Generating Property Graphs from RDF using a semantic preserving conversion approach (en-US)
Graph Databases are on a rise since the last decade due to their dominance in mining and analysis of complex networks. Property Graphs (PGs), one of the graph data models which Graph Databases use, are suitable for the representation of many real-life application scenarios. They allow to efficiently represent complex networks (e.g. social networks, E-commerce) and interactions. In order to leverage this advantage of graph databases, conversions of other data models to property graphs are a current area of research. The aim of this thesis is to (i) propose a novel systematic conversion approach for generating PGs from RDF (one of the graph data models) (ii) and carry out exhaustive experiments on both RDF and PG datasets with respect to their native storage databases (i.e. Graph DBs vs Triplestores). This will allow to identify the types of queries for which graph databases offer performance advantages and ideally allow to adapt the storage mechanism accordingly. The outcome of this work will be integrated into the LITMUS framework, which is an open extensible framework for benchmarking of diverse Data Management Solutions.
Basically, this subject would offer the student the possibility of entering in the SemanticWeb world while creating a fancy and useful tool. In a nutshell, RDF2Résumé would imply (1) to design a résumé ontology; (2) to be provide a simple tool (a simple piece of software such as a script) able to generate -let’s say- LaTeX code from an RDF file compliant with the aforementioned ontology; (3) in parallel to propose several final résumé templates; (4) and finally to realize a basic user-interface; (+) to give the possibility of automatically changing languages.