Interactive Visualization for Interdisciplinary Research

Naomi Keena, Mohamed Aly Etman, Joshua Draper, P. Pinheiro, A. Dyson
{"title":"Interactive Visualization for Interdisciplinary Research","authors":"Naomi Keena, Mohamed Aly Etman, Joshua Draper, P. Pinheiro, A. Dyson","doi":"10.2352/ISSN.2470-1173.2016.1.VDA-491","DOIUrl":null,"url":null,"abstract":"Studies show that many multi-scalar research problems cannot easily be addressed from the confines of individual disciplines for they require the participation of many experts, each viewing the problem from their distinctive disciplinary perspective. The bringing together of disparate experts or fields of expertise is known as interdisciplinary research. The benefit of such an approach is that discourse and collaboration among experts in distinct fields can generate new insights to the research problem at hand. With this approach comes large amounts of multivariate data and understanding the possible relationships between variables and their corresponding relevance to the problem is in itself a challenge. One of the most valuable means through which to comprehend big data and make it more approachable, is through data visualization. This paper presents a trial to encompass an interdisciplinary research centers collaborators, experiments, and results, and represent them simultaneously through the use of a high-resolution visualization. Multiple studies on how best to visualize the multivalent parameters of interdisciplinary work are discussed, highlighting how the use of an interactive data-driven documents (D3) visualization is proving very useful in managing and analyzing the interdisciplinary work of the center in the pursuit of common research goals.","PeriodicalId":89305,"journal":{"name":"Visualization and data analysis","volume":"4 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Visualization and data analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2352/ISSN.2470-1173.2016.1.VDA-491","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

Studies show that many multi-scalar research problems cannot easily be addressed from the confines of individual disciplines for they require the participation of many experts, each viewing the problem from their distinctive disciplinary perspective. The bringing together of disparate experts or fields of expertise is known as interdisciplinary research. The benefit of such an approach is that discourse and collaboration among experts in distinct fields can generate new insights to the research problem at hand. With this approach comes large amounts of multivariate data and understanding the possible relationships between variables and their corresponding relevance to the problem is in itself a challenge. One of the most valuable means through which to comprehend big data and make it more approachable, is through data visualization. This paper presents a trial to encompass an interdisciplinary research centers collaborators, experiments, and results, and represent them simultaneously through the use of a high-resolution visualization. Multiple studies on how best to visualize the multivalent parameters of interdisciplinary work are discussed, highlighting how the use of an interactive data-driven documents (D3) visualization is proving very useful in managing and analyzing the interdisciplinary work of the center in the pursuit of common research goals.
跨学科研究的交互式可视化
研究表明,许多多标量研究问题不容易从单个学科的范围内解决,因为它们需要许多专家的参与,每个专家都从他们独特的学科角度看待问题。将不同的专家或专业领域聚集在一起被称为跨学科研究。这种方法的好处是,不同领域的专家之间的讨论和合作可以对手头的研究问题产生新的见解。这种方法带来了大量的多变量数据,理解变量之间的可能关系以及它们与问题的相应相关性本身就是一个挑战。理解大数据并使其更易于接近的最有价值的方法之一是通过数据可视化。本文提出了一个包含跨学科研究中心的合作者、实验和结果的试验,并通过使用高分辨率可视化同时表示它们。讨论了如何最好地可视化跨学科工作的多价参数的多项研究,强调了如何使用交互式数据驱动文档(D3)可视化证明在管理和分析中心的跨学科工作中非常有用,以追求共同的研究目标。
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:604180095
Book学术官方微信