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VERTIGo: A visual Platform for Querying and Exploring Large Multilayer Networks

IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2022年第3期28卷 1634-1647页

作者： Cuenca, Erick Sallaberry, Arnaud Ienco, Dino Poncelet, Pascal Yachay Tech Univ Urcuqui 100650 Ecuador Univ Montpellier Paul Valery Univ Montpellier LIRMM AMIS Res Grp F-34000 Montpellier France CNRS F-75016 Paris France INRAE F-69100 Villeurbanne France Univ Montpellier LIRMM F-34000 Montpellier France

Many real world data can be modeled by a graph with a set of nodes interconnected to each other by multiple relationships. Such a rich graph is called multilayer graph or network. Providing useful visualization tools to support the query process for such graphs is challenging. Although many approaches have addressed the visual query construction, few efforts have been done to provide a contextualized exploration of query results and suggestion strategies to refine the original query. This is due to several issues such as i) the size of the graphs ii) the large number of retrieved results and iii) the way they can be organized to facilitate their exploration. In this article, we present VERTIGo, a novel visual platform to query, explore and support the analysis of large multilayer graphs. VERTIGo provides coordinated views to navigate and explore the large set of retrieved results at different granularity levels. In addition, the proposed system supports the refinement of the query by visual suggestions to guide the user through the exploration process. Two examples and a user study demonstrate how VERTIGo can be used to perform visual analysis (query, exploration, and suggestion) on real world multilayer networks.

关键词： visualization Nonhomogeneous media Task analysis Social networking (online) Query processing databases Standards visual querying system visual pattern suggestion multilayer networks

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Engineering Annotations to Support Analytical Provenance in visual exploration Processes 22nd

Engineering Annotations to Support Analytical Provenance in ...

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22nd International conference on Web Engineering (ICWE)

作者： Tikat, Maroua Menin, Aline Buffa, Michel Winckler, Marco Univ Cote dAzur CNRS INRIA I3SSPARKS Wimm Team Nice France

ISBN: (纸本)9783031099175;9783031099168

This paper focuses on the fundamental role played by annotations to support provenance analysis in visual exploration processes of large datasets. Particularly, we investigate the use of annotations during the visual exploration of semantic datasets assisted by chained visualization techniques. In this paper, we identify three potential uses of annotations: (i) documenting findings (including errors in the dataset), (ii) supporting collaborative reasoning among teammates, and (iii) analysing provenance during the exploratory process. To demonstrate the feasibility of our approach, we implemented it as a tool support, while illustrating its usage and effectiveness through a series of use case scenarios. We identify the attributes and meta-data that describe the dependencies between annotations and visual representations, and we illustrate these dependencies through a domain-specific model.

关键词： Annotations Provenance analysis visual exploration Information visualization data quality

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visualization Atlases: Explaining and Exploring Complex Topics through data, visualization, and Narration

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IEEE TRANSACTIONS ON visualIZATION AND COMPUTER GRAPHICS 2025年第1期31卷 437-447页

作者： Wang, Jinrui Shu, Xinhuan Bach, Benjamin Hinrichs, Uta Univ Edinburgh Edinburgh Midlothian Scotland Newcastle Univ Newcastle NSW Australia INRIA Paris France

This paper defines, analyzes, and discusses the emerging genre of visualization atlases. We currently witness an increase in web-based, data-driven initiatives that call themselves "atlases" while explaining complex, contemporary issues through data and visualizations: climate change, sustainability, AI, or cultural discoveries. To understand this emerging genre and inform their design, study, and authoring support, we conducted a systematic analysis of 33 visualization atlases and semi-structured interviews with eight visualization atlas creators. Based on our results, we contribute (1) a definition of a visualization atlas as a compendium of (web) pages aimed at explaining and supporting exploration of data about a dedicated topic through data, visualizations and narration. (2) a set of design patterns of 8 design dimensions, (3) insights into the atlas creation from interviews and (4) the definition of 5 visualization atlas genres. We found that visualization atlases are unique in the way they combine i) exploratory visualization, ii) narrative elements from data-driven storytelling and iii) structured navigation mechanisms. They target a wide range of audiences with different levels of domain knowledge, acting as tools for study, communication, and discovery. We conclude with a discussion of current design practices and emerging questions around the ethics and potential real-world impact of visualization atlases, aimed to inform the design and study of visualization atlases.

关键词： visualization Atlases Information visualization data-driven Storytelling

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Interactive Parallel Coordinates visualization Platform for Survey data 5

Interactive Parallel Coordinates Visualization Platform for ...

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5th International conference on Artificial Intelligence and data Sciences, AiDAS 2024

作者： Bakri, M. Afrina, N.A. Hamiz, M. UiTM Cawangan Melaka Kampus Jasin Melaka Malaysia

ISBN: (纸本)9798331528553

Survey data often encompasses many variables, making it challenging to identify complex relationships. Parallel coordinates visualization offers a powerful solution for exploring these relationships. We propose a web-based application that leverages parallel coordinates to enhance survey data analysis. This user-friendly tool overcomes limitations of traditional methods by enabling interactive exploration of high-dimensional data. The application adheres to the waterfall model for development, ensuring thorough testing and achieving a high System Usability Scale (SUS) score of 86.8%. By providing deeper insights through visual exploration, this application empowers researchers to make more informed decisions. However, well-structured and pre-processed data remains essential for accurate visualizations. Overall, our web-based application with parallel coordinates visualization offers an innovative and efficient approach to survey data analysis. © 2024 IEEE.

关键词： data accuracy

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Creative Insights into Motion: Enhancing Human Activity Understanding with 3D data visualization and Annotation 16

Creative Insights into Motion: Enhancing Human Activity Unde...

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16th ACM conference on Creativity and Cognition (C and C)

作者： Browen, Isaac Camarillo-Abad, Hector M. Cibrian, Franceli L. Di Qi, Trudi Chapman Univ Fowler Sch Engn Orange CA 92866 USA Chapman Univ Schmid Coll Sci & Technol Orange CA USA

ISBN: (纸本)9798400704857

This paper presents a novel 3D system for human motion analysis - Motion data visualization and Annotation (MoViAn). Designed to provide a comprehensive visual representation of 3D human motion data, MoViAn incorporates detailed visualization of gaze direction, hand movements, and object interactions, alongside an interactive interface for efficient data annotation. A user study involving eight participants indicates that MoViAn enables users to thoroughly explore and annotate human motion data, with System Usability Scale (SUS) results demonstrating a satisfactory usability level. The contribution of this paper lies in the development of an interactive and usable data analytics tool aimed at deepening the understanding of human behaviors and intentions in various creative, cognitive, and physical activities that ultimately can facilitate the design and creation of innovative tools that enhance human life in multiple domains.

关键词： Human motion analysis 3D visualization data exploration data annotation User interface Usability evaluation

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visual Analytics of Streaming data in Concept Drift Detection 11

Visual Analytics of Streaming Data in Concept Drift Detectio...

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11th International conference on Electrical, Electronic and Computing Engineering, IcETRAN 2024

作者： Ilic, Aleksandra Stojnev Stojanovic, Dragan University of Nis Faculty of Electronic engineering Dept. Computer Science Nis Serbia

ISBN: (纸本)9798350386998

Recent developments in sensor technology have enabled real-time data acquisition, high-frequency and multimodal data capturing thus underlying the need for monitoring physical or operational conditions in various aspects of the data. High dimensionality and volume of the data poses significant statistical challenges creating a need for accurate concept drift detection and prompt responses, a task that can be performed either by an algorithm or by human expert. visual analytics plays a crucial role in concept drift detection by enabling analysts to visually explore, analyze, and interpret complex data streams, facilitating real-time monitoring, decision-making, and communication with stakeholders. This paper examines the usability of radar graphs for concept drift exploration, as well as their usage in other steps of analysis. For the purpose of demonstration, a pipeline for real-time health data analysis is presented and steps are visualized using radar graphs. © 2024 IEEE.

关键词： visual analytics

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Construction of quantitative prediction model of metal mineral resources based on big data mining 3

Construction of quantitative prediction model of metal miner...

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3rd International conference on Computer Technology, Information Engineering, and Electron Materials, CTIEEM 2023

作者： Fu, Taiyu Chongqing Test Center of Geology and Minerals Chongqing400042 China

ISBN: (纸本)9781510672925

With the vigorous development of big data technology, the application of data mining program to complete quantitative prediction and evaluation of mineral resources has become a new trend in the development of mineral exploration industry and an important way to promote the digital transformation of traditional prospecting technology. In this regard, this paper will combine geological theory analysis and data mining algorithm to build a quantitative prediction model of metal mineral resources, realize the analysis, processing and visual interpretation of deep geoscience data, and provide necessary data science support for actual mineral exploration. The prediction model takes the machine learning algorithm as the core, and relies on the class libraries such as Numpy, Pandas and Sklearn in Python environment to complete the development and training. Combined with the spatial attribute database in ArcGIS, the prediction elements and importance evaluation indicators are obtained, and the final quantitative prediction results are obtained, and the result evaluation is completed. Practice has proved that the quantitative prediction model of mineral resources based on machine learning algorithm has high prediction accuracy, and the visual results can clearly show the high probability mineral resources areas, which has high practical promotion value. © 2024 SPIE.

关键词： Minerals

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Automated data exploration and analysis 41st

Automated Data Exploration and Analysis

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41st Computer Graphics International conference, CGI 2024

作者： Wu, Tong Wang, Song Peng, Xin School of Computer Science and Technology Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9783031820205

The paper presents a recommender algorithm for visual analysis based on data field Schema and Aggregation, and developed an automated data analysis solution recommendation system (AutoEDA) in conjunction with the Exploratory data analysis process (EDA). To address the issue of field type recognition, we designed a dynamic field recognition framework combining four classification models to automatically classify data field types. For the evaluation of analysis strategies, we proposed an analysis strategy evaluation method based on the Chart Attribute Length for designing custom search strategies and defining chart matching rules. Finally, through interactive visual backtracking and the functionality of modifying and tracing analysis solutions, we collaborated with data analysts of varying experience levels, and validated the effectiveness and feasibility of the proposed solution with structured data from publicly available websites. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： data aggregation

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Weedle: Composable Dashboard for data-Centric NLP in Computational Notebooks

Weedle: Composable Dashboard for Data-Centric NLP in Computa...

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32nd World Wide Web conference (WWW)

作者： Kwon, Nahyun Kim, Hannah Rahman, Sajjadur Zhang, Dan Hruschka, Estevam Texas A&M Univ College Stn TX 77834 USA Megagon Labs Mountain View CA USA

ISBN: (纸本)9781450394161

data-centric NLP is a highly iterative process requiring careful exploration of text data throughout entire model development life-cycle. Unfortunately, existing data exploration tools are not suitable to support data-centric NLP because of workfow discontinuity and lack of support for unstructured text. In response, we propose Weedle, a seamless and customizable exploratory text analysis system for data-centric NLP. Weedle is equipped with built-in text transformation operations and a suite of visual analysis features. With its widget, users can compose customizable dashboards interactively and programmatically in computational notebooks.

关键词： exploratory data analysis computational notebooks

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Motion Blur Impact on Measurement in Autonomous Inspection 20

Motion Blur Impact on Measurement in Autonomous Inspection

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20th IEEE/ASME International conference on Mechatronic and Embedded Systems and Applications (MESA)

作者： Jose, Nahuel Marchello, Gabriele Cannella, Ferdinando Italian Inst Technol Genoa Italy

ISBN: (纸本)9798331516246;9798331516239

This paper investigates the application of mobile robotic platforms for visual data capture in infrastructure inspection tasks. The captured data offer significant value for both manual and automated inspection processes. It can produce detailed visual information for human inspectors and serve as input for automated systems to detect anomalies or assist inspectors through computer-aided analysis. Additionally, these data can be integrated into the robot navigation system for real-time path optimisation. A critical challenge in optimising data capture is highlighted: balancing the desired precision with the time invested in inspections. The study explores this tradeoff by analysing the impact of motion blur on measurement errors. Capturing high-quality images with minimal motion blur necessitates slower inspection speeds. The findings suggest that for extensive inspection areas, prioritising mid-range object distances can optimise data capture, as errors increase at a slower pace at these distances compared to closer or farther ranges. This research paves the way for further advancements. Future areas of exploration include evaluating noise reduction techniques, incorporating real-world complexities into testing environments, and investigating the impact of capture speed on machine learning algorithms.

关键词： Image quality assessment video quality assessment monitoring of structures visual inspection motion blur assessment structural health monitoring (SHM)

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