In some cases, incompatibilities across samples are so great that the composite coding scheme is significantly more cumbersome than the original variable coding design. In these cases, we will develop alternate versions of the variables suitable for particular comparisons across time and space. The data access system will recommend the most appropriate version of each variable to researchers based on user profile and the particular combination of datasets they are using. Where feasible, we will base our coding designs on United Nations coding systems. For geographic variables, we will generally conform to the standard of the country.
Most data transformations are simple recodes of one value into another.
These matrices will be maintained in a standard relational database. The actual recoding operations, however, will be carried out with a C program operating as a sequential batch process, since that is the most efficient approach with respect to both storage and speed. In many instances, it is necessary to use information from more than one variable in the original to construct a new compatible variable. For example, one might need information on both province and subdistrict to identify a metropolitan area. Data transformation matrices can sometimes handle such complex transformations, but in other cases we will have to resort to customized programming solutions.