The increasing amount of heterogeneous data from different data sources is a challenging problem in many areas. Visual Analytics, a discipline which emerged in the last decade, tries to cope with this issue. Visual Analytics is "the science of analytical reasoning facilitated by visual interfaces" [Thomas+Cook 2005]. In other words, Visual Analytics is a combination of automatic, visual, and interactive methods to explore large datasets. To achieve this, Visual Analytics draws on several different disciplines, as e.g. information visualization, data mining, data management, spatio-temporal data analysis, and cognitive psychology [Keim et al. 2010]. In this context, the human element plays an important role. The seamless interplay between human and computer is essential for getting relevant insights from the data. In this way, Visual Analytics supports the exploration and understanding of large and complex datasets. In Europe, Visual Analytics was put forward by the VisMaster project that was financed by the European Commission from August 2008 until September 2010. Members of the VisMaster consortium established the EuroVA workshop. The goal of the EuroVA workshop is to provide a forum for researchers in the area of Visual Analytics – to present novel research and to discuss new findings. This special section of Computers & Graphics is based on contributions from the 4th EuroVA workshop in 2013.
Mendeley saves you time finding and organizing research
Choose a citation style from the tabs below