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JAAD Reviews 2025年 4卷 44-47页

作者： Stetkevich, S.A., MD Rasiah, S.S., MD Fahoury, A., MD Molenda, M., MD, FAAD, FACMS Anatomy Mapper Holland Ohio Department of Dermatology University of California Davis Sacramento California Department of Laboratory Medicine & Pathology University of Washington Seattle Washington Department of Internal Medicine The Ohio State University Columbus Ohio Division of Dermatology University of Toledo College of Medicine and Life Sciences Toledo Ohio Bravia Dermatology Holland Ohio

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

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VISUAL INFORMATICS 2025年第1期9卷 58-70页

作者： Zhou, Feng Hu, Hao Wang, Fengjie Zhu, Jiamin Gao, Wenwen Zhu, Min Sichuan Univ Coll Comp Sci Chengdu Peoples R China

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. (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： Ensemble visualization Isocontours hierarchical visualization Isovalue selection Spaghetti plots

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Scalable, interactive and hierarchical visualization of virus taxonomic data

Scalable, interactive and hierarchical visualization of viru...

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14th IEEE Workshop on Visual Analytics in Healthcare (VAHC)

作者： Balakavi, Kashyap Janga, Rushitha Shovon, Aluncdur Ralunan Dcmpscy, Don Lefkowitz, Elliot Kumar, Sidharth Univ Alabama Birmingham Dept Comp Sci Birmingham AL 35294 USA Univ Alabama Birmingham Dept Microbiol Birmingham AL 35294 USA

ISBN: (纸本)9798350330243

The International Committee on Taxonomy of Viruses (ICTV) (https://***) maintains a database of virus taxonomy, including records from 1971 up to the most recent release in 2022. Recent years have seen an increasing number of viruses, recording 11,273 distinct species in the latest report. Exploring this increasingly high number of species requires a custom data visualization approach that is both scalable and interactive. Our paper presents a structure-preserving, collapsible, node-link layout-based hierarchical visualization called the Visual Taxonomy Browser (https://***/taxonomy/visual-browser), for the virus taxonomy dataset. Developed in collaboration with micro-biologists, our visualization improves over the existing Taxonomy Browser (https://***/taxonomy) which is a stacked bar-based approach that lacks scalability and does not preserve the underlying topological structure of the taxonomy. The Visual Taxonomy Browser has been deployed on the ICTV website and has been serving virologists from across the world.

关键词： hierarchical hierarchical visualization linked-views virus Virus taxonomy

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Evaluation of hierarchical visualization for Large and Small Hierarchies 24

Evaluation of Hierarchical Visualization for Large and Small...

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24th International Conference Information Visualisation (IV)

作者： Macquisten, Alexander Smith, Adrian M. Fernstad, Sara Johansson Newcastle Univ Sch Comp Newcastle Upon Tyne Tyne & Wear England Unilever Unilever Res Colworth England

ISBN: (纸本)9781728191348

hierarchical visualization can provide a useful abstraction for exploring and analysing complex datasets. Many different methods for visualization of hierarchical data have been developed and determining which is the most suitable for a given dataset can be a challenge. Previous evaluations of hierarchical visualization methods typically focus on comparing hierarchical structures and less so on how well they represent underlying data. In this paper five different visualization methods for hierarchical data are evaluated: Treemaps, Icicle plots, Sunburst, Circular Treemaps and Bubble Treemaps. Each method was compared at two different sizes of hierarchical structure with questions comparing nodes based on their underlying data features, through size and colour. The initial results from this study indicate that for large hierarchies, Sunburst and Circular Treemaps are the best overall performers, while for small hierarchies, Treemap, Icicle plot and Circular Treemaps performed best.

关键词： hierarchical visualization usability evaluation information visualization

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A classification algorithm of 3D volumetric data for hierarchical visualization

A classification algorithm of 3D volumetric data for hierarc...

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Conference on Input/Output and Imaging Technologies

作者： Sato, M Liu, Y Takahashi, H Nakajima, M Tokyo Inst Technol Grad Sch Informat Sci & Engn Meguro Ku Tokyo 1528552 Japan

ISBN: (纸本)0819428760

This paper presents one part of our work on "hierarchical visualization." Here, we propose an efficient hierarchical structure for the visualization of 3D volumetric data, where for instance, data compression techniques are embedded into the hierarchical structure. The hierarchical structure consists of two layers. The first hierarchy roughly visualizes the whole lossy compressed data so that we can quickly understand and interpret the outline of the whole 3D volumetric dataset. This step allows users to choose the desired parts of the 3D volumetric data. The second hierarchy is used for scrutinizing the detail of the chosen parts using lossless compressed data. To implement the hierarchical structure we propose a partitioning algorithm for 3D volumetric data based on principal component analysis. With principal component analysis, the original 3D volumetric space can be divided into a number of 3D volumetric blocks such that each block contains similar data. Analyzing these specific blocks and taking advantage of an octree hierarchy, from the whole 3D volumetric dataset we can easily access only the parts which are required for display. The proposed partitioning algorithm should be very useful in reducing the amount of rendering, which means that we will need only to precisely render the blocks required for display, and not the whole 3D volumetric dataset.

关键词： 3D medical volume visualization hierarchical visualization partitioning algorithm octree

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Evaluating a Bilingual Text-Mining System With a Taxonomy of Key Words and hierarchical visualization for Understanding Learner-Generated Text

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JOURNAL OF EDUCATIONAL COMPUTING RESEARCH 2018年第3期56卷 369-395页

作者： Kong, Siu Cheung Li, Ping Song, Yanjie Educ Univ Hong Kong Dept Math & Informat Technol Hong Kong Hong Kong Peoples R China

This study evaluated a bilingual text-mining system, which incorporated a bilingual taxonomy of key words and provided hierarchical visualization, for understanding learner-generated text in the learning management systems through automatic identification and counting of matching key words. A class of 27 in-service teachers studied a course "e-Learning in primary mathematics" was asked to reflect "what is e-Learning" before and after the course. Their concept of "e-Learning" was investigated by counting the matching key words using the text-mining system and a content analysis of learner-generated text using a rubric, respectively. The correlations of the results using these two methods were .823 and .840 in the preteaching and postteaching reflections. This text-mining system has the potential as a supporting tool for teachers to gain a general understanding of learner-generated text using the hierarchical visualization for supporting pedagogical decision-making, which can be applied to massive open online courses with a large enrolment of learners.

关键词： bilingual text-mining system bilingual taxonomy of key words evaluation hierarchical visualization learner-generated text

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HintVis: The hierarchical visualization of Network Traffic Data

HintVis: The Hierarchical Visualization of Network Traffic D...

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International Conference on Virtual Reality and visualization (ICVRV)

作者： Zhang, Hengyuan Chen, Xiaowu Hu, Haifeng Beihang Univ Sch Comp Sci & Engn State Key Lab Virtual Real Technol & Syst Beijing Peoples R China

ISBN: (纸本)9780769551500

The network traffic data is interpreted differently by people in different sectors. This paper proposes a framework for hierarchically visualizing the network traffic data, and customizes a set of the classic approaches or algorithms to produce visualizations in different levels. Based on the framework, we developed a prototype system HintVis to support analyzing network traffic data in different levels by constructing layered semantic network traffic objects and producing hierarchical visualizations. The usability of HintVis is demonstrated by visualizing packets going through the gateway in a LAN. Depending on the hierarchical visualizations, analysts are able to semantically navigate in the network traffic data and concentrate on what they need.

关键词： Network Traffic hierarchical visualization User Interface

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Evaluating boundary conditions and hierarchical visualization in CBIR 23

Evaluating boundary conditions and hierarchical visualizatio...

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23rd International Conference on the Information Visualisation (IV) - Incorporating Biomedical visualization, Learning Analytics and Geometric Modelling and Imaging

作者： Real, Luiz Gustavo S. Bueno, Renato Ribeiro, Marcela X. Sao Paulo State Univ IT Dept Aracatuba Brazil Univ Fed Sao Carlos Dept Comp Sao Carlos Brazil

ISBN: (纸本)9781728128382

Multiple descriptors are employed to represent images in Content-Based Image Retrieval (CBIR) systems. Each descriptor consists of a feature extractor associated with a distance function. An extractor is generally suitable for representing a specific subset of images on a database. The boundary conditions are information used to detect this subset. The use of visualization in CBIR helps to represent the similarity relationship between images, improving the user's understanding of the CBIR system, allowing them to modify parameters to obtain better results. It is proven that the use of multiple descriptors with boundary conditions tends to improve the precision of CBIR queries, but there is no data on the impact that the technique generates on visualization. This paper uses multiple descriptors with boundary conditions to generate a Neighbor Joining similarity tree-based view. Tests have shown that the quality of the visualization may be related to the quality of the query result. In the context of similarity trees, the use of multiple descriptors contributed to a better-organized visualization.

关键词： CBIR hierarchical visualization similarity tree neighbor joining multiple descriptors boundary conditions

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Exploring OLAP Aggregates with hierarchical visualization Techniques 07

Exploring OLAP Aggregates with Hierarchical Visualization Te...

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22nd ACM Symposium on Applied Computing

作者： Mansmann, Svetlana Scholl, Marc H. Univ Konstanz D-78457 Constance Germany

ISBN: (纸本)9781595934802

This paper presents an approach to exploring multidimensional data cubes with hierarchical visualization techniques. Analysts interact with data in a predominantly "drill-down" fashion, i.e. from coarse grained aggregates towards the desired level of detail. We suggest that visual hierarchies are adequate for mapping the multiscale nature of decomposition as they preserve the results of the entire interaction. We introduce a class of visual structures called Enhanced Decomposition Tree. Every tree level is created by a disaggregation step along a chosen dimension, the nodes contain the corresponding sub-aggregates arranged into a chart and the edges axe labeled with their dimensional values. Various layouts axe proposed to account for different analysis tasks. Data cubes are queried using a schema-based browser which presents dimensions by the hierarchies of their granularity levels, thus offering an efficient way of generating hierarchical visualizations. Multiple data cubes may be explored in parallel along their shared dimensions. The power of our approach is exemplified using a real-world study from the domain of academic administration.

关键词： Multidimensional Data OLAP hierarchical visualization

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HintVis:The hierarchical visualization of Network Traffic Data

HintVis:The Hierarchical Visualization of Network Traffic Da...

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2013中国虚拟现实大会暨ICVRV'2013

作者： Hengyuan Zhang Xiaowu Chen Haifeng Hu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University BeijingChina

The network traffic data is interpreted differently by people in different *** paper proposes a framework for hierarchically visualizing the network traffic data,and customizes a set of the classic approaches or algorithms to produce visualizations in different *** on the framework,we developed a prototype system HintVis to support analyzing network traffic data in different levels by constructing layered semantic network traffic objects and producing hierarchical *** usability of HintVis is demonstrated by visualizing packets going through the gateway in a *** on the hierarchical visualizations,analysts are able to semantically navigate in the network traffic data and concentrate on what they need.

关键词： Network Traffic hierarchical visualization User Interface

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