As part of the derivation process, standardization is considered as the strategies by which the same information or data received in many formats is changed or transformed to a standard form that increases the comparison process. For instance, street names commonly comprise of directions including north or west; thus, the standardization routines format these values as “N” or “W” with the aim of increasing the comparison process (Almklov, 2008). Therefore, working with a standardized data is appropriate due to its significance including improved research capabilities through enhanced data quality, effective data integration and reusability, and improved team communication process. However, using standardized data needs a collaborative expert technique, evaluation, and consensus which will, in turn, make it appropriate for use.
Ahrens, J., Geveci, B., & Law, C. (2005). Paraview: An end-user tool for large data visualization. The visualization handbook, 717.
Almklov, P. G. (2008). Standardized data and singular situations. Social Studies of Science, 38(6), 873-897.