Reimagining TaxiVis through an Immersive Space-Time Cube metaphor and reflecting on potential benefits of Immersive Analytics for urban data exploration
CoRR(2024)
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.
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关键词
Human-centered computing,Visualization,Visualization systems and tools,Human computer interaction (HCI),Interaction paradigms,Virtual reality
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