Uncertainty-aware visual analytics: scope, opportunities, and challenges

In many applications, visual analytics (VA) has developed into a standard tool to ease data access and knowledge generation. VA describes a holistic cycle transforming data into hypothesis and visualization to generate insights that enhance the data. Unfortunately, many data sources used in the VA p...

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Bibliographic Details
Published in:The Visual computer 2023-12, Vol.39 (12), p.6345-6366
Main Authors: Maack, Robin G. C., Scheuermann, Gerik, Hagen, Hans, Peñaloza, Jose Tiberio Hernández, Gillmann, Christina
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Graphics
Computer Science
Datasets
Decision making
Hypotheses
Image Processing and Computer Vision
Mathematical analysis
Original Article
Taxonomy
Uncertainty
Visualization
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Summary:In many applications, visual analytics (VA) has developed into a standard tool to ease data access and knowledge generation. VA describes a holistic cycle transforming data into hypothesis and visualization to generate insights that enhance the data. Unfortunately, many data sources used in the VA process are affected by uncertainty. In addition, the VA cycle itself can introduce uncertainty to the knowledge generation process but does not provide a mechanism to handle these sources of uncertainty. In this manuscript, we aim to provide an extended VA cycle that is capable of handling uncertainty by quantification, propagation, and visualization, defined as uncertainty-aware visual analytics (UAVA). Here, a recap of uncertainty definition and description is used as a starting point to insert novel components in the visual analytics cycle. These components assist in capturing uncertainty throughout the VA cycle. Further, different data types, hypothesis generation approaches, and uncertainty-aware visualization approaches are discussed that fit in the defined UAVA cycle. In addition, application scenarios that can be handled by such a cycle, examples, and a list of open challenges in the area of UAVA are provided.
ISSN:0178-2789
1432-2315
DOI:10.1007/s00371-022-02733-6