Scalable Interactive Visualization
Gunther H. Weber (Ed.)
Scalable Interactive Visualization - MDPI - Multidisciplinary Digital Publishing Institute 2018 - 1 electronic resource (VIII, 236 p.)
Open Access
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 better data understanding by significantly reducing cognitive load on the analyst. Two fundamental concepts, visualization and interaction, form the basis of the underlying scientific methods. Combining these concepts connects two key research areas in computer science: visualization and human-computer interaction (HCI) and brings together practitioners from many disciplines. The result is highly multi-disciplinary work with significant impact and virtually unlimited application areas. However, truly interactive visualizations are hard to design and implement, so researchers have to solve multiple problems. This Special Issue provides an overciew over the current state-of-the-art of “Interactive Visualization.” It shows recent work in the field, as well as trends for future development.
Creative Commons
English
9783038428046 9783038428039
Web-based visualization Interactive visualization Challenges for scalable interactive visualization Interactive visualization systems Scalability Feature detection High-Performance Computing (HPC) Collaborative visualization Visual analysis Handling and visualization of Big Data
Scalable Interactive Visualization - MDPI - Multidisciplinary Digital Publishing Institute 2018 - 1 electronic resource (VIII, 236 p.)
Open Access
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 better data understanding by significantly reducing cognitive load on the analyst. Two fundamental concepts, visualization and interaction, form the basis of the underlying scientific methods. Combining these concepts connects two key research areas in computer science: visualization and human-computer interaction (HCI) and brings together practitioners from many disciplines. The result is highly multi-disciplinary work with significant impact and virtually unlimited application areas. However, truly interactive visualizations are hard to design and implement, so researchers have to solve multiple problems. This Special Issue provides an overciew over the current state-of-the-art of “Interactive Visualization.” It shows recent work in the field, as well as trends for future development.
Creative Commons
English
9783038428046 9783038428039
Web-based visualization Interactive visualization Challenges for scalable interactive visualization Interactive visualization systems Scalability Feature detection High-Performance Computing (HPC) Collaborative visualization Visual analysis Handling and visualization of Big Data