Data Visualization and Data Product: Two Easily Confusing Terms
Liao Shunbao, Institute of Geographical Sciences and Natural Resources Research,
Chinese Academy of Science, China
Data visualization and data production are two terms often used in data processing. However, people are often confused by them. Data visualization means that data are displayed on screen in forms of graph or image through computer graphics and image processing technologies, so it is related to computer graphics, image processing, computer aided design, computer vision and man-computer interaction. Data product refers to the new data generated by a kind of mathematical model or formula with raw data, and there is essential difference between data product and raw data in either formats or contents. The terms of data product and raw data are relative. When a data product is used to produce another data product, it becomes raw data.
Sometimes data visualization is mistaken for data product. For example, when we have population data by administrative divisions (such as province, county or township) and administrative boundary data, a statistical population map is usually generated. The map is often mistaken for a new data product. In fact, the map is only a visualization of statistical population data. Because there is no substantial difference before and after the map is generated in either data formats or data contents, it is not a data product. When we interpolate data from meteorological stations to a region, although no new data are generated, but data format changes from vector to grid, and volume of information is enlarged. So the dataset generated by interpolation is a new data product. VI (Vegetation Index) is an indicator of ecosystem and environment. It is usually calculated by combination of different bands of remotely sensed data. Compared with raw data, it generates new information although its format is not changed. So it is a data product.
Scientific data is generalization and abstract for objective things or phenomenon. However, visualization tries to recover objective things or phenomenon from generalization and abstract to its real status to some extent. It stresses visual and aesthetic effects. A 3-dimension DEM (Digital Elevation Model) is better than 2-dimension DEM visually or aesthetically, but a 2-dimension DEM is more convenient and efficient than a 3-dimension DEM for us to understand and grasp differential and spatial distribution of altitude in a geographic region. It is very important to understand properly the role of visualization in scientific research.
The purpose of data visualization is to enhance visual effects, but it does not generate new data and information. Compared with raw data, data product either generates new information or has essential difference in formats.
Keywords: Data Visualization, Data Product, Differential