Scalable Interactive Visualization

Dear Colleagues,

Data available in today’s information society is ever growing in size and complexity—i.e., unstructured, multidimensional, uncertain, etc.—making it impossible to survey and understand this data. Traditionally, most of these datasets are stored and depicted as huge tables, hindering efficient retrieval of salient information—similarities, outliers, structures, origin, etc. Interactive visualization provides an interface to this data that can help gleaning valuable information from it, thus supporting a better data understanding by significantly reducing cognitive load on the analyst. As the term implies, two concepts form the fundamental basis of the underlying scientific methods: visualization and interaction. Combining these concepts builds a bridge between two key research areas in computer science: visualization and human-computer interaction (HCI) and brings together practitioners from many disciplines. This results in highly multi-disciplinary work with significant impact.

Applications for interactive visualization are virtually unlimited and include:

• Analysis of complex data sets (“big data”),
• Virtual reality environments,
• Augmented reality,
• Mobile Environments,
• Cooperative Work,
• Computer-supported surgery,
• Large-scale simulations,
• Experimental and observational data, and
• Sensor networks.

However, truly interactive visualizations are hard to design and implement. Researchers have to solve multiple problems, e.g.:

• Transforming complexity into simplicity,
• Efficient algorithms and implementations,
• Guaranteeing real-time performance,
• Scaling to multiple platforms and user types,
• Minimizing and managing data transfer, and
• Efficient parallel implementations.

This Special Issue will provide an insight on the current state-of-the-art of “Interactive Visualization”. It will show recent works in the field, as well as trends for future development.

Prof. Dr. Achim Ebert
Prof. Dr. Gunther H. Weber
Guest Editors

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