Immersive Analytics: Theory and Research Agenda
Immersive Analytics: Theory and Research Agenda
复制标题
沉浸式分析：理论和研究议程
作者：
Richard Skarbez;Nicholas F. Polys;J. T. Ogle;Chris North;D. Bowman
各种计算领域的进步，包括“大数据”、机器学习、可视化和增强/混合/虚拟现实，共同催生了新兴的沉浸式分析领域，该领域研究这些新技术如何支持分析和决策。到目前为止，我们觉得沉浸式分析研究有点特别，可能是因为还没有一个组织框架来进行沉浸式分析研究。在本文中，我们提出了沉浸式分析的定义，并确定了一些对该领域的发展至关重要的一般研究领域和具体研究问题，以解决这一不足。我们还提供了三个案例研究，虽然都是我们认为的身临其境分析的例子，但也提出了不同的挑战和机遇。这些有助于展示沉浸式分析的广度，并说明本文提出的框架如何应用于实际研究。
Advances in a variety of computing fields, including “big data,” machine learning, visualization, and augmented/mixed/virtual reality, have combined to give rise to the emerging field of immersive analytics, which investigates how these new technologies support analysis and decision making. Thus far, we feel that immersive analytics research has been somewhat ad hoc, possibly owing to the fact that there is not yet an organizing framework for immersive analytics research. In this paper, we address this lack by proposing a definition for immersive analytics and identifying some general research areas and specific research questions that will be important for the development of this field. We also present three case studies that, while all being examples of what we would consider immersive analytics, present different challenges, and opportunities. These serve to demonstrate the breadth of immersive analytics and illustrate how the framework proposed in this paper applies to practical research.