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Expanding the Horizons of Situated Visualization: The Extended SV Model

Authors :
Nuno Cid Martins
Bernardo Marques
Paulo Dias
Beatriz Sousa Santos
Source :
Big Data and Cognitive Computing, Vol 7, Iss 2, p 112 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

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.

Details

Language :
English
ISSN :
25042289
Volume :
7
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Big Data and Cognitive Computing
Publication Type :
Academic Journal
Accession number :
edsdoj.3614e23bdf84212a28e979383d1976d
Document Type :
article
Full Text :
https://doi.org/10.3390/bdcc7020112