The State of the Art in User‐Adaptive Visualizations

Abstract Research shows that user traits can modulate the use of visualization systems and have a measurable influence on users' accuracy, speed, and attention when performing visual analysis. This highlights the importance of user‐adaptive visualization that can modify themselves to the characteristics and preferences of the user. However, there are very few such visualization systems, as creating them requires broad knowledge from various sub‐domains of the visualization community. A user‐adaptive system must consider which user traits they adapt to, their adaptation logic and the types of interventions they support. In this STAR, we survey a broad space of existing literature and consolidate them to structure the process of creating user‐adaptive visualizations into five components: Capture Ⓐ Input from the user and any relevant peripheral information. Perform computational Ⓑ User Modelling with this input to construct a Ⓒ User Representation . Employ Ⓓ Adaptation Assignment logic to identify when and how to introduce Ⓔ Interventions . Our novel taxonomy provides a road map for work in this area, describing the rich space of current approaches and highlighting open areas for future work.

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Publication Details

Journal
Computer Graphics Forum
Published
2024-12-04
DOI
https://doi.org/10.1111/cgf.15271
Citations
11
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
2.74
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article

The State of the Art in User‐Adaptive Visualizations

Cristina Conati, Carolina Nobre, Alvitta Ottley, Fernando Yanez
11 citations
Computer Graphics Forum
Data Visualization and Analytics
2.74
article

The State of the Art in User‐Adaptive Visualizations

Cristina Conati, Carolina Nobre, Alvitta Ottley, Fernando Yanez
article en
11 citations

Abstract

Abstract Research shows that user traits can modulate the use of visualization systems and have a measurable influence on users' accuracy, speed, and attention when performing visual analysis. This highlights the importance of user‐adaptive visualization that can modify themselves to the characteristics and preferences of the user. However, there are very few such visualization systems, as creating them requires broad knowledge from various sub‐domains of the visualization community. A user‐adaptive system must consider which user traits they adapt to, their adaptation logic and the types of interventions they support. In this STAR, we survey a broad space of existing literature and consolidate them to structure the process of creating user‐adaptive visualizations into five components: Capture Ⓐ Input from the user and any relevant peripheral information. Perform computational Ⓑ User Modelling with this input to construct a Ⓒ User Representation . Employ Ⓓ Adaptation Assignment logic to identify when and how to introduce Ⓔ Interventions . Our novel taxonomy provides a road map for work in this area, describing the rich space of current approaches and highlighting open areas for future work.

Computer Graphics ForumVol. 44(1)
University of British Columbia (CA), University of Toronto (CA), Washington University in St. Louis (US)
Openalex Percentile: Top 8%
Data Visualization and Analytics
2.74
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