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A Design Space for Explainable Ranking and Ranking Models 可解释排名和排名模型的设计空间
Eurographics Conference on Visualization Pub Date : 2022-05-27 DOI: 10.48550/arXiv.2205.15305
I. A. Hazwani, J. Schmid, M. Sachdeva, J. Bernard
{"title":"A Design Space for Explainable Ranking and Ranking Models","authors":"I. A. Hazwani, J. Schmid, M. Sachdeva, J. Bernard","doi":"10.48550/arXiv.2205.15305","DOIUrl":"https://doi.org/10.48550/arXiv.2205.15305","url":null,"abstract":"Item ranking systems support users in multi-criteria decision-making tasks. Users need to trust rankings and ranking algorithms to reflect user preferences nicely while avoiding systematic errors and biases. However, today only few approaches help end users, model developers, and analysts to explain rankings. We report on the study of explanation approaches from the perspectives of recommender systems, explainable AI, and visualization research and propose the first cross-domain design space for explainers of item rankings. In addition, we leverage the descriptive power of the design space to characterize a) existing explainers and b) three main user groups involved in ranking explanation tasks. The generative power of the design space is a means for future designers and developers to create more target-oriented solutions in this only weakly exploited space.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"17 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132026238","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
Inferential Tasks as an Evaluation Technique for Visualization 作为可视化评价技术的推理任务
Eurographics Conference on Visualization Pub Date : 2022-05-11 DOI: 10.48550/arXiv.2205.05712
Ashley Suh, Abigail Mosca, Shannon Robinson, Quinn Pham, Dylan Cashman, Alvitta Ottley, Remco Chang
{"title":"Inferential Tasks as an Evaluation Technique for Visualization","authors":"Ashley Suh, Abigail Mosca, Shannon Robinson, Quinn Pham, Dylan Cashman, Alvitta Ottley, Remco Chang","doi":"10.48550/arXiv.2205.05712","DOIUrl":"https://doi.org/10.48550/arXiv.2205.05712","url":null,"abstract":"Designing suitable tasks for visualization evaluation remains challenging. Traditional evaluation techniques commonly rely on 'low-level' or 'open-ended' tasks to assess the efficacy of a proposed visualization, however, nontrivial trade-offs exist between the two. Low-level tasks allow for robust quantitative evaluations, but are not indicative of the complex usage of a visualization. Open-ended tasks, while excellent for insight-based evaluations, are typically unstructured and require time-consuming interviews. Bridging this gap, we propose inferential tasks: a complementary task category based on inferential learning in psychology. Inferential tasks produce quantitative evaluation data in which users are prompted to form and validate their own findings with a visualization. We demonstrate the use of inferential tasks through a validation experiment on two well-known visualization tools.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124982756","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
Data+Shift: Supporting visual investigation of data distribution shifts by data scientists Data+Shift:支持数据科学家对数据分布变化进行可视化调查
Eurographics Conference on Visualization Pub Date : 2022-04-29 DOI: 10.48550/arXiv.2204.14025
João Palmeiro, Beatriz Malveiro, Rita Costa, David Polido, Ricardo Moreira, P. Bizarro
{"title":"Data+Shift: Supporting visual investigation of data distribution shifts by data scientists","authors":"João Palmeiro, Beatriz Malveiro, Rita Costa, David Polido, Ricardo Moreira, P. Bizarro","doi":"10.48550/arXiv.2204.14025","DOIUrl":"https://doi.org/10.48550/arXiv.2204.14025","url":null,"abstract":"Machine learning on data streams is increasingly more present in multiple domains. However, there is often data distribution shift that can lead machine learning models to make incorrect decisions. While there are automatic methods to detect when drift is happening, human analysis, often by data scientists, is essential to diagnose the causes of the problem and adjust the system. We propose Data+Shift, a visual analytics tool to support data scientists in the task of investigating the underlying factors of shift in data features in the context of fraud detection. Design requirements were derived from interviews with data scientists. Data+Shift is integrated with JupyterLab and can be used alongside other data science tools. We validated our approach with a think-aloud experiment where a data scientist used the tool for a fraud detection use case.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121837265","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
DSS: Drawing Dynamic Graphs with Spectral Sparsification DSS:绘制动态图形与谱稀疏
Eurographics Conference on Visualization Pub Date : 2022-01-01 DOI: 10.2312/evs.20221093
A. Meidiana, Seok-Hee Hong, Yanyi Pu, Justin Lee, P. Eades, Jinwook Seo
{"title":"DSS: Drawing Dynamic Graphs with Spectral Sparsification","authors":"A. Meidiana, Seok-Hee Hong, Yanyi Pu, Justin Lee, P. Eades, Jinwook Seo","doi":"10.2312/evs.20221093","DOIUrl":"https://doi.org/10.2312/evs.20221093","url":null,"abstract":"This paper presents DSS (Dynamic Spectral Sparsification), a sampling approach for drawing large and complex dynamic graphs which can preserve important structural properties of the original graph. Specifically, we present two variants: DSS-I (Independent) which performs spectral sparsification independently on each dynamic graph time slice; and DSS-U (Union) which performs spectral sparsification on the union graph of all time slices. Moreover, for evaluation of dynamic graph drawing using sampling approach, we introduce two new metrics: DSQ (Dynamic Sampling Quality) to measure how faithfully the samples represent the ground truth change in the dynamic graph, and DSDQ (Dynamic Sampling Drawing Quality) to measure how faithfully the drawings of the sample represent the ground truth change. Experiments demonstrate that DSS significantly outperform random sampling on quality metrics and visual comparison. On average, DSS obtains over 80% (resp., 30%) better DSQ (resp., DSDQ) than random sampling, and visually better preserves the ground truth changes in dynamic graphs.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128054490","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
Discussion Flows: An Interactive Visualization for Analyzing Engagement in Multi-Party Meetings 讨论流程:用于分析多方会议参与的交互式可视化
Eurographics Conference on Visualization Pub Date : 2021-06-14 DOI: 10.2312/EVS.20211060
Tao Wang, Mandy Keck, Zana Vosough
{"title":"Discussion Flows: An Interactive Visualization for Analyzing Engagement in Multi-Party Meetings","authors":"Tao Wang, Mandy Keck, Zana Vosough","doi":"10.2312/EVS.20211060","DOIUrl":"https://doi.org/10.2312/EVS.20211060","url":null,"abstract":"Engagement in multi-party meetings is a key indicator of outcome. Poor attendee involvement can hinder progress and hurt team cohesion. Thus, there is a strong motivation for organizations to better understand what happens in meetings and improve upon their experience. However, analyzing multi-party meetings is a challenging task, as one needs to consider both verbal exchanges and meeting dynamics among speakers. There is currently a lack of support on these unique tasks. In this paper, we present a new visual approach to help analyze multi-party meetings in industry settings: Discussion Flows, a multi-level interactive visualization tool. Its glyph-based overview allows effortless comparison of overall interactions among different meetings, whereas the individual meeting view uses flow diagrams to convey the relative participation of different speakers throughout the meeting agenda in different levels of details. We demonstrate our approach with meeting recordings from an open source dialogue corpora and use them as the benchmark dataset. CCS Concepts • Human-centered computing → Information visualization; Visualization techniques; Interactive systems and tools;","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128564521","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
A Tool to Help lay out Multiple View Visualisations Guided by View Analysis 一个工具，以帮助布局多个视图可视化指导的视图分析
Eurographics Conference on Visualization Pub Date : 2020-05-25 DOI: 10.2312/eurp.20201114
H. Al-Maneea, Jonathan C. Roberts
{"title":"A Tool to Help lay out Multiple View Visualisations Guided by View Analysis","authors":"H. Al-Maneea, Jonathan C. Roberts","doi":"10.2312/eurp.20201114","DOIUrl":"https://doi.org/10.2312/eurp.20201114","url":null,"abstract":"In this paper, we present ‘Layouts for Multiple View’ (LMV), a tool that helps users build, control and save multiple view visualisations simply and easily using a bespoke grammar. The tool incorporates template multiple view layout strategies as quantified from prior research on view analysis, and the user can build different layouts by defining the grammar, or through the linked visual interface. LMV saves the multiple view layout as a JSON file, including all the details of the layout and attributes of the visualisation, which can be subsequently loaded and adapted or used to create dashboards. LMV guides the user to (i) design and control the multiple view layout, (ii) add data and allocate a specific visualisation technique for each view, and (iii) to adapt specific appearance properties of the layout. CCS Concepts • Human-centered computing → Visualization systems and tools;","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132336795","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
Dissecting Visual Analytics: Comparing Frameworks for Interpreting and Modelling Observed Visual Analytics Behavior 剖析视觉分析:比较解释和建模观察到的视觉分析行为的框架
Eurographics Conference on Visualization Pub Date : 2020-05-24 DOI: 10.2312/evs.20201045
Vanessa Brown, C. Turkay, R. Jianu
{"title":"Dissecting Visual Analytics: Comparing Frameworks for Interpreting and Modelling Observed Visual Analytics Behavior","authors":"Vanessa Brown, C. Turkay, R. Jianu","doi":"10.2312/evs.20201045","DOIUrl":"https://doi.org/10.2312/evs.20201045","url":null,"abstract":"This paper provides an empirical, comparative exploration of the role of analytic frameworks in interpreting and modelling visual analytics behavior through data gathered in observational studies. The crucial research on understanding the complex and multi-faceted interplay between visual analytics tools and their users is often done through controlled or naturalistic observations of analysts engaging in the visual analytic process, followed by the interpretation of the observation data. The researchers in Human Computer Interaction and Cognitive Sciences have long used structured analytic frameworks for such analyses, where a guiding set of principles and questions direct attention to relevant aspects of the studied behavior, eventually leading to more complete and consistent analyses. Such frameworks are rarely applied in the visualization domain however, and information about how to apply them and their benefits is scarce. With this paper, we contribute a comparative account, grounded in empirical data collected in a user study with 10 participants using Tableau to analyze domain-specific data, of the types of insights we can glean from interpreting observational data using three different frameworks: Joint Action Theory, Distributed Cognition, and Situated Cognition.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116989202","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
Exploring Design Opportunities for Visually Congruent Proxemics in Information Visualization: A Design Space 探索信息可视化中视觉一致性的设计机会:一个设计空间
Eurographics Conference on Visualization Pub Date : 2020-05-01 DOI: 10.2312/evs.20201051
Neil Chulpongsatorn, Jackie Yu, S. Knudsen
{"title":"Exploring Design Opportunities for Visually Congruent Proxemics in Information Visualization: A Design Space","authors":"Neil Chulpongsatorn, Jackie Yu, S. Knudsen","doi":"10.2312/evs.20201051","DOIUrl":"https://doi.org/10.2312/evs.20201051","url":null,"abstract":"This project was funded in part by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 753816","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128003347","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
Characterizing Exploratory Behaviors on a Personal Visualization Interface Using Interaction Logs 使用交互日志描述个人可视化界面上的探索行为
Eurographics Conference on Visualization Pub Date : 2020-04-09 DOI: 10.31219/osf.io/axqwc
P. Sukumar, Gonzalo J. Martínez, Ted Grover, G. Mark, S. D’Mello, N. Chawla, Stephen M. Mattingly, A. Striegel
{"title":"Characterizing Exploratory Behaviors on a Personal Visualization Interface Using Interaction Logs","authors":"P. Sukumar, Gonzalo J. Martínez, Ted Grover, G. Mark, S. D’Mello, N. Chawla, Stephen M. Mattingly, A. Striegel","doi":"10.31219/osf.io/axqwc","DOIUrl":"https://doi.org/10.31219/osf.io/axqwc","url":null,"abstract":"Personal visualizations present a separate class of visualizations where users interact with their own data to draw inferences about themselves. In this paper, we study how a realistic understanding of personal visualizations can be gained from analyzing user interactions. We designed an interface presenting visualizations of the personal data gathered in a prior study and logged interactions from 369 participants as they each explored their own data. We found that the participants spent different amounts of time in exploring their data and used a variety of physical devices which could have affected their engagement with the visualizations. Our findings also suggest that the participants made more comparisons between their data instances than with the provided baselines and certain interface design choices, such as the ordering of options, influenced their exploratory behaviors.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133312099","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
TopoLines: Topological Smoothing for Line Charts TopoLines:折线图的拓扑平滑
Eurographics Conference on Visualization Pub Date : 2019-06-22 DOI: 10.2312/evs.20201053
Ashley Suh, Christopher Salgado, Mustafa Hajij, P. Rosen
{"title":"TopoLines: Topological Smoothing for Line Charts","authors":"Ashley Suh, Christopher Salgado, Mustafa Hajij, P. Rosen","doi":"10.2312/evs.20201053","DOIUrl":"https://doi.org/10.2312/evs.20201053","url":null,"abstract":"Line charts are commonly used to visualize a series of data samples. When the data are noisy, smoothing is applied to make the signal more apparent. However, the difference between signal and noise is ill-defined, as it depends upon the application domain of the data. Common methods used to smooth line charts, such as rank filters, convolutional filters, frequency domain filters, and subsampling, optimize on various properties of the data. However, these methods are only ideal in certain limited scenarios. We present TopoLines, a method for smoothing line charts by leveraging techniques from Topological Data Analysis. The design goal of TopoLines is to smooth line charts while maintaining prominent peaks, as defined by persistent homology, in the data. We compare TopoLines to 5 popular line smoothing methods using data from 4 application domains. We evaluate TopoLines in terms of $l^2$-norm of the residual as the simplification threshold is varied, and we perform a user study to evaluate users' perception of the accuracy of TopoLines.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121157288","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
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