Data visualization refers to techniques used to communicate insights from data through visual representation. Its main goal is to distill large datasets into visual graphics to allow for easy understanding of complex relationships within the data. It is often used interchangeably with terms such as information graphics, statistical graphics, and information visualization.
Scientific visualization, information visualization, and visual analytics are often seen as the three main branches of visualization. The new discipline “Data Visualization”, which is a combination of these three branches, is a new starting point in the field of visual research.
Generalized data visualization involves various disciplines such as information technology, natural science, statistical analysis, graphics, interaction, and geographic information.
1.1 Scientific Visualization
Scientific visualization is an interdisciplinary research and application field in science, focusing on the visualization of three-dimensional phenomena, such as architecture, meteorology, medicine or biological systems. Its purpose is to graphically illustrate scientific data, enabling scientists to understand, explain, and collect patterns from the data.
1.2 Information visualization
Information visualization is the study of interactive visual representations of abstract data to enhance human cognition. Abstract data includes both digital and non-digital data such as geographic information and text. Graphics such as histograms, trend graphs, flow charts, and tree diagrams all belong to information visualization, and the design of these graphics transforms abstract concepts into visual information.
1.3 Visual Analytics
Visual analytics is a new field that has evolved with the development of scientific visualization and information visualization, with an emphasis on analytical reasoning through an interactive visual interface.
The amount of information that humans gain through vision is far beyond that of other organs. Data visualization is the use of human natural skills to enhance data processing and organization efficiency.