Clinical interpretation for variants of uncertain significance is important to provide appropriate medical treatment. However, enormous effort and specialized knowledge are required to give a clinical interpretation to variants. To reduce the burden, it is necessary to develop an automated estimation system of clinical significance using aggregated knowledge from public databases and literature for interpretation. We are constructing a database that collects disease-related variants in Japanese population in order to improve interpretation of Japanese variants. In this work, we carry out RDF conversion of public databases that are needed to interpret variants, and integration of them to apply to the estimation system using a machine learning method.