Visual Analytics is the science of analytical reasoning empowered by interactive visualizations. The research on Visual Analytics is closely related to that of Data Science. Both areas seek to enhance knowledge discovery using machine learning, data mining, and artificial intelligence methods. In contrast, Visual Analytics commonly allows direct manipulation of the underlying models through graphical representations. By leveraging human perception of the visual space, patterns that might not otherwise be discovered emerge. Visual Analytics utilizes concepts from various disciplines, including computer graphics, information visualization, machine learning, artificial intelligence, knowledge discovery, cognition, and visual perception.
The topics of interest include but are not limited to:
- Combining visual and computational methods of Data Analysis, Machine Learning, and Artificial Intelligence
- Visual Analytics models and approaches
- Novel Visual Analytics applications
- Visual Trend Analytics
- Visual Analytics, geo-visualization, and geographical visualization of spatial, temporal, and Spatio-temporal data
- Visualization support for multi-criteria decision analysis related to multivariate and spatial data
- Knowledge construction and management in Visual Analytics
- Guidance in Visual Analytics
- Intelligent approaches of Visual Analytics and Data Science
- Adaptive Visual Analytics
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Integrative visual analytics and artificial intelligence systems and approaches
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AI and visual analytics to support decision-making
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Techniques and methods in explainable AI
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Visual analytic solutions for handling big data challenges
- HCI issues of geographical and Spatio-temporal visual analytics
- Cognitive approaches and explanations for Visual Analytics
- Visual Analytics for explaining AI
- Visualization of Data Mining algorithms
- Empirical performance studies
- Evaluation of Visual Data Mining methods
- Collaborative Visual Analytics and Data Science
- Computational steering for long-running Data Mining applications
- Reviews and surveys of related literature
Supporting Bodies
Darmstadt University of Applied Sciences, Germany
NOVA LINCS and ISEL-Instituto Politécnico de Lisboa, PT
Organizing Committee
Prof. Kawa Nazemi, Darmstadt University of Applied Sciences, Germany
Prof. Nuno Miguel Soares Datia, NOVA LINCS and ISEL, Instituto Politécnico de Lisboa, PT
Prof. Joao M. Pires, NOVA LINCS Laboratory for Computer Science and Informatics, Universidade NOVA de Lisboa, PT
Dr Loredana Caruccio, University of Salerno, Italy
Dr Autilia Vitiello, University of Naples Federico II, Italy
Symposium specific enquiries should be addressed to the symposium lead organizing coordinators:
Prof. Kawa Nazemi, Darmstadt University of Applied Sciences, Germany
kawa.nazemi (@) h-da.de
Prof. Nuno Miguel Soares Datia, NOVA LINCS and ISEL-Instituto Politécnico de Lisboa, PT
datia (@) isel.ipl.pt