StoryFacets: A design study on storytelling with visualizations for collaborative data analysis

Author:

Park Deokgun1ORCID,Suhail Mohamed2,Zheng Minsheng3,Dunne Cody4,Ragan Eric5,Elmqvist Niklas6ORCID

Affiliation:

1. University of Texas at Arlington, Arlington, TX, USA

2. Texas A&M University, College Station, TX, USA

3. OCAD University, TO, CA

4. Northeastern University, Boston, MA, USA

5. University of Florida, Gainesville, FL, USA

6. University of Maryland, College Park, MD, USA

Abstract

Tracking the sensemaking process is a well-established practice in many data analysis tools, and many visualization tools facilitate overview and recall during and after exploration. However, the resulting communication materials such as presentations or infographics often omit provenance information for the sake of simplicity. This unfortunately limits later viewers from engaging in further collaborative sensemaking or discussion about the analysis. We present a design study where we introduced visual provenance and analytics to urban transportation planning. Maintaining the provenance of all analyses was critical to support collaborative sensemaking among the many and diverse stakeholders. Our system, STORYFACETS, exposes several different views of the same analysis session, each view designed for a specific audience: (1) the trail view provides a data flow canvas that supports in-depth exploration + provenance (expert analysts); (2) the dashboard view organizes visualizations and other content into a space-filling layout to support high-level analysis (managers); and (3) the slideshow view supports linear storytelling via interactive step-by-step presentations (laypersons). Views are linked so that when one is changed, provenance is maintained. Visual provenance is available on demand to support iterative sensemaking for any team member.

Funder

Defense Advanced Research Projects Agency

National Science Foundation

Publisher

SAGE Publications

Subject

Computer Vision and Pattern Recognition

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Imagining Just and Sustainable Food Futures: Using Interactive Visualizations to Explore the Possible Land Uses and Food Systems Approaches in Revelstoke, Canada;Land;2024-08-24

2. Multi-Temporal Analysis of Urban Heat Island Phenomenon Distribution in the Special Region of Yogyakarta (2018-2022) Using ArcGIS Story Map;IOP Conference Series: Earth and Environmental Science;2024-06-01

3. How Do Analysts Understand and Verify AI-Assisted Data Analyses?;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

4. Graph-Neural-Network-Based User Intent Understanding for Visual Analytics;2024 IEEE 17th Pacific Visualization Conference (PacificVis);2024-04-23

5. Data Visualization in Transforming Raw Data into Compelling Visual Narratives;2024 International Conference on Trends in Quantum Computing and Emerging Business Technologies;2024-03-22

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3