Digitizing strategy on the same ontology in heterogeneous data source

The existence of the data objects, having the same ontology in heterogeneous data source (SO-HDS), is always the difficulty in cleaning process. Nowadays, there are several matching algorithms which can detect these data, such as Descartes Method, Enhanced Descartes Method and Priority Queue Algorithm. All these algorithms detect the similarity among the data directly without any pre-process on the original data. In this paper, we put forward a digitizing strategy on matching data objects based on the ontology of data object. When the data objects have the feature of SO-HDS, the storage mode and expression of these data objects can be ignored. We also propose a new data matching algorithm to find out the data objects having SO-HDS with the help of physics store attribute of data object. The new digitizing strategy will reduce the comparison amongst data objects, and keep the accuracy at the same time.