We are co-organizing track
International Symposium Visual Analytics and Data Science at the next
International Information Visualisation Conference (iV 2020) in Vienna, Austria. The Information Visualisation Conference (iV) is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation and development. The scope of the conference covers the following topics:
- 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 of spatial, temporal, and spatio-temporal data
- Knowledge construction and management in Visual Analytics
- Guidance in Visual Analytics
- Intelligent approaches of Visual Analytics and Data Science
- Adaptive 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
Please note the
iV2020 Call for Papers (CfP).
The Visual Analytics and Data Science track is organized via the
12th International Symposium Visual Analytics and Data Science.
Visual Analytics is viewed as the science of analytical reasoning empowered by interactive visualizations. It combines interactive visualizations with models and approaches of machine learning and artificial intelligence, enabling solving complex analytical tasks by uncovering hidden patterns in data.
The research on Visual Analytics is closely related to that of Data Science. Both areas seek to enhance the knowledge discovery process using machine learning, data mining and artificial intelligence methods, whereas Visual Analytics allows commonly a direct manipulation of the underlying models through graphical representations. By leveraging human perception of the visual space, patterns that might not otherwise be discovered. Visual Analytics utilizes concepts from a wide variety of disciplines, including Computer Graphics, Information Visualization, Machine Learning, Artificial Intelligence, Knowledge Discovery, Cognition and Visual Perception. The scope of the VA track covers the following topics:
- 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 of spatial, temporal, and spatio-temporal data
- Knowledge construction and management in Visual Analytics
- Guidance in Visual Analytics
- Intelligent approaches of Visual Analytics and Data Science
- Adaptive 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
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