重新构想TaxiVis：通过沉浸式时空立方体隐喻及其对城市数据探索的沉浸式分析潜在益处的反思
Reimagining TaxiVis through an Immersive Space-Time Cube metaphor and reflecting on potential benefits of Immersive Analytics for urban data exploration
AI总结：
本研究重新构想TaxiVis为沉浸式时空立方体原型，探索沉浸式分析对城市数据探索的潜在益处，通过案例研究展示其独特功能与互补性。
摘要：
当前的视觉化研究已认识到利用VR和AR技术进行数据探索的更具沉浸式环境的潜力。为了探索传统视觉化系统如何适应沉浸式框架，以及它如何从中受益，我们决定重新审视十年前在IEEE VIS上发表的具有里程碑意义的论文。Ferreira等人提出的TaxiVis实现了对纽约市出租车出行大型数据集的交互式时空查询。在此，我们重新构想TaxiVis的功能如何在3D沉浸式环境中实现和扩展。在沉浸式TaxiVis原型中，我们识别出的独特功能包括：额外视觉维度的替代用途、完全可视化的3D时空查询框架，以及在不同尺度和参考系下探索数据的机会。通过重新审视原始论文中的案例研究，我们展示了能从这种沉浸式视角中受益的工作流程。通过报告我们的经验，以及我们设计决策背后的愿景和推理，我们希望为关于传统和沉浸式视觉化范式如何互补以及未来几年如何促进城市数据集探索的辩论做出贡献。
英文摘要：
Current visualization research has identified the potential of more immersive settings for data exploration, leveraging VR and AR technologies. To explore how a traditional visualization system could be adapted into an immersive framework, and how it could benefit from this, we decided to revisit a landmark paper presented ten years ago at IEEE VIS. TaxiVis, by Ferreira et al., enabled interactive spatio-temporal querying of a large dataset of taxi trips in New York City. Here, we reimagine how TaxiVis' functionalities could be implemented and extended in a 3D immersive environment. Among the unique features we identify as being enabled by the Immersive TaxiVis prototype are alternative uses of the additional visual dimension, a fully visual 3D spatio-temporal query framework, and the opportunity to explore the data at different scales and frames of reference. By revisiting the case studies from the original paper, we demonstrate workflows that can benefit from this immersive perspective. Through reporting on our experience, and on the vision and reasoning behind our design decisions, we hope to contribute to the debate on how conventional and immersive visualization paradigms can complement each other and on how the exploration of urban datasets can be facilitated in the coming years.
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。
