Understanding Open Access Data Using Visuals: Integrating Prospective Studies of Children’s Responses to Natural Disasters
Understanding Open Access Data Using Visuals: Integrating Prospective Studies of Children’s Responses to Natural Disasters
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DOI：
10.1007/s10566-019-09496-7
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发表时间：
2019-03-01
影响因子：
1.8
通讯作者：
Medzhitova J
中科院分区：
文献类型：
--
作者：
Shah HJ;Lai BS;Leroux AJ;La Greca AM;Colgan CA;Medzhitova J
随着获取开放数据的机会越来越多，研究人员获得了建立综合数据集和进行更强大的统计分析的机会。然而，使用开放获取的数据给研究人员理解数据带来了挑战。可视化使研究人员能够通过促进对可用信息的更好理解来应对这些挑战。本文阐述了可视化如何解决研究人员在使用开放获取数据时所面临的挑战，例如：(1)熟悉数据，(2)识别数据中的模式和趋势，以及(3)确定如何整合来自多个研究的数据。本文使用了一项综合数据分析研究的数据，该研究结合了儿童对四种自然灾害：安德鲁飓风、查利飓风、卡特里娜飓风和艾克飓风的前瞻性研究数据。综合数据集评估了1707名参与者(53.61%女性)的飓风暴露、创伤后应激症状、焦虑、社会支持和生活事件。儿童年龄7~16岁(男性=9.61，SD=1.60)。可视化是理解新的和不熟悉的数据集的有效方法。为了应对开放获取数据的增长，研究人员必须培养创造信息丰富的视觉效果所需的技能。大多数以研究为基础的研究生课程在毕业时不需要以编程为基础的课程。需要提供更多的编程语言培训机会，以便未来的研究人员更好地准备理解新数据。本文讨论了当前研究生课程要求和标准期刊实践对研究人员如何可视化数据的影响。
As access to open data is increasing, researchers gain the opportunity to build integrated datasets and to conduct more powerful statistical analyses. However, using open access data presents challenges for researchers in understanding the data. Visuals allow researchers to address these challenges by facilitating a greater understanding of the information available. This paper illustrates how visuals can address the challenges that researchers face when using open access data, such as: (1) becoming familiar with the data, (2) identifying patterns and trends within the data, and (3) determining how to integrate data from multiple studies. This paper uses data from an integrative data analysis study that combined data from prospective studies of children’s responses to four natural disasters: Hurricane Andrew, Hurricane Charley, Hurricane Katrina, and Hurricane Ike. The integrated dataset assessed hurricane exposure, posttraumatic stress symptoms, anxiety, social support, and life events among 1707 participants (53.61% female). The children’s ages ranged from 7 to 16 years (M = 9.61, SD = 1.60). Visuals serve as an effective method for understanding new and unfamiliar datasets. In response to the growth of open access data, researchers must develop the skills necessary to create informative visuals. Most research-based graduate programs do not require programming-based courses for graduation. More opportunities for training in programming languages need to be offered so that future researchers are better prepared to understand new data. This paper discusses implications of current graduate course requirements and standard journal practices on how researchers visualize data.
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影响因子：
6.6
作者：
La Greca, Annette M.;Lai, Betty S.;Short, Mary A.
通讯作者：
Short, Mary A.
DOI：
10.1007/s12144-015-9338-6
发表时间：
2015-09
期刊：
Current psychology (New Brunswick, N.J.)
影响因子：
--
作者：
Lai BS;Tiwari A;Beaulieu BA;Self-Brown S;Kelley ML
通讯作者：
Kelley ML
影响因子：
7
作者：
Curran, Patrick J.;Hussong, Andrea M.
通讯作者：
Hussong, Andrea M.
影响因子：
12.7
作者：
Amico, K. Rivet
通讯作者：
Amico, K. Rivet
影响因子：
4.9
作者：
GREENBERG, MT;SIEGEL, JM;LEITCH, CJ
通讯作者：
LEITCH, CJ