This master's thesis seeks to apply research into RDBMS – which has led to mature techniques for storing and querying data – to the problem of improving how RDF data can be handled efficiently without missing any of the additional insights for which the RDF data model allows. The authors have come up with an unusual approach in which RDF data is transformed into the relational data model. Inherently unstructured RDF data is structured by means of semantic information, and relationships between these structures are extracted with the names for structures, their attributes, and relationships automatically generated. Subsequently, using the relational schema thus created, RDF data is physically stored in efficient data structures. Afterwards, it can be queried with an SQL-based interface.

Keywords: RDBMS, URI shortening, Characteristic sets, MonetDB/RDF
Author: Passing, Linnea
Date created: 2014-05-22 04:00:00.000
Time required: P2H
Educational use: instruction
Educational audience: student
Interactivity type: expositive

  • Competencies