Expanding the Horizons of Situated Visualization: The Extended SV Model

IF 3.7 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Big Data and Cognitive Computing Pub Date : 2023-06-07 DOI:10.3390/bdcc7020112
Nuno Cid Martins, Bernardo Marques, Paulo Dias, B. Sousa Santos
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引用次数: 0

Abstract

To fully leverage the benefits of augmented and mixed reality (AR/MR) in supporting users, it is crucial to establish a consistent and well-defined situated visualization (SV) model. SV encompasses visualizations that adapt based on context, considering the relevant visualizations within their physical display environment. Recognizing the potential of SV in various domains such as collaborative tasks, situational awareness, decision-making, assistance, training, and maintenance, AR/MR is well-suited to facilitate these scenarios by providing additional data and context-driven visualization techniques. While some perspectives on the SV model have been proposed, such as space, time, place, activity, and community, a comprehensive and up-to-date systematization of the entire SV model is yet to be established. Therefore, there is a pressing need for a more comprehensive and updated description of the SV model within the AR/MR framework to foster research discussions.
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扩展位置可视化的视野:扩展的SV模型
为了充分利用增强和混合现实(AR/MR)在支持用户方面的优势,建立一致且定义良好的位置可视化(SV)模型至关重要。SV包含基于上下文的可视化,考虑到物理显示环境中的相关可视化。认识到SV在各种领域的潜力,如协作任务、态势感知、决策、援助、培训和维护,AR/MR非常适合通过提供额外的数据和上下文驱动的可视化技术来促进这些场景。虽然对SV模型提出了空间、时间、地点、活动和社区等观点,但尚未建立一个全面的、最新的系统的整个SV模型。因此,迫切需要在AR/MR框架内对SV模型进行更全面和更新的描述,以促进研究讨论。
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来源期刊
Big Data and Cognitive Computing
Big Data and Cognitive Computing Business, Management and Accounting-Management Information Systems
CiteScore
7.10
自引率
8.10%
发文量
128
审稿时长
11 weeks
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