Exploring Cognitive Strategies for Integrating Multiple-View Visualizations

Author:

Ryu Young Sam1,Yost Beth2,Convertino Gregorio2,Chen Jian2,North Chris2

Affiliation:

1. Grado Department of Industrial and Systems Engineering

2. Department of Computer Science Virginia Polytechnic Institute and State University Blacksburg, Virginia

Abstract

Visualizing information is useful for finding patterns in complex data sets, but little research has been done on how people understand multiple-view visualizations (multiple visualizations presented simultaneously). A controlled experiment was performed using different combinations of visualizations and different task types as independent variables, and qualitative and quantitative data were collected. To collect the data psychological tests, logs of the participants' interaction, eye-tracking equipment, and video recordings were used. This paper reports a portion of the results from this experiment. Main findings include that, contrary to what was suggested in previous literature, the time cost for switching between different types of visualizations (context switching) may not be significant, and that displaying the data using the same type of visualization may cause interference. Orthogonal combinations appear to aid users in finding and recognizing patterns, and focusing attention and analogical reasoning on spatial relationships may be important cognitive abilities for the given tasks.

Publisher

SAGE Publications

Subject

General Medicine,General Chemistry

Cited by 10 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. Hybrid User Interfaces for Multiple Views: why designer intuition is not enough;2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct);2023-10-16

2. Toward Systematic Design Considerations of Organizing Multiple Views;2022 IEEE Visualization and Visual Analytics (VIS);2022-10

3. Cueing effects of colour on attention management in multiple-view visualisations: evidence from eye-tracking by using a dual-task paradigm;Behaviour & Information Technology;2021-03-01

4. Toward Rigorous Parameterization of Underconstrained Neural Network Models Through Interactive Visualization and Steering of Connectivity Generation;Frontiers in Neuroinformatics;2018-06-01

5. ENIGMA-Viewer;Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics;2016-10-02

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