Guiding through uncertainties in visual analytics: A survey

Information

• Publication Type: Journal Paper (without talk)
• Workgroup(s)/Project(s):
  • Visual Analytics and Computer Vision meet Cultural Heritage
• Date: 2026
• Article Number: 104739
• DOI: 10.1016/j.cag.2026.104739
• ISSN: 1873-7684
• Journal: Computers & Graphics
• Pages: 25
• Publisher: PERGAMON-ELSEVIER SCIENCE LTD
• Keywords: Guidance, Uncertainty, Visual Analytics, Decision Support Systems

Abstract

Several uncertainties emerge in each component of the visual analytics (VA) cycle that hinder the user’s ability to make efficient and effective decisions, e.g., through missing data, model approximations, or visual mappings. Well-known VA strategies aim first at making users aware of these uncertainties, often through visual means. When visuals alone are insufficient to accurately quantify or communicate uncertainties, VA designers may rely on guidance to support users’ understanding of these uncertainties throughout the VA cycle. While prior VA research has attempted to conceptualize guidance, the ability and mechanisms for guidance to comprehensively address different sources of uncertainties remain an open question. In this survey, we characterize the relationships between uncertainties and guidance in VA literature. Our key contribution is a taxonomic framework that relates uncertainty sources to relevant guidance strategies and their respective profiles, i.e., roles, scopes, and features. Through this taxonomy, we discuss how guidance addresses uncertainties, identify research gaps, and promote a more comprehensive understanding of guidance strategies to support effective design for uncertainty in VA. Our survey underscores the effectiveness of guidance in navigating uncertainties with context-aware and multi-scope strategies. We highlight challenging opportunities for further research in this space, especially in the adjacent areas of accessibility and onboarding, and suggest new research areas, such as narrative and persuasion guidance to support uncertainty awareness in VA.

Additional Files and Images

Weblinks

• Entry in reposiTUm (TU Wien Publication Database)
• DOI: 10.1016/j.cag.2026.104739

BibTeX

@article{musleh-2026-gtu,
  title =      "Guiding through uncertainties in visual analytics: A survey",
  author =     "Maath Musleh and Davide Ceneda and Ke Er Amy Zhang and Laura
               Garrison and Ignacio P\'{e}rez-Messina and Silvia Miksch and
               Renata Georgia Raidou",
  year =       "2026",
  abstract =   "Several uncertainties emerge in each component of the visual
               analytics (VA) cycle that hinder the user’s ability to
               make efficient and effective decisions, e.g., through
               missing data, model approximations, or visual mappings.
               Well-known VA strategies aim first at making users aware of
               these uncertainties, often through visual means. When
               visuals alone are insufficient to accurately quantify or
               communicate uncertainties, VA designers may rely on guidance
               to support users’ understanding of these uncertainties
               throughout the VA cycle. While prior VA research has
               attempted to conceptualize guidance, the ability and
               mechanisms for guidance to comprehensively address different
               sources of uncertainties remain an open question. In this
               survey, we characterize the relationships between
               uncertainties and guidance in VA literature. Our key
               contribution is a taxonomic framework that relates
               uncertainty sources to relevant guidance strategies and
               their respective profiles, i.e., roles, scopes, and
               features. Through this taxonomy, we discuss how guidance
               addresses uncertainties, identify research gaps, and promote
               a more comprehensive understanding of guidance strategies to
               support effective design for uncertainty in VA. Our survey
               underscores the effectiveness of guidance in navigating
               uncertainties with context-aware and multi-scope strategies.
               We highlight challenging opportunities for further research
               in this space, especially in the adjacent areas of
               accessibility and onboarding, and suggest new research
               areas, such as narrative and persuasion guidance to support
               uncertainty awareness in VA.",
  articleno =  "104739",
  doi =        "10.1016/j.cag.2026.104739",
  issn =       "1873-7684",
  journal =    "Computers & Graphics",
  pages =      "25",
  publisher =  "PERGAMON-ELSEVIER SCIENCE LTD",
  keywords =   "Guidance, Uncertainty, Visual Analytics, Decision Support
               Systems",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2026/musleh-2026-gtu/",
}