify the key technologies and developers in a specific field, and other technologies deeply related to specific technologies, and explore the changes in popularity of technologies, languages, and libraries over time. This study includes two case studies to obtain information using the proposed visualization. We demonstrate our system with GitHub repositories data.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131895730","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00038
R. Khulusi, J. Kusnick, Josef Focht, S. Jänicke
Joseph Priestley's Chart of Biography is a masterpiece of hand-drawn data visualization. He arranged the lifespans of around 2,000 individuals on a timeline, and the chart obtained great value for teaching purposes. We present a generic, interactive variant of the chart adopting Priestley's basic design principles. Our proposed visualization allows for dynamically defining person groups to be visually compared on different zoom levels. We designed the visualization in cooperation with musicologists having multifaceted research interests on a biographical database of musicians. On the one hand, we enable deriving new relationships between musicians in order to extend the underlying database, and on the other hand, our visualization supports analyzing time-dependent changes of musical institutions. Various usage scenarios outline the benefit of the Interactive Chart of Biography for research in musicology.
{"title":"An Interactive Chart of Biography","authors":"R. Khulusi, J. Kusnick, Josef Focht, S. Jänicke","doi":"10.1109/PacificVis.2019.00038","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00038","url":null,"abstract":"Joseph Priestley's Chart of Biography is a masterpiece of hand-drawn data visualization. He arranged the lifespans of around 2,000 individuals on a timeline, and the chart obtained great value for teaching purposes. We present a generic, interactive variant of the chart adopting Priestley's basic design principles. Our proposed visualization allows for dynamically defining person groups to be visually compared on different zoom levels. We designed the visualization in cooperation with musicologists having multifaceted research interests on a biographical database of musicians. On the one hand, we enable deriving new relationships between musicians in order to extend the underlying database, and on the other hand, our visualization supports analyzing time-dependent changes of musical institutions. Various usage scenarios outline the benefit of the Interactive Chart of Biography for research in musicology.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126670506","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00017
Ciara Fletcher, Weidong Huang, David Arness, Quang Vinh Nguyen
We process information in memory and different people have different memory capacity. It is therefore important to understand possible impact of memory capacity when it comes to graph comprehension. In an attempt towards this direction, we conducted a user study investigating the impact of working memory capacity on graph reading task performance. Forty-six university students participated in the study performing a graph reading task with one hundred graph drawings of different complexity levels. Their working memory capacity and task performance (accuracy and time) were measured and recorded. The results of regression analyses indicated that working memory capacity was a significant predictor of performance accuracy, but not for response time. In this paper, we present the details of the study and discuss our findings and limitations of the study. Possible future research directions are also suggested.
{"title":"The Role of Working Memory Capacity in Graph Reading Performance","authors":"Ciara Fletcher, Weidong Huang, David Arness, Quang Vinh Nguyen","doi":"10.1109/PacificVis.2019.00017","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00017","url":null,"abstract":"We process information in memory and different people have different memory capacity. It is therefore important to understand possible impact of memory capacity when it comes to graph comprehension. In an attempt towards this direction, we conducted a user study investigating the impact of working memory capacity on graph reading task performance. Forty-six university students participated in the study performing a graph reading task with one hundred graph drawings of different complexity levels. Their working memory capacity and task performance (accuracy and time) were measured and recorded. The results of regression analyses indicated that working memory capacity was a significant predictor of performance accuracy, but not for response time. In this paper, we present the details of the study and discuss our findings and limitations of the study. Possible future research directions are also suggested.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114469154","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}
Pub Date : 2019-04-01DOI: 10.1109/PacificVis.2019.00036
Qing Chen, Zhen Li, T. Pong, Huamin Qu
The practical power of data visualization is currently attracting much attention in the e-learning domain. A growing number of studies have been conducted in recent years to help instructors better analyze learner behavior and reflect on their teaching. However, current elearning dashboards and visualization systems usually require a lot of time and effort into the exploration process. Moreover, the lack of communication power of existing systems constrains users from organizing the narrative of information pieces into a compelling data story. In this paper, we have proposed a narrative visualization approach with an interactive slideshow that helps instructors and education experts explore potential learning patterns and convey data stories. This approach contains three key components: guided-tour concept, drill-down path, and dig-in exploration dimension. The use cases further demonstrate the potential of employing this visual narrative approach in the e-learning context.
{"title":"Designing Narrative Slideshows for Learning Analytics","authors":"Qing Chen, Zhen Li, T. Pong, Huamin Qu","doi":"10.1109/PacificVis.2019.00036","DOIUrl":"https://doi.org/10.1109/PacificVis.2019.00036","url":null,"abstract":"The practical power of data visualization is currently attracting much attention in the e-learning domain. A growing number of studies have been conducted in recent years to help instructors better analyze learner behavior and reflect on their teaching. However, current elearning dashboards and visualization systems usually require a lot of time and effort into the exploration process. Moreover, the lack of communication power of existing systems constrains users from organizing the narrative of information pieces into a compelling data story. In this paper, we have proposed a narrative visualization approach with an interactive slideshow that helps instructors and education experts explore potential learning patterns and convey data stories. This approach contains three key components: guided-tour concept, drill-down path, and dig-in exploration dimension. The use cases further demonstrate the potential of employing this visual narrative approach in the e-learning context.","PeriodicalId":208856,"journal":{"name":"2019 IEEE Pacific Visualization Symposium (PacificVis)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117064903","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}
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