Pub Date : 2024-12-01Epub Date: 2024-10-04DOI: 10.1016/j.visinf.2024.09.007
An-An Liu , Quanhan Wu , Chenxi Huang , Chao Xue , Xianzhu Liu , Ning Xu
Knowledge-based Visual Dialog is a challenging vision-language task, where an agent engages in dialog to answer questions with humans based on the input image and corresponding commonsense knowledge. The debiasing methods based on causal graphs have gradually sparked much attention in the field of Visual Dialog (VD), yielding impressive achievements. However, existing studies focus on the coarse-grained deconfounding, which lacks a principled analysis of the bias. In this paper, we propose a fined-grained study of deconfounding on: (1) We define the confounder from two perspectives. The first is user preference (denoted as ), derived from human-annotated dialog history, which may introduce spurious correlations between questions and answers. The second is commonsense language bias (denoted as ), where certain words appear so frequently in the retrieved commonsense knowledge that the model tends to memorize these patterns, thereby establishing spurious correlations between the commonsense knowledge and the answers. (2) Given that the current question directly influences answer generation, we further decompose the confounders into and , based on their relevance to the current question. Specifically, and represent dialog history and high-frequency words that are highly correlated with the current question, while and are sampled from dialog history and words with low relevance to the current question. Through a comprehensive evaluation and comparison of all components, we demonstrate the necessity of jointly considering both and . Fine-grained deconfounding, particularly with respect to the current question, proves to be more effective. Ablation studies, quantitative results, and visualizations further confirm the effectiveness of the proposed method.
{"title":"A fine-grained deconfounding study for knowledge-based visual dialog","authors":"An-An Liu , Quanhan Wu , Chenxi Huang , Chao Xue , Xianzhu Liu , Ning Xu","doi":"10.1016/j.visinf.2024.09.007","DOIUrl":"10.1016/j.visinf.2024.09.007","url":null,"abstract":"<div><div>Knowledge-based Visual Dialog is a challenging vision-language task, where an agent engages in dialog to answer questions with humans based on the input image and corresponding commonsense knowledge. The debiasing methods based on causal graphs have gradually sparked much attention in the field of Visual Dialog (VD), yielding impressive achievements. However, existing studies focus on the coarse-grained deconfounding, which lacks a principled analysis of the bias. In this paper, we propose a fined-grained study of deconfounding on: (1) We define the confounder from two perspectives. The first is user preference (denoted as <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>h</mi></mrow></msub></math></span>), derived from human-annotated dialog history, which may introduce spurious correlations between questions and answers. The second is commonsense language bias (denoted as <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span>), where certain words appear so frequently in the retrieved commonsense knowledge that the model tends to memorize these patterns, thereby establishing spurious correlations between the commonsense knowledge and the answers. (2) Given that the current question directly influences answer generation, we further decompose the confounders into <span><math><mrow><msub><mrow><mi>U</mi></mrow><mrow><mi>h</mi><mn>1</mn></mrow></msub><mo>,</mo><msub><mrow><mi>U</mi></mrow><mrow><mi>h</mi><mn>2</mn></mrow></msub></mrow></math></span> and <span><math><mrow><msub><mrow><mi>U</mi></mrow><mrow><mi>c</mi><mn>1</mn></mrow></msub><mo>,</mo><msub><mrow><mi>U</mi></mrow><mrow><mi>c</mi><mn>2</mn></mrow></msub></mrow></math></span>, based on their relevance to the current question. Specifically, <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>h</mi><mn>1</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>c</mi><mn>1</mn></mrow></msub></math></span> represent dialog history and high-frequency words that are highly correlated with the current question, while <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>h</mi><mn>2</mn></mrow></msub></math></span> and <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>c</mi><mn>2</mn></mrow></msub></math></span> are sampled from dialog history and words with low relevance to the current question. Through a comprehensive evaluation and comparison of all components, we demonstrate the necessity of jointly considering both <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>h</mi></mrow></msub></math></span> and <span><math><msub><mrow><mi>U</mi></mrow><mrow><mi>c</mi></mrow></msub></math></span>. Fine-grained deconfounding, particularly with respect to the current question, proves to be more effective. Ablation studies, quantitative results, and visualizations further confirm the effectiveness of the proposed method.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 4","pages":"Pages 36-47"},"PeriodicalIF":3.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143098852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-09-11DOI: 10.1016/j.visinf.2024.09.002
Shuangcheng Jiao , Jiang Cheng , Zhaosong Huang , Tong Li , Tiankai Xie , Wei Chen , Yuxin Ma , Xumeng Wang
Differential privacy is an essential approach for privacy preservation in data queries. However, users face a significant challenge in selecting an appropriate privacy scheme, as they struggle to balance the utility of query results with the preservation of diverse individual privacy. Customizing a privacy scheme becomes even more complex in dealing with queries that involve multiple data attributes. When adversaries attempt to breach privacy firewalls by conducting multiple regular data queries with various attribute values, data owners must arduously discern unpredictable disclosure risks and construct suitable privacy schemes. In this paper, we propose a visual analysis approach for formulating privacy schemes of differential privacy. Our approach supports the identification and simulation of potential privacy attacks in querying statistical results of multi-dimensional databases. We also developed a prototype system, called DPKnob, which integrates multiple coordinated views. DPKnob not only allows users to interactively assess and explore privacy exposure risks by browsing high-risk attacks, but also facilitates an iterative process for formulating and optimizing privacy schemes based on differential privacy. This iterative process allows users to compare different schemes, refine their expectations of privacy and utility, and ultimately establish a well-balanced privacy scheme. The effectiveness of this study is verified by a user study and two case studies with real-world datasets.
{"title":"DPKnob: A visual analysis approach to risk-aware formulation of differential privacy schemes for data query scenarios","authors":"Shuangcheng Jiao , Jiang Cheng , Zhaosong Huang , Tong Li , Tiankai Xie , Wei Chen , Yuxin Ma , Xumeng Wang","doi":"10.1016/j.visinf.2024.09.002","DOIUrl":"10.1016/j.visinf.2024.09.002","url":null,"abstract":"<div><div>Differential privacy is an essential approach for privacy preservation in data queries. However, users face a significant challenge in selecting an appropriate privacy scheme, as they struggle to balance the utility of query results with the preservation of diverse individual privacy. Customizing a privacy scheme becomes even more complex in dealing with queries that involve multiple data attributes. When adversaries attempt to breach privacy firewalls by conducting multiple regular data queries with various attribute values, data owners must arduously discern unpredictable disclosure risks and construct suitable privacy schemes. In this paper, we propose a visual analysis approach for formulating privacy schemes of differential privacy. Our approach supports the identification and simulation of potential privacy attacks in querying statistical results of multi-dimensional databases. We also developed a prototype system, called DPKnob, which integrates multiple coordinated views. DPKnob not only allows users to interactively assess and explore privacy exposure risks by browsing high-risk attacks, but also facilitates an iterative process for formulating and optimizing privacy schemes based on differential privacy. This iterative process allows users to compare different schemes, refine their expectations of privacy and utility, and ultimately establish a well-balanced privacy scheme. The effectiveness of this study is verified by a user study and two case studies with real-world datasets.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 42-52"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142358092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-09-10DOI: 10.1016/j.visinf.2024.08.002
Han Bao , Xuhong Zhang , Qinying Wang , Kangming Liang , Zonghui Wang , Shouling Ji , Wenzhi Chen
Existing lip synchronization (lip-sync) methods generate accurately synchronized mouths and faces in a generated video. However, they still confront the problem of artifacts in regions of non-interest (RONI), e.g., background and other parts of a face, which decreases the overall visual quality. To solve these problems, we innovatively introduce diverse image inpainting to lip-sync generation. We propose Modulated Inpainting Lip-sync GAN (MILG), an audio-constraint inpainting network to predict synchronous mouths. MILG utilizes prior knowledge of RONI and audio sequences to predict lip shape instead of image generation, which can keep the RONI consistent. Specifically, we integrate modulated spatially probabilistic diversity normalization (MSPD Norm) in our inpainting network, which helps the network generate fine-grained diverse mouth movements guided by the continuous audio features. Furthermore, to lower the training overhead, we modify the contrastive loss in lip-sync to support small-batch-size and few-sample training. Extensive experiments demonstrate that our approach outperforms the existing state-of-the-art of image quality and authenticity while keeping lip-sync.
{"title":"MILG: Realistic lip-sync video generation with audio-modulated image inpainting","authors":"Han Bao , Xuhong Zhang , Qinying Wang , Kangming Liang , Zonghui Wang , Shouling Ji , Wenzhi Chen","doi":"10.1016/j.visinf.2024.08.002","DOIUrl":"10.1016/j.visinf.2024.08.002","url":null,"abstract":"<div><div>Existing lip synchronization (lip-sync) methods generate accurately synchronized mouths and faces in a generated video. However, they still confront the problem of artifacts in regions of non-interest (RONI), <em>e.g.</em>, background and other parts of a face, which decreases the overall visual quality. To solve these problems, we innovatively introduce diverse image inpainting to lip-sync generation. We propose Modulated Inpainting Lip-sync GAN (MILG), an audio-constraint inpainting network to predict synchronous mouths. MILG utilizes prior knowledge of RONI and audio sequences to predict lip shape instead of image generation, which can keep the RONI consistent. Specifically, we integrate modulated spatially probabilistic diversity normalization (MSPD Norm) in our inpainting network, which helps the network generate fine-grained diverse mouth movements guided by the continuous audio features. Furthermore, to lower the training overhead, we modify the contrastive loss in lip-sync to support small-batch-size and few-sample training. Extensive experiments demonstrate that our approach outperforms the existing state-of-the-art of image quality and authenticity while keeping lip-sync.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 71-81"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-09-12DOI: 10.1016/j.visinf.2024.09.001
Shaoxu Meng , Tong Wu , Fang-Lue Zhang , Shu-Yu Chen , Yuewen Ma , Wenbo Hu , Lin Gao
Recent advancements in the field have resulted in significant progress in achieving realistic head reconstruction and manipulation using neural radiance fields (NeRF). Despite these advances, capturing intricate facial details remains a persistent challenge. Moreover, casually captured input, involving both head poses and camera movements, introduces additional difficulties to existing methods of head avatar reconstruction. To address the challenge posed by video data captured with camera motion, we propose a novel method, AvatarWild, for reconstructing head avatars from monocular videos taken by consumer devices. Notably, our approach decouples the camera pose and head pose, allowing reconstructed avatars to be visualized with different poses and expressions from novel viewpoints. To enhance the visual quality of the reconstructed facial avatar, we introduce a view-dependent detail enhancement module designed to augment local facial details without compromising viewpoint consistency. Our method demonstrates superior performance compared to existing approaches, as evidenced by reconstruction and animation results on both multi-view and single-view datasets. Remarkably, our approach stands out by exclusively relying on video data captured by portable devices, such as smartphones. This not only underscores the practicality of our method but also extends its applicability to real-world scenarios where accessibility and ease of data capture are crucial.
{"title":"AvatarWild: Fully controllable head avatars in the wild","authors":"Shaoxu Meng , Tong Wu , Fang-Lue Zhang , Shu-Yu Chen , Yuewen Ma , Wenbo Hu , Lin Gao","doi":"10.1016/j.visinf.2024.09.001","DOIUrl":"10.1016/j.visinf.2024.09.001","url":null,"abstract":"<div><div>Recent advancements in the field have resulted in significant progress in achieving realistic head reconstruction and manipulation using neural radiance fields (NeRF). Despite these advances, capturing intricate facial details remains a persistent challenge. Moreover, casually captured input, involving both head poses and camera movements, introduces additional difficulties to existing methods of head avatar reconstruction. To address the challenge posed by video data captured with camera motion, we propose a novel method, AvatarWild, for reconstructing head avatars from monocular videos taken by consumer devices. Notably, our approach decouples the camera pose and head pose, allowing reconstructed avatars to be visualized with different poses and expressions from novel viewpoints. To enhance the visual quality of the reconstructed facial avatar, we introduce a view-dependent detail enhancement module designed to augment local facial details without compromising viewpoint consistency. Our method demonstrates superior performance compared to existing approaches, as evidenced by reconstruction and animation results on both multi-view and single-view datasets. Remarkably, our approach stands out by exclusively relying on video data captured by portable devices, such as smartphones. This not only underscores the practicality of our method but also extends its applicability to real-world scenarios where accessibility and ease of data capture are crucial.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 96-106"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142442832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-09-26DOI: 10.1016/j.visinf.2024.09.005
Tong Zhang, Jie Li, Chao Xu
We propose an approach to learning sample embedding for analyzing multi-dimensional datasets. The basic idea is to extract rules from the given dataset and learn the embedding for each sample based on the rules it satisfies. The approach can filter out pattern-irrelevant attributes, leading to significant visual structures of samples satisfying the same rules in the projection. In addition, analysts can understand a visual structure based on the rules that the involved samples satisfy, which improves the projection’s pattern interpretability. Our research involves two methods for achieving and applying the approach. First, we give a method to learn rule-based embedding for each sample. Second, we integrate the method into a system to achieve an analytical workflow. Cases on real-world dataset and quantitative experiment results show the usability and effectiveness of our approach.
{"title":"Visual exploration of multi-dimensional data via rule-based sample embedding","authors":"Tong Zhang, Jie Li, Chao Xu","doi":"10.1016/j.visinf.2024.09.005","DOIUrl":"10.1016/j.visinf.2024.09.005","url":null,"abstract":"<div><div>We propose an approach to learning sample embedding for analyzing multi-dimensional datasets. The basic idea is to extract rules from the given dataset and learn the embedding for each sample based on the rules it satisfies. The approach can filter out pattern-irrelevant attributes, leading to significant visual structures of samples satisfying the same rules in the projection. In addition, analysts can understand a visual structure based on the rules that the involved samples satisfy, which improves the projection’s pattern interpretability. Our research involves two methods for achieving and applying the approach. First, we give a method to learn rule-based embedding for each sample. Second, we integrate the method into a system to achieve an analytical workflow. Cases on real-world dataset and quantitative experiment results show the usability and effectiveness of our approach.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 53-56"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-09-16DOI: 10.1016/j.visinf.2024.09.004
Jinyuan Yang, Soumyabrata Dev, Abraham G. Campbell
Real-time rendering applications leverage heterogeneous computing to optimize performance. However, software development across multiple devices presents challenges, including data layout inconsistencies, synchronization issues, resource management complexities, and architectural disparities. Additionally, the creation of such systems requires verbose and unsafe programming models. Recent developments in domain-specific and unified shading languages aim to mitigate these issues. Yet, current programming models primarily address data layout consistency, neglecting other persistent challenges.In this paper, we introduce RenderKernel, a programming model designed to simplify the development of real-time rendering systems. Recognizing the need for a high-level approach, RenderKernel addresses the specific challenges of real-time rendering, enabling development on heterogeneous systems as if they were homogeneous. This model allows for early detection and prevention of errors due to system heterogeneity at compile-time. Furthermore, RenderKernel enables the use of common programming patterns from homogeneous environments, freeing developers from the complexities of underlying heterogeneous systems. Developers can focus on coding unique application features, thereby enhancing productivity and reducing the cognitive load associated with real-time rendering system development.
{"title":"RenderKernel: High-level programming for real-time rendering systems","authors":"Jinyuan Yang, Soumyabrata Dev, Abraham G. Campbell","doi":"10.1016/j.visinf.2024.09.004","DOIUrl":"10.1016/j.visinf.2024.09.004","url":null,"abstract":"<div><div>Real-time rendering applications leverage heterogeneous computing to optimize performance. However, software development across multiple devices presents challenges, including data layout inconsistencies, synchronization issues, resource management complexities, and architectural disparities. Additionally, the creation of such systems requires verbose and unsafe programming models. Recent developments in domain-specific and unified shading languages aim to mitigate these issues. Yet, current programming models primarily address data layout consistency, neglecting other persistent challenges.In this paper, we introduce RenderKernel, a programming model designed to simplify the development of real-time rendering systems. Recognizing the need for a high-level approach, RenderKernel addresses the specific challenges of real-time rendering, enabling development on heterogeneous systems as if they were homogeneous. This model allows for early detection and prevention of errors due to system heterogeneity at compile-time. Furthermore, RenderKernel enables the use of common programming patterns from homogeneous environments, freeing developers from the complexities of underlying heterogeneous systems. Developers can focus on coding unique application features, thereby enhancing productivity and reducing the cognitive load associated with real-time rendering system development.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 82-95"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-07-25DOI: 10.1016/j.visinf.2024.06.003
Tao Yu , Shaoxuan Lai , Wenjin Zhang , Jun Cui , Jun Tao
Cultural relics visualization brings digital archives of relics to broader audiences in many applications, such as education, historical research, and virtual museums. However, previous research mainly focused on modeling and rendering the relics. While enhancing accessibility, these techniques still provide limited ability to improve user engagement. In this paper, we introduce RelicCARD, a semantics-based augmented reality (AR) tangible interaction design for exploring cultural relics. Our design uses an easily available tangible interface to encourage the users to interact with a large collection of relics. The tangible interface allows users to explore, select, and arrange relics to form customized scenes. To guide the design of the interface, we formalize a design space by connecting the semantics in relics, the tangible interaction patterns, and the exploration tasks. We realize the design space as a tangible interactive prototype and examine its feasibility and effectiveness using multiple case studies and an expert evaluation. Finally, we discuss the findings in the evaluation and future directions to improve the design and implementation of the interactive design space.
{"title":"RelicCARD: Enhancing cultural relics exploration through semantics-based augmented reality tangible interaction design","authors":"Tao Yu , Shaoxuan Lai , Wenjin Zhang , Jun Cui , Jun Tao","doi":"10.1016/j.visinf.2024.06.003","DOIUrl":"10.1016/j.visinf.2024.06.003","url":null,"abstract":"<div><div>Cultural relics visualization brings digital archives of relics to broader audiences in many applications, such as education, historical research, and virtual museums. However, previous research mainly focused on modeling and rendering the relics. While enhancing accessibility, these techniques still provide limited ability to improve user engagement. In this paper, we introduce RelicCARD, a semantics-based augmented reality (AR) tangible interaction design for exploring cultural relics. Our design uses an easily available tangible interface to encourage the users to interact with a large collection of relics. The tangible interface allows users to explore, select, and arrange relics to form customized scenes. To guide the design of the interface, we formalize a design space by connecting the semantics in relics, the tangible interaction patterns, and the exploration tasks. We realize the design space as a tangible interactive prototype and examine its feasibility and effectiveness using multiple case studies and an expert evaluation. Finally, we discuss the findings in the evaluation and future directions to improve the design and implementation of the interactive design space.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 32-41"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141839325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-06-27DOI: 10.1016/j.visinf.2024.06.001
Christina Stoiber , Daniela Moitzi , Holger Stitz , Florian Grassinger , Anto Silviya Geo Prakash , Dominic Girardi , Marc Streit , Wolfgang Aigner
Visualization onboarding supports users in reading, interpreting, and extracting information from visual data representations. General-purpose onboarding tools and libraries are applicable for explaining a wide range of graphical user interfaces but cannot handle specific visualization requirements. This paper describes a first step towards developing an onboarding library called VisAhoi, which is easy to integrate, extend, semi-automate, reuse, and customize. VisAhoi supports the creation of onboarding elements for different visualization types and datasets. We demonstrate how to extract and describe onboarding instructions using three well-known high-level descriptive visualization grammars — Vega-Lite, Plotly.js, and ECharts. We show the applicability of our library by performing two usage scenarios that describe the integration of VisAhoi into a VA tool for the analysis of high-throughput screening (HTS) data and, second, into a Flourish template to provide an authoring tool for data journalists for a treemap visualization. We provide a supplementary website (https://datavisyn.github.io/visAhoi/) that demonstrates the applicability of VisAhoi to various visualizations, including a bar chart, a horizon graph, a change matrix/heatmap, a scatterplot, and a treemap visualization.
{"title":"VisAhoi: Towards a library to generate and integrate visualization onboarding using high-level visualization grammars","authors":"Christina Stoiber , Daniela Moitzi , Holger Stitz , Florian Grassinger , Anto Silviya Geo Prakash , Dominic Girardi , Marc Streit , Wolfgang Aigner","doi":"10.1016/j.visinf.2024.06.001","DOIUrl":"10.1016/j.visinf.2024.06.001","url":null,"abstract":"<div><p>Visualization onboarding supports users in reading, interpreting, and extracting information from visual data representations. General-purpose onboarding tools and libraries are applicable for explaining a wide range of graphical user interfaces but cannot handle specific visualization requirements. This paper describes a first step towards developing an onboarding library called VisAhoi, which is easy to <em>integrate, extend, semi-automate, reuse, and customize</em>. VisAhoi supports the creation of onboarding elements for different visualization types and datasets. We demonstrate how to extract and describe onboarding instructions using three well-known high-level descriptive visualization grammars — Vega-Lite, Plotly.js, and ECharts. We show the applicability of our library by performing two usage scenarios that describe the integration of VisAhoi into a VA tool for the analysis of high-throughput screening (HTS) data and, second, into a Flourish template to provide an authoring tool for data journalists for a treemap visualization. We provide a supplementary website (<span><span>https://datavisyn.github.io/visAhoi/</span><svg><path></path></svg></span>) that demonstrates the applicability of VisAhoi to various visualizations, including a bar chart, a horizon graph, a change matrix/heatmap, a scatterplot, and a treemap visualization.</p></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 1-17"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468502X24000214/pdfft?md5=b500608cf3b6d6a02fdc48334024bff3&pid=1-s2.0-S2468502X24000214-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141954338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-09-13DOI: 10.1016/j.visinf.2024.09.003
Qiru Wang, Kai Xu, Robert S. Laramee
Cartograms serve as representations of geographical and abstract data, employing a value-by-area mapping technique. As a variant of the Dorling cartogram, the Demers cartogram utilizes squares instead of circles to represent regions. This alternative approach allows for a more intuitive comparison of regions, utilizing screen space more efficiently. However, a drawback of the Dorling cartogram and its variants lies in the potential displacement of regions from their original positions, ultimately compromising legibility, readability, and accuracy. To tackle this limitation, we propose a novel hybrid cartogram layout algorithm that incorporates topological elements, such as rivers, into Demers cartograms. The presence of rivers significantly impacts both the layout and visual appearance of the cartograms. Through a user study conducted on an Electronic Health Records (EHR) dataset, we evaluate the efficacy of the proposed hybrid layout algorithm. The obtained results illustrate that this approach successfully retains key aspects of the original cartogram while enhancing legibility, readability, and overall accuracy.
{"title":"Demers cartogram with rivers","authors":"Qiru Wang, Kai Xu, Robert S. Laramee","doi":"10.1016/j.visinf.2024.09.003","DOIUrl":"10.1016/j.visinf.2024.09.003","url":null,"abstract":"<div><div>Cartograms serve as representations of geographical and abstract data, employing a value-by-area mapping technique. As a variant of the Dorling cartogram, the Demers cartogram utilizes squares instead of circles to represent regions. This alternative approach allows for a more intuitive comparison of regions, utilizing screen space more efficiently. However, a drawback of the Dorling cartogram and its variants lies in the potential displacement of regions from their original positions, ultimately compromising legibility, readability, and accuracy. To tackle this limitation, we propose a novel hybrid cartogram layout algorithm that incorporates topological elements, such as rivers, into Demers cartograms. The presence of rivers significantly impacts both the layout and visual appearance of the cartograms. Through a user study conducted on an Electronic Health Records (EHR) dataset, we evaluate the efficacy of the proposed hybrid layout algorithm. The obtained results illustrate that this approach successfully retains key aspects of the original cartogram while enhancing legibility, readability, and overall accuracy.</div></div>","PeriodicalId":36903,"journal":{"name":"Visual Informatics","volume":"8 3","pages":"Pages 57-70"},"PeriodicalIF":3.8,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142417781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-01Epub Date: 2024-07-19DOI: 10.1016/j.visinf.2024.07.001
Ran Wang , Qianhe Chen , Yong Wang , Lewei Xiong , Boyang Shen
Online job advertisements on various job portals or websites have become the most popular way for people to find potential career opportunities nowadays. However, the majority of these job sites are limited to offering fundamental filters such as job titles, keywords, and compensation ranges. This often poses a challenge for job seekers in efficiently identifying relevant job advertisements that align with their unique skill sets amidst a vast sea of listings. Thus, we propose well-coordinated visualizations to provide job seekers with three levels of details of job information: a skill-job overview visualizes skill sets, employment posts as well as relationships between them with a hierarchical visualization design; a post exploration view leverages an augmented radar-chart glyph to represent job posts and further facilitates users’ swift comprehension of the pertinent skills necessitated by respective positions; a post detail view lists the specifics of selected job posts for profound analysis and comparison. By using a real-world recruitment advertisement dataset collected from 51Job, one of the largest job websites in China, we conducted two case studies and user interviews to evaluate JobViz. The results demonstrated the usefulness and effectiveness of our approach.
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