• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

面向问题驱动科学可视化的活动中心领域特征描述。

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization.

出版信息

IEEE Trans Vis Comput Graph. 2018 Jan;24(1):913-922. doi: 10.1109/TVCG.2017.2744459. Epub 2017 Aug 29.

DOI:10.1109/TVCG.2017.2744459
PMID:28866550
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5796424/
Abstract

Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage-and its evaluation-of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature.

摘要

尽管文献中存在以更高层次方法论框架形式出现的可视化设计模型,但这些模型并未为领域特征描述步骤提供明确的方法处方。本工作提出了一个针对问题驱动可视化应用设计的需求工程的框架和端到端模型。该框架和模型基于以活动为中心的设计范例,这是以人为中心的设计的增强。所提出的以活动为中心的方法侧重于用户任务和活动,并允许在需求工程过程与抽象阶段及其对现有、更高层次的可视化设计模型的评估之间建立明确的联系。与现有的可视化设计模型不同,所得到的模型:根据用户活动为可视化分配价值;在用户数据之前对用户任务进行排序;将需求划分为与活动相关的功能、非功能特性和约束;并将用户工作流明确纳入需求过程。该模型的另一个优点是明确将功能规范(这是本工作从软件工程文献中采用的概念)集成到可视化设计嵌套模型中。使用两组跨学科项目进行的定量评估支持了以活动为中心的模型的优点。其结果是为问题驱动的数据可视化的可视化设计的领域特征描述步骤提供了一个实用的路线图。遵循此领域特征描述模型可以帮助消除在可视化设计文献中多次出现的一些陷阱。

相似文献

1
Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization.面向问题驱动科学可视化的活动中心领域特征描述。
IEEE Trans Vis Comput Graph. 2018 Jan;24(1):913-922. doi: 10.1109/TVCG.2017.2744459. Epub 2017 Aug 29.
2
Creative user-centered visualization design for energy analysts and modelers.面向能源分析师和建模师的创新用户为中心的可视化设计。
IEEE Trans Vis Comput Graph. 2013 Dec;19(12):2516-25. doi: 10.1109/TVCG.2013.145.
3
A design space of visualization tasks.可视化任务的设计空间。
IEEE Trans Vis Comput Graph. 2013 Dec;19(12):2366-75. doi: 10.1109/TVCG.2013.120.
4
ManyVis: multiple applications in an integrated visualization environment.ManyVis:集成可视化环境中的多个应用程序。
IEEE Trans Vis Comput Graph. 2013 Dec;19(12):2878-85. doi: 10.1109/TVCG.2013.174.
5
An insight-based longitudinal study of visual analytics.一项基于洞察的视觉分析纵向研究。
IEEE Trans Vis Comput Graph. 2006 Nov-Dec;12(6):1511-22. doi: 10.1109/TVCG.2006.85.
6
Software design patterns for information visualization.信息可视化的软件设计模式。
IEEE Trans Vis Comput Graph. 2006 Sep-Oct;12(5):853-60. doi: 10.1109/TVCG.2006.178.
7
Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing.扩展以用户为中心的可解释人工智能的嵌套模型:基于图神经网络的药物重定位设计研究
IEEE Trans Vis Comput Graph. 2023 Jan;29(1):1266-1276. doi: 10.1109/TVCG.2022.3209435. Epub 2022 Dec 20.
8
Opening the Black Box: Strategies for Increased User Involvement in Existing Algorithm Implementations.打开黑匣子:提高用户对现有算法实现参与度的策略
IEEE Trans Vis Comput Graph. 2014 Dec;20(12):1643-52. doi: 10.1109/TVCG.2014.2346578.
9
User-centered requirements engineering in health information systems: a study in the hemophilia field.以用户为中心的健康信息系统需求工程:血友病领域的研究。
Comput Methods Programs Biomed. 2012 Jun;106(3):160-74. doi: 10.1016/j.cmpb.2010.10.007. Epub 2010 Nov 13.
10
Human factors in visualization research.可视化研究中的人为因素。
IEEE Trans Vis Comput Graph. 2004 Jan-Feb;10(1):72-84. doi: 10.1109/TVCG.2004.1260759.

引用本文的文献

1
Empowering Communities: Tailored Pandemic Data Visualization for Varied Tasks and Users.赋能社区:针对不同任务和用户的定制化疫情数据可视化
IEEE Comput Graph Appl. 2025 Jan-Feb;45(1):130-138. doi: 10.1109/MCG.2024.3509293.
2
Explainable Spatial Clustering: Leveraging Spatial Data in Radiation Oncology.可解释的空间聚类:利用放射肿瘤学中的空间数据
IEEE Vis Conf. 2020 Oct;2020:281-285. doi: 10.1109/vis47514.2020.00063.
3
DITTO: A Visual Digital Twin for Interventions and Temporal Treatment Outcomes in Head and Neck Cancer.DITTO:头颈癌干预与时间性治疗结果的可视化数字孪生模型

本文引用的文献

1
Echo: A Large Display Interactive Visualization of ICU Data for Effective Care HandOffs.回声:用于有效护理交接的重症监护室数据大型显示交互式可视化工具。
IEEE Workshop Vis Anal Healthc. 2017 Oct;2017:47-54. doi: 10.1109/VAHC.2017.8387500.
2
StickySchedule: An Interactive Multi-user Application for Conference Scheduling on Large-scale Shared Displays.粘性日程安排:一种用于在大型共享显示屏上进行会议日程安排的交互式多用户应用程序。
Pervasive Disp 2017 (2017). 2017 Jun;2017. doi: 10.1145/3078810.3078817.
3
PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.
IEEE Trans Vis Comput Graph. 2025 Jan;31(1):65-75. doi: 10.1109/TVCG.2024.3456160. Epub 2024 Nov 25.
4
Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining.玫瑰有刺:通过可视化分析和序列规则挖掘了解肿瘤学护理提供的弊端。
IEEE Trans Vis Comput Graph. 2024 Jan;30(1):1227-1237. doi: 10.1109/TVCG.2023.3326939. Epub 2023 Dec 25.
5
DASS Good: Explainable Data Mining of Spatial Cohort Data.DASS Good:空间队列数据的可解释数据挖掘
Comput Graph Forum. 2023 Jun;42(3):283-295. doi: 10.1111/cgf.14830. Epub 2023 Jun 27.
6
Alveolus analysis: a web browser-based tool to analyze lung intravital microscopy.肺泡分析:一种基于网络浏览器的分析肺活体显微镜的工具。
BMC Pulm Med. 2022 Dec 17;22(1):480. doi: 10.1186/s12890-022-02274-7.
7
Visual Analysis and Detection of Contrails in Aircraft Engine Simulations.飞机发动机模拟中的凝结尾迹的视觉分析与检测。
IEEE Trans Vis Comput Graph. 2023 Jan;29(1):798-808. doi: 10.1109/TVCG.2022.3209356. Epub 2022 Dec 16.
8
A Tale of Two Centers: Visual Exploration of Health Disparities in Cancer Care.两个中心的故事:癌症护理中健康差异的可视化探索
IEEE Pac Vis Symp. 2022 Apr;2022:101-110. doi: 10.1109/pacificvis53943.2022.00019. Epub 2022 Jun 8.
9
THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy.THALIS:癌症治疗中纵向症状的人机分析。
IEEE Trans Vis Comput Graph. 2022 Jan;28(1):151-161. doi: 10.1109/TVCG.2021.3114810. Epub 2021 Dec 24.
10
DarkSky Halos: Use-Based Exploration of Dark Matter Formation Data in a Hybrid Immersive Virtual Environment.暗物质晕圈:混合沉浸式虚拟环境中基于用途的暗物质形成数据探索
Front Robot AI. 2019 Mar;6(11). doi: 10.3389/frobt.2019.00011. Epub 2019 Mar 4.
PRODIGEN:可视化状态和时间空间中随机基因调控网络的概率格局。
BMC Bioinformatics. 2017 Feb 15;18(Suppl 2):24. doi: 10.1186/s12859-016-1447-1.
4
Large-Scale Overlays and Trends: Visually Mining, Panning and Zooming the Observable Universe.大规模叠加与趋势:可视化挖掘、平移和缩放可观测宇宙
IEEE Trans Vis Comput Graph. 2014 Jul;20(7):1048-61. doi: 10.1109/TVCG.2014.2312008.
5
Design Study Methodology: Reflections from the Trenches and the Stacks.设计研究方法:来自实践与理论的思考
IEEE Trans Vis Comput Graph. 2012 Dec;18(12):2431-40. doi: 10.1109/TVCG.2012.213.
6
Design Activity Framework for Visualization Design.可视化设计的设计活动框架。
IEEE Trans Vis Comput Graph. 2014 Dec;20(12):2191-200. doi: 10.1109/TVCG.2014.2346331.
7
Moving beyond sequential design: Reflections on a rich multi-channel approach to data visualization.超越序列设计:对丰富的多通道数据可视化方法的反思。
IEEE Trans Vis Comput Graph. 2014 Dec;20(12):2171-80. doi: 10.1109/TVCG.2014.2346323.
8
BactoGeNIE: a large-scale comparative genome visualization for big displays.BactoGeNIE:用于大型显示屏的大规模比较基因组可视化工具。
BMC Bioinformatics. 2015;16 Suppl 11(Suppl 11):S6. doi: 10.1186/1471-2105-16-S11-S6. Epub 2015 Aug 13.
9
MOSBIE: a tool for comparison and analysis of rule-based biochemical models.MOSBIE:一种用于基于规则的生化模型比较与分析的工具。
BMC Bioinformatics. 2014 Sep 25;15(1):316. doi: 10.1186/1471-2105-15-316.
10
FixingTIM: interactive exploration of sequence and structural data to identify functional mutations in protein families.FixingTIM:对序列和结构数据进行交互式探索,以识别蛋白质家族中的功能突变。
BMC Proc. 2014 Aug 28;8(Suppl 2 Proceedings of the 3rd Annual Symposium on Biologica):S3. doi: 10.1186/1753-6561-8-S2-S3. eCollection 2014.