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Data Clothing and BigBarChart: Designing Physical Data Reports on Indoor Pollutants for Individuals and Communities

机译:数据服装和BigBarchart:设计关于个人和社区的室内污染物的物理数据报告

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In response to participant preferences and new ethics guidelines, researchers are increasingly sharing data with health study participants, including data on their own household chemical exposures. Data physicalization may be a useful tool for these communications, because it is thought to be accessible to a general audience and emotionally engaged. However, there are limited studies of data physicalization in the wild with diverse communities. Our application of this method in the Green Housing Study is an early example of using data physicalization in environmental health report-back. We gathered feedback through community meetings, prototype testing, and semistructured interviews, leading to the development of data t-shirts and other garments and person-sized bar charts. We found that participants were enthusiastic about data physicalizations, it connected them to their previous experience, and they had varying desires to share their data. Our findings suggest that researchers can enhance environmental communications by further developing the human experience of physicalizations and engaging diverse communities.
机译:为了回应参与者偏好和新的道德准则,研究人员越来越多地与健康研究参与者分享数据,包括有关自己家庭化学曝光的数据。数据物理化可能是这些通信的有用工具,因为它被认为可以访问一般观众和情绪从事。然而,与多元社区的野外数据相似有限的研究。我们在绿色住房研究中应用这种方法是在环境健康报告中使用数据物理化的早期示例。我们通过社区会议,原型测试和半系统采访收集了反馈,导致数据T恤和其他服装和其他人尺寸的条形图。我们发现参与者对数据的热情感到热烈,它将它们与他们以前的经历联系起来,他们有不同的愿望来分享他们的数据。我们的研究结果表明,研究人员可以通过进一步发展物体化的人类经验并参与多样化的社区来提高环境通信。

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