Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data

Visual analytics is an emerging area of research and practice aimed at leveraging the excellent capabilities of humans in terms of visual information exploration. Thanks to the enormous increase in the processing power of computers and their graphics handling capabilities, we are now able to implement extremely powerful visual and interactive knowledge discovery environments [1] that can empower individual researchers or groups of researchers to make well-informed decisions in complex situations [2]. The goal of visual analytics is to make the processes of data elaboration, information gathering and knowledge generation transparent to tool users. Visual analytics is an enhancement of the information visualisation concept and can be seen as an integrated approach combining visualisation, human factors and data analysis [3].The basic idea of visual analytics is to visually represent the information, allowing the human to directly interact with the underpinning data to gain insight, draw conclusions, and ultimately make better decisions. The synergic integration between computation, visual representation, and interactive thinking supports intensive analysis by harnessing the human visual system to support the process of sense-making, in which information is collected, organised, and analysed to generate knowledge and plan actions. The goal is not only to permit users to detect expected events, such as might be predicted by models, but also to help users discover the unexpected--the surprising anomalies, changes, patterns, and relationships that are then examined and assessed to develop new insights [4].Visual analytics is an inherently multi-disciplinary field [5-7] that aims to combine the methods and strengths of various research areas, including human-computer interaction (HCI) and usability engineering, cognitive and perceptual science, decision science, information visualisation, scientific visualisation, geospatial visualisation, databases, data mining, statistic