arXiv 1908.006802019-08-02cs.HC

设计现场移动和沉浸式可视化分析

Designing for Mobile and Immersive Visual Analytics in the Field

Matt Whitlock, Keke Wu, Danielle Szafir

摘要：

实地的数据汇集和分析对于环境科学和公共安全等领域的业务至关重要。然而，现场工作人员目前在现场的有效数据汇集和分析中面临面向数据和平台的问题，例如有限的连接性、屏幕空间和注意力资源。在本文中，我们将探讨可视化分析工具如何通过更深入地将数据集成到这些操作中来改变现场实践。我们使用了一个结合移动、云和沉浸式分析组件的设计探针来指导对来自五个领域的十位专家的采访，以探索可视化分析如何支持该领域的数据汇集和分析需求。结果确定了当前方法和目标场景的缺点，并为未来的现场分析系统的设计考虑。我们将这些发现体现在FieldView中，这是一个可扩展的开源原型，旨在支持现场分析的关键用例。我们的研究结果表明，整合移动和沉浸式技术，以提高数据的各种现场操作和可视化分析工具的新方向，以改变现场工作的效用的潜力。

英文摘要：

Data collection and analysis in the field is critical for operations in domains such as environmental science and public safety. However, field workers currently face data- and platform-oriented issues in efficient data collection and analysis in the field, such as limited connectivity, screen space, and attentional resources. In this paper, we explore how visual analytics tools might transform field practices by more deeply integrating data into these operations. We use a design probe coupling mobile, cloud and immersive analytics components to guide interviews with ten experts from five domains to explore how visual analytics could support data collection and analysis needs in the field. The results identify shortcomings of current approaches and target scenarios and design considerations for future field analysis systems. We embody these findings in FieldView, an extensible, open-source prototype designed to support critical use cases for situated field analysis. Our findings suggest the potential for integrating mobile and immersive technologies to enhance data's utility for various field operations and new directions for visual analytics tools to transform fieldwork.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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