Extracting class diagram from hidden dependencies in data set

A conceptual model is a high-level, graphical representation of a specic domain, presenting its key concepts and relationships between them. In particular, these dependencies can be inferred from concepts' instances being a part of big raw data les. The paper aims to propose a method for constructing a conceptual model from data frames encompassed in data les. The result is presented in the form of a class diagram. The method is explained with several examples and veried by a case study in which the real data sets are processed. It can also be applied for checking the quality of the data set.