Visual Informatics最新文献

英文中文

Key-isovalue selection and hierarchical exploration visualization of weather forecast ensembles

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2025-03-01 DOI: 10.1016/j.visinf.2025.02.001

Feng Zhou, Hao Hu, Fengjie Wang, Jiamin Zhu, Wenwen Gao, Min Zhu

Weather forecast ensembles are commonly used to assess the uncertainty and confidence of weather predictions. Conventional methods in meteorology often employ ensemble mean and standard deviation plots, as well as spaghetti plots, to visualize ensemble data. However, these methods suffer from significant information loss and visual clutter. In this paper, we propose a new approach for uncertainty visualization of weather forecast ensembles, including isovalue selection based on information loss and hierarchical visualization that integrates visual abstraction and detail preservation. Our approach uses non-uniform downsampling to select key-isovalues and provides an interactive visualization method based on hierarchical clustering. Firstly, we sample key-isovalues by contour probability similarity and determine the optimal sampling number using an information loss curve. Then, the corresponding isocontours are presented to guide users in selecting key-isovalues. Once the isovalue is chosen, we perform agglomerative hierarchical clustering on the isocontours based on signed distance fields and generate visual abstractions for each isocontour cluster to avoid visual clutter. We link a bubble tree to the visual abstractions to explore the details of isocontour clusters at different levels. We demonstrate the utility of our approach through two case studies with meteorological experts on real-world data. We further validate its effectiveness by quantitatively assessing information loss and visual clutter. Additionally, we confirm its usability through expert evaluation.

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引用次数: 0

A human-centric perspective on interpretability in large language models

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2025-03-01 DOI: 10.1016/j.visinf.2025.03.001

Zihan Zhou, Minfeng Zhu, Wei Chen

引用次数: 0

What about thematic information? An analysis of the multidimensional visualization of individual mobility

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2025-03-01 DOI: 10.1016/j.visinf.2025.02.002

Aline Menin , Clément Quere , Jorge Wagner , Sonia Chardonnel , Paule-Annick Davoine , Wolfgang Stuerzlinger , Carla Maria Dal Sasso Freitas , Luciana Nedel , Marco Winckler

This paper reviews the literature on the visualization of individual mobility data, with a focus on thematic integration. It emphasizes the importance of visualization in understanding mobility patterns within a population and how it helps mobility experts address domain-specific questions. We analyze 38 papers published between 2010 and 2024 in GIS and VIS venues that describe visualizations of multidimensional data related to individual movements in urban environments, concentrating on individual mobility rather than traffic data. Our primary aim is to report advances in interactive visualization for individual mobility analysis, particularly regarding the representation of thematic information about people’s motivations for mobility. Our findings indicate that the thematic dimension is only partially represented in the literature, despite its critical significance in transportation. This gap often stems from the challenge of identifying data sources that inherently provide this information, necessitating visualization designers and developers to navigate multiple, heterogeneous data sources. We identify the strengths and limitations of existing visualizations and suggest potential research directions for the field.

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引用次数: 0

ClayVolume: A progressive refinement interaction system for immersive visualization

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2025-03-01 DOI: 10.1016/j.visinf.2025.01.003

Zhenyuan Wang , Qing Zhao , Yue Zhang , Jinhui Zhang , Guihua Shan , Xiao Zhou , Dong Tian

Immersive visualization has become an important tool for discovering hidden patterns and obtaining insights from data. Target acquisition in immersive visualization is a fundamental step in visual analysis. However, limited visual encoding attributes and the presence of stacking and occlusion in immersive environments pose challenges in discovering valuable targets and making unambiguous selections. In this paper, we present ClayVolume, an interactive system designed for immersive visualization. It comprises metaphorical tools for customizing regions of interest (ROIs) and multiple views that serve as interactive and analytical mediums. ClayVolume empowers analysts to efficiently acquire valuable targets through a progressive refinement of interactive methods, enabling further extraction of insights. We evaluate ClayVolume in the scenario of immersive visualization of network data and perform a comparative analysis of its performance against other techniques in target selection tasks. The results indicate that ClayVolume enables flexible target selection in immersive visualization and provides fast target discovery and localization capabilities.

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引用次数: 0

EmotionLens: Interactive visual exploration of the circumplex emotion space in literary works via affective word clouds

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2025-03-01 DOI: 10.1016/j.visinf.2025.02.003

Bingyuan Wang , Qing Shi , Xiaohan Wang , You Zhou , Wei Zeng , Zeyu Wang

Emotion (e.g., valence and arousal) is an important factor in literature (e.g., poetry and prose), and has rich values for plotting the life and knowledge of historical figures and appreciating the aesthetics of literary works. Currently, digital humanities and computational literature apply data statistics extensively in emotion analysis but lack visual analytics for efficient exploration. To fill the gap, we propose a user-centric approach that integrates advanced machine learning models and intuitive visualization for emotion analysis in literature. We make three main contributions. First, we consolidate a new emotion dataset of literary works in different periods, literary genres, and language contexts, augmented with fine-grained valence and arousal labels. Next, we design an interactive visual analytic system named EmotionLens, which allows users to perform multi-granularity (e.g., individual, group, society) and multi-faceted (e.g., distribution, chronology, correlation) analyses of literary emotions, supporting both exploratory and confirmatory approaches in digital humanities. Specifically, we introduce a novel affective word cloud with augmented word weight, position, and color, to facilitate literary text analysis from an emotional perspective. To validate the usability and effectiveness of EmotionLens, we provide two consecutive case studies, two user studies, and interviews with experts from different domains. Our results show that EmotionLens bridges literary text, emotion, and various other attributes, enables efficient knowledge discovery in massive data, and facilitates raising and validating domain-specific hypotheses in literature.

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引用次数: 0

Leveraging personality as a proxy of perceived transparency in hierarchical visualizations

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2025-02-22 DOI: 10.1016/j.visinf.2025.01.002

Tomás Alves , Carlota Dias , Daniel Gonçalves , Sandra Gama

Understanding which factors affect information visualization transparency continues to be one of the most relevant challenges in current research, especially since trust models how users build on the knowledge and use it. This work extends the current body of research by studying the user’s subjective evaluation of the visualization transparency of hierarchical charts through the clarity, coverage, and look and feel dimensions. Additionally, we extend the user profile to better understand whether personality facets manifest a biasing effect on the trust-building process. Our results show that the data encodings do not affect how users perceive visualization transparency while controlling for personality factors. Regarding personality, the propensity to trust affects how they judge the clarity of a hierarchical chart. Our findings provide new insights into the research challenges of measuring trust and understanding the transparency of information visualization. Specifically, we explore how personality factors manifest in this trust-building relationship and user interaction within visualization systems.

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引用次数: 0

Visual comparative analytics of multimodal transportation

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2025-01-16 DOI: 10.1016/j.visinf.2025.01.001

Zikun Deng , Haoming Chen , Qing-Long Lu , Zicheng Su , Tobias Schreck , Jie Bao , Yi Cai

Contemporary urban transportation systems frequently depend on a variety of modes to provide residents with travel services. Understanding a multimodal transportation system is pivotal for devising well-informed planning; however, it is also inherently challenging for traffic analysts and planners. This challenge stems from the necessity of evaluating and contrasting the quality of transportation services across multiple modes. Existing methods are constrained in offering comprehensive insights into the system, primarily due to the inadequacy of multimodal traffic data necessary for fair comparisons and their inability to equip analysts and planners with the means for exploration and reasoned analysis within the urban spatial context. To this end, we first acquire sufficient multimodal trips leveraging well-established navigation platforms that can estimate the routes with the least travel time given an origin and a destination (an OD pair). We also propose TraDyssey, a visual analytics system that enables analysts and planners to evaluate and compare multiple modes by exploring acquired massive multimodal trips. TraDyssey follows a streamlined query-and-explore workflow supported by user-friendly and effective interactive visualizations. Specifically, a revisited difference-aware parallel coordinate plot (PCP) is designed for overall mode comparisons based on multimodal trips. Trip groups can be flexibly queried on the PCP based on differential features across modes. The queried trips are then organized and presented on a geographic map by OD pairs, forming a group-OD-trip hierarchy of visual exploration. Domain experts gained valuable insights into transportation planning through real-world case studies using TraDyssey.

当代城市交通系统通常依靠多种模式为居民提供出行服务。了解多式联运系统对于制定明智的规划至关重要，但对交通分析师和规划师来说，这本身也是一项挑战。这一挑战源于对多种交通方式的交通服务质量进行评估和对比的必要性。现有方法在提供对系统的全面见解方面受到限制，主要原因是缺乏进行公平比较所需的多模式交通数据，以及无法为分析师和规划师提供在城市空间背景下进行探索和合理分析的手段。为此，我们首先利用成熟的导航平台获取足够的多式联运出行数据，这些平台可以根据起点和终点（OD 对）估算出旅行时间最少的路线。我们还提出了 TraDyssey，这是一个可视化分析系统，使分析师和规划师能够通过探索获取的大量多式联运行程来评估和比较多种模式。TraDyssey 采用简化的查询和探索工作流程，并辅以用户友好和有效的交互式可视化。具体来说，基于多式联运的整体模式比较设计了一个重新设计的差异感知平行坐标图（PCP）。根据不同模式的差异特征，可以在平行坐标图上灵活地查询行程组。然后，查询到的行程按 OD 对在地理地图上进行组织和展示，形成一个可视化探索的组-OD-行程层次结构。领域专家通过使用 TraDyssey 进行实际案例研究，对交通规划获得了宝贵的见解。

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引用次数: 0

Out-of-focus artifacts mitigation and autofocus methods for 3D displays

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2024-12-20 DOI: 10.1016/j.visinf.2024.12.001

T. Chlubna , T. Milet , P. Zemčík

This paper proposes a novel content-aware method for automatic focusing of the scene on a 3D display. The method addresses a common problem that visualized content is often out of focus, which adversely affects perceived 3D content. The method outperforms existing focusing method, having the error lower by almost 30%. The existing and novel focusing is extended with depth-of-field enhancement of the scene to mitigate out-of-focus artifacts. The relation between the total depth range of the scene and the visual quality of the result is discussed and evaluated according to human perception experiments. A space-warping method for synthetic scenes is proposed to reduce out-of-focus artifacts while maintaining the scene appearance. A user study was conducted to evaluate the proposed methods and identify the crucial parameters in the scene-focusing process on the 3D stereoscopic display by Looking Glass Factory. The study confirmed the efficiency of the proposals and discovered that the depth-of-field artifact mitigation might not be suitable for all scenes despite theoretical hypotheses. The overall proposal of this paper is a set of methods that can be used to produce the best user experience with an arbitrary scene displayed on a 3D display.

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引用次数: 0

Transforming cinematography lighting education in the metaverse

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2024-12-05 DOI: 10.1016/j.visinf.2024.11.003

Xian Xu , Wai Tong , Zheng Wei , Meng Xia , Lik-Hang Lee , Huamin Qu

Lighting education is a foundational component of cinematography education. However, many art schools do not have expensive soundstages for traditional cinematography lessons. Migrating physical setups to virtual experiences is a potential solution driven by metaverse initiatives. Yet there is still a lack of knowledge on the design of a VR system for teaching cinematography. We first analyzed the educational needs for cinematography lighting education by conducting interviews with six cinematography professionals from academia and industry. Accordingly, we presented Art Mirror, a VR soundstage for teachers and students to emulate cinematography lighting in virtual scenarios. We evaluated Art Mirror from the aspects of usability, realism, presence, sense of agency, and collaboration. Sixteen participants were invited to take a cinematography lighting course and assess the design elements of Art Mirror. Our results demonstrate that Art Mirror is usable and useful for cinematography lighting education, which sheds light on the design of VR cinematography education.

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引用次数: 0

ArtEyer: Enriching GPT-based agents with contextual data visualizations for fine art authentication

IF 3.8 3区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Visual Informatics

Pub Date : 2024-12-01 DOI: 10.1016/j.visinf.2024.11.001

Tan Tang , Yanhong Wu , Junming Gao , Kejia Ruan , Yanjie Zhang , Shuainan Ye , Yingcai Wu , Xiaojiao Chen

Fine art authentication plays a significant role in protecting cultural heritage and ensuring the integrity of artworks. Traditional authentication methods require professionals to collect many reference materials and conduct detailed analyses. To ease the difficulty, we collaborate with domain experts to develop a GPT-based agent, namely ArtEyer, that offers accurate attributions, determines the origin and authorship, and executes visual analytics. Despite the convenience of the conversational user interface, novice users may still face challenges due to the hallucination issue and the steep learning curve associated with prompting. To face these obstacles, we propose a novel solution that places interactive data visualizations into the conversations. We create contextual visualizations from an external domain-dependent database to ensure data trustworthiness and allow users to provide precise instructions to the agent by interacting directly with these visualizations, thus overcoming the vagueness inherent in natural language-based prompting. We evaluate ArtEyer through an in-lab user study and demonstrate its usage with a real-world case.

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