MonetDB/RDF: Discovering and Exploiting the Emergent Schema of RDF Data

The Resource Description Framework (RDF) has been used as the main data model for the semantic web and Linked Open Data, providing great flexibility for users to represent and evolve data without need for a prior schema. This flexibility, however, poses challenges in implementing efficient RDF stores. It i) leads to query plan with many self-joins in triple tables, ii) blocks the use of advanced relational physical storage optimization such as clustered indexes and data partitioning, and iii) the lack of a schema sometimes makes it problematic for users to comprehend the data and formulate queries [1]. In the Database Architecture group at CWI, Amsterdam, we tackle these RDF data management problems by automatically recovering the structure present in RDF data, leveraging this structure both internally inside the database systems (in storage, optimization, and execution), and externally as an emergent schema towards the users who pose queries