Identifying the Relationships Between the Visualization Context and Representation Components to Enable Recommendations for Designing New Visualizations

Alma Cantu, O. Grisvard, Thierry Duval, G. Coppin
{"title":"Identifying the Relationships Between the Visualization Context and Representation Components to Enable Recommendations for Designing New Visualizations","authors":"Alma Cantu, O. Grisvard, Thierry Duval, G. Coppin","doi":"10.1109/iV.2017.55","DOIUrl":null,"url":null,"abstract":"In this paper we address the question of the relationships between visualization challenges and the representation components that provide solutions to these challenges. Our approach involves extracting such relationships through an identification of the context and the components of a significant number of representations and a comparison of the result to existing theoretical studies. To make such an identification possible, we rely on a characterization of the representation context based on a thoughtful aggregation of existing characterizations of the data type, the tasks and the context of use of the representations. We illustrate our approach on a use-case with examples of a relationships extraction and of a comparison of that relationships to the theory. We believe that the establishment of such relationships makes it possible to understand the mechanisms behind the representations, in order to build a representation design recommendation tool. Such a tool will enable us to recommend the components to use in a representation, given a visualization challenge to address.","PeriodicalId":410876,"journal":{"name":"2017 21st International Conference Information Visualisation (IV)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 21st International Conference Information Visualisation (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iV.2017.55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

In this paper we address the question of the relationships between visualization challenges and the representation components that provide solutions to these challenges. Our approach involves extracting such relationships through an identification of the context and the components of a significant number of representations and a comparison of the result to existing theoretical studies. To make such an identification possible, we rely on a characterization of the representation context based on a thoughtful aggregation of existing characterizations of the data type, the tasks and the context of use of the representations. We illustrate our approach on a use-case with examples of a relationships extraction and of a comparison of that relationships to the theory. We believe that the establishment of such relationships makes it possible to understand the mechanisms behind the representations, in order to build a representation design recommendation tool. Such a tool will enable us to recommend the components to use in a representation, given a visualization challenge to address.
识别可视化上下文和表示组件之间的关系,以便为设计新的可视化提供建议
在本文中,我们讨论了可视化挑战和为这些挑战提供解决方案的表示组件之间的关系问题。我们的方法包括通过识别上下文和大量表征的组成部分来提取这种关系,并将结果与现有理论研究进行比较。为了使这种识别成为可能,我们依赖于基于数据类型、任务和使用表示的上下文的现有特征的深思熟虑的聚合的表示上下文的特征。我们在一个用例上用关系提取和关系与理论比较的例子来说明我们的方法。我们相信这种关系的建立使得理解表示背后的机制成为可能,从而构建一个表示设计推荐工具。这样的工具将使我们能够在给定要解决的可视化挑战的情况下,推荐在表示中使用的组件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信