For the robust exchange of parametric CAD model data, it is very important to perform mapping rightly and accurately between different CAD models. However, data model mapping is usually performed on a case-by-case basis. This results in the problem that mapping quality fluctuates very widely depending on the abilities of developers. In order to solve this problem, the concept of symantic distance is adapted and applied to the translation of parametric CAD model data in order to measure the difference between different CAD models quantitatively in a computer-interpretable form and systematize the mapping process.