Construction of RDF Knowledge Graph with MongoDB

Resource Description Framework (RDF) is widely used in semantic extraction, unified organization, and intelligent processing of large amounts of data because of its machine intelligibility. For example, knowledge graph based on RDF is commonly used in intelligent search, recommendation system, and smart medical treatment. And RDF is used to express the relationship between entities and process the semantics of data. Many efforts have been made to convert various data (such as relational database, XML, and JSON) into RDF. Yet, the effective generation of usable RDF data is still an urgent problem to be solved. With the wide use of NoSQL database, massive data is stored in NoSQL database, but the research on generating RDF from NoSQL database is not emphasized. We put forward a formal definition of MongoDB, and according to this definition, we propose a method of automatically extracting data from MongoDB and building corresponding RDF. Based on this method, we have also implemented a prototype system named M2R to validate method performance. The experimental results show that our approach is feasible and efficient.