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CHI conference on Human Factors in Computing Systems (CHI)

作者： Li, Wenchao Schottler, Sarah Scott-Brown, James Wang, Yun Chen, Siming Qu, Huamin Bach, Benjamin Hong Kong Univ Sci & Technol Hong Kong Peoples R China Univ Edinburgh Edinburgh Midlothian Scotland Microsoft Res Asia Beijing Peoples R China Fudan Univ Shanghai Peoples R China

ISBN: (纸本)9781450394215

This paper introduces semi-automatic data tours to aid the exploration of complex networks. Exploring networks requires significant effort and expertise and can be time-consuming and challenging. Distinct from guidance and recommender systems for visual analytics, we provide a set of goal-oriented tours for network overview, ego-network analysis, community exploration, and other tasks. Based on interviews with five network analysts, we developed a user interface (NetworkNarratives) and 10 example tours. The interface allows analysts to navigate an interactive slideshow featuring facts about the network using visualizations and textual annotations. On each slide, an analyst can freely explore the network and specify nodes, links, or subgraphs as seed elements for follow-up tours. Two studies, comprising eight expert and 14 novice analysts, show that data tours reduce exploration effort, support learning about network exploration, and can aid the dissemination of analysis results. NetworkNarratives is available online, together with detailed illustrations for each tour.

关键词： Guided exploration network visualization

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Contextualized visual analytics for multivariate events

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visual INFORMATICS 2025年第2期9卷

作者： Peng, Lei Lin, Ziyue Andrienko, Natalia Andrienko, Gennady Chen, Siming Fudan Univ Sch Data Sci Shanghai Peoples R China Fraunhofer IAIS St Augustin Germany City Univ London London England

For event analysis, the information from both before and after the event can be crucial in certain scenarios. By incorporating a contextualized perspective in event analysis, analysts can gain deeper insights from the events. We propose a contextualized visual analysis framework which enables the identification and interpretation of temporal patterns within and across multivariate events. The framework consists of a design of visual representation for multivariate event contexts, a data processing workflow to support the visualization, and a context-centered visual analysis system to facilitate the interactive exploration of temporal patterns. To demonstrate the applicability and effectiveness of our framework, we present case studies using real-world datasets from two different domains and an expert study conducted with experienced data analysts. (c) 2025 The Authors. Published by Elsevier B.v. on behalf of Zhejiang University and Zhejiang University Press Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： visual analytics Event analysis Contextualized analysis Interactive exploration visualization design

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v-Mail: 3D-Enabled Correspondence About Spatial data on (Almost) All Your Devices

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2024年第4期30卷 1853-1867页

作者： Nam, Jung Who Isenberg, Tobias Keefe, Daniel F. Univ Minnesota Minneapolis MN 55455 USA Univ Paris Saclay CNRS Inria LISN F-91190 Gif Sur Yvette France

We present v-Mail, a framework of cross-platform applications, interactive techniques, and communication protocols for improved multi-person correspondence about spatial 3D datasets. Inspired by the daily use of e-mail, v-Mail seeks to enable a similar style of rapid, multi-person communication accessible on any device;however, it aims to do this in the new context of spatial 3D communication, where limited access to 3D graphics hardware typically prevents such communication. The approach integrates visual data storytelling with data exploration, spatial annotations, and animated transitions. v-Mail "data stories" are exported in a standard video file format to establish a common baseline level of access on (almost) any device. The v-Mail framework also includes a series of complementary client applications and plugins that enable different degrees of story co-authoring and data exploration, adjusted automatically to match the capabilities of various devices. A lightweight, phone-based v-Mail app makes it possible to annotate data by adding captions to the video. These spatial annotations are then immediately accessible to team members running high-end 3D graphics visualization systems that also include a v-Mail client, implemented as a plugin. Results and evaluation from applying v-Mail to assist communication within an interdisciplinary science team studying Antarctic ice sheets confirm the utility of the asynchronous, cross-platform collaborative framework while also highlighting some current limitations and opportunities for future work.

关键词： data visualization Three-dimensional displays Annotations Spatial databases Collaboration Software Task analysis Communication human-computer interaction immersive analytics storytelling visualization of scientific 3D data

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Tinycubes: A modular technology for interactive visual analysis of historical and continuously updated spatiotemporal data

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2023年第1期143卷 378-391页

作者： Damasceno, Nilson L. Lage, Marcos Rocha, Antonio A. de A. Inst Comp UFF Ave Gal Milton Tavares de Souza S-N BR-24210346 Niteroi RJ Brazil

Technological advances allow sending data collected, like IoT data and Social Network data, immedi-ately to computational centers. However, state-of-the-art solutions for interactive visual exploration and analysis of spatiotemporal multidimensional using a single computer are focused on historical datasets. Also, most of these solutions utilize a monolithic architecture, with a restricted set of information extraction techniques and rigid internal data structures, which leads to the creation of forks to handle different usage needs. Tinycubes is a technology that supports the interactive exploration and visual analysis of spatiotemporal multidimensional continuously collected data in real-time combined with data from historical datasets, consistently producing up-to-date information using a single computer. The technology's core is a novel and efficient data structure based on data cubes that allow data insertion and removal on-the-fly. The Tinycubes Technology is modular, allowing the usage of different information extraction algorithms and efficient data storage methods. Our experiments indicate that Tinycubes will enable the exploration of newly generated data combined with historical data while presenting performance similar or superior to the state-of-the-art solutions that use a single computer.& COPY;2023 Elsevier B.v. All rights reserved.

关键词： visual data analysis visual analytics Exploratory visualization Spatiotemporal datacube Decision support system

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visual analysis of multi-subject association patterns in high-dimensional time-varying student performance data

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visual INFORMATICS 2025年第2期9卷

作者： Ji, Lianen Wang, Ziyi Qiu, Shirong Yang, Guang Zhang, Sufang China Univ Petr Dept Comp Sci & Technol Beijing 102249 Peoples R China China Univ Petr Beijing Key Lab Petr Data Min Beijing Peoples R China

Exploring the association patterns of student performance in depth can help administrators and teachers optimize the curriculum structure and teaching plans more specifically to improve teaching effectiveness in a college undergraduate major. However, these high-dimensional time-varying student performance data involve multiple associated subjects, such as student, course, and teacher, which exhibit complex interrelationships in academic semesters, knowledge categories, and student groups. This makes it challenging to conduct a comprehensive analysis of association patterns. To this end, we construct a visual analysis framework, called MAPvis, to support multi-method and multilevel interactive exploration of the association patterns in student performance. MAPvis consists of two stages: in the first stage, we extract students' learning patterns and further introduce mutual information to explore the distribution of learning patterns;in the second stage, various learning patterns and subject attributes are integrated based on a hierarchical apriori algorithm to achieve a multi-subject interactive exploration of the association patterns among students, courses, and teachers. Finally, we conduct a case study using real student performance data to verify the applicability and effectiveness of MAPvis. (c) 2025 The Authors. Published by Elsevier B.v. on behalf of Zhejiang University and Zhejiang University Press Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Learning pattern Course grades Multi-subject Association pattern visual analysis

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

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visual INFORMATICS 2025年第1期9卷 84-98页

作者： Wang, Bingyuan Shi, Qing Wang, Xiaohan Zhou, You Zeng, Wei Wang, Zeyu Hong Kong Univ Sci & Technol Guangzhou Guangzhou Peoples R China Hong Kong Univ Sci & Technol Hong Kong Peoples R China

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. (c) 2025 The Authors. Published by Elsevier B.v. on behalf of Zhejiang University and Zhejiang University Press Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Emotion visualization Word cloud Emotion analysis Literary text analysis Digital humanities

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v4RIN:visual analysis of regional industry network with domain knowledge

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visual Computing for Industry,Biomedicine,and Art 2024年第1期7卷 286-299页

作者： Wenli Xiong Chenjie Yu Chen Shi Yaxuan Zheng Xiping Wang Yanpeng Hu Hong Yin Chenhui Li Changbo Wang School of Computer Science and Technology East China Normal UniversityShanghai 200062China China Fortune Securities Co. LtdShanghai 200030China Shanghai Chinafortune Co. LtdShanghai 200030China Faculty of Economics and Management East China Normal UniversityShanghai 200062China

The regional industry network(RIN)is a type of financial network derived from industry networks that possess the capability to describe the connections between specific industries within a particular *** most investors and financial analysts lacking extensive experience,the decision-support information provided by industry networks may be too ***,RINs express more detailed and specific industry connections both within and out-side the *** RIN analysis is domain-specific and current financial network analysis tools are designed for gener-alized analytical tasks and cannot be directly applied to RINs,new visual analysis approaches are needed to enhance information exploration *** this study,we collaborated with domain experts and proposed v4RIN,an inter-active visualization analysis system that integrates predefined domain knowledge and data processing methods to support users in uploading custom *** multiple views in the system panel,users can comprehensively explore the structure,geographical distribution,and spatiotemporal variations of the *** case studies were con-ducted and a set of expert interviews with five domain experts to validate the usability and reliability of our system.

关键词： visualization visual analytics visualization in finance Regional industry analysis

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Uncovering temporal patterns in visualizations of high-dimensional data

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MACHINE LEARNING 2025年第2期114卷 1-27页

作者： Policar, Pavlin G. Zupan, Blaz Univ Ljubljana Fac Comp & Informat Sci Vecna Pot 113 Ljubljana 1000 Slovenia Baylor Coll Med Dept Educ Innovat & Technol 1 Baylor Plz Houston TX 77030 USA

With the increasing availability of high-dimensional data, analysts often rely on exploratory data analysis to understand complex data sets. A key approach to exploring such data is dimensionality reduction, which embeds high-dimensional data in two dimensions to enable visual exploration. However, popular embedding techniques, such as t-SNE and UMAP, typically assume that data points are independent. When this assumption is violated, as in time-series data, the resulting visualizations may fail to reveal important temporal patterns and trends. To address this, we propose a formal extension to existing dimensionality reduction methods that incorporates two temporal loss terms that explicitly highlight temporal progression in the embedded visualizations. Through a series of experiments on both synthetic and real-world datasets, we demonstrate that our approach effectively uncovers temporal patterns and improves the interpretability of the visualizations. Furthermore, the method improves temporal coherence while preserving the fidelity of the embeddings, providing a robust tool for dynamic data analysis.

关键词： Temporal-data visualization Dimensionality reduction data visualization

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A Survey of Cross-Modal visual Content Generation

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR vIDEO TECHNOLOGY 2024年第8期34卷 6814-6832页

作者： Nazarieh, Fatemeh Feng, Zhenhua Awais, Muhammad Wang, Wenwu Kittler, Josef Univ Surrey Sch Comp Sci & Elect Engn Guildford GU2 7XH England Univ Surrey Nat Inspired Comp & Engn NICE Res Grp Guildford GU2 7XH England Univ Surrey Ctr Vis Speech & Signal Proc Guildford GU2 7XH England

Cross-modal content generation has become very popular in recent years. To generate high-quality and realistic content, a variety of methods have been proposed. Among these approaches, visual content generation has attracted significant attention from academia and industry due to its vast potential in various applications. This survey provides an overview of recent advances in visual content generation conditioned on other modalities, such as text, audio, speech, and music, with a focus on their key contributions to the community. In addition, we summarize the existing publicly available datasets that can be used for training and benchmarking cross-modal visual content generation models. We provide an in-depth exploration of the datasets used for audio-to-visual content generation, filling a gap in the existing literature. various evaluation metrics are also introduced along with the datasets. Furthermore, we discuss the challenges and limitations encountered in the area, such as modality alignment and semantic coherence. Last, we outline possible future directions for synthesizing visual content from other modalities including the exploration of new modalities, and the development of multi-task multi-modal networks. This survey serves as a resource for researchers interested in quickly gaining insights into this burgeoning field.

关键词： visualization Surveys data models Task analysis Measurement Training Generative adversarial networks Generative models cross-modal visual content generation

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Failure mode analysis of Austria's first road-integrated photovoltaic system

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EPJ PHOTOvOLTAICS 2024年 15卷 42-42页

作者： Erber, Alexander Grasel, Bernhard Univ Appl Sci Tech Vienna Competence Field Renewable Energy Technol A-1210 Vienna Austria

The exploration of traffic areas as a novel photovoltaic integration opportunity within the traffic sector, specifically in road surfaces, has been demonstrated in various projects. Limited data and publications about the performance and failure modes of these innovative road-integrated modules highlights the need for a comprehensive failure analysis. This study focuses on first time assessing failure modes of road-integrated photovoltaic modules installed at Austria's first road-integrated Pv system in Teesdorf. A comprehensive failure mode analysis is conducted at the 100 m2 Pv parking place using a combination of quantitative and qualitative methods. These methods include regular visual inspections, I-v-curve measurements at both string- and module-levels (with a simplified STC correction), electroluminescence- and dark-I-v-curve measurements, and the use of monitoring data. The Pv parking place produced 10.2 MWh in its first operation year, 27.18% less than the estimated yield. visual inspections reveal various failure modes, including detachment of the module top layer, delamination, and broken module edges. In the analysed monitoring data continuous power losses are observed over the systems operation time. String-level power losses of up to 47.8% (mean: 33.5%) are calculated for the first year of operation. For the second year of operation the power losses reach a up to of 77.5% (mean: 56.2%). Cell cracks as the main cause of these power losses, attributed to vehicle loads, are identified through electroluminescence images. Out of 16 analysed strings with dark I-v-curve measurements three showed at least one bypass diode malfunctions. The combination of quantitative and qualitative methods identified multiple failure modes and their main causes. As a conclusion, the study highlights the challenges of integrating Pv modules into road surfaces, emphasizing the need for standardisation and quality assurance in the field of road-integrated Pv applications.

关键词： Road-integrated photovoltaics maintenance reliability failure mode analysis I-v curve measurements dark I-v curve electroluminescence

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