Data visualization is the study of the visual representation of data, meaning "information that has been abstracted in some schematic form, including attributes or variables for the units of information"
Data visualization is closely related to information graphics, information vizualization, scientific vizualization, and statistical graphics. In the new millennium, data visualization has become an active area of research, teaching, and development. According to Post et al. (2002), it has united the field of scientific and information visualization. As demonstrated by Brian Willison, data visualization has been also been linked to enhancing agile software development and customer engagement.According to Friedman (2008) the "main goal of data visualization is to communicate information clearly and effectively through graphical means. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often fail to achieve a balance between form and function, creating gorgeous data visualizations which fail to serve their main purpose to communicate information" Indeed,Fernanda Viegas and Martin M. Wattenberg have suggested that an ideal visualization should not merely communicate clearly, but stimulate viewer engagement and attention.
KPI Library has developed the “Periodic Table of Visualization Methods”, an interactive chart displaying various data visualization methods. It details 6 types of data visualization methods: data, information, concept, strategy, metaphor and compound.
