Virtual RDF stores for Property Graphs

Over the past few years, knowledge graphs have emerged to address the need of extracting and combining multiple data sources [1]. Their flexible structure makes them suitable to integrate heterogeneous data. This has propelled many advances in query processing over knowledge graphs. However, there are many graph data models and query languages for graph data [2]. In this project idea, we focus on RDF, which is the proposed standard by the World Web Wide Consortium, and property graphs, that is the underlying model for several graph database engines. The goal of this Master's thesis is to implement a mapping language as that allows to map data from property graphs to RDF, and to implement virtual RDF stores on top of Property Graph stores. This thesis proposes a mapping language based on the R2RML language, which is the mapping language recommended by the W3C to map relational databases to RDF [3].

1. Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, Claudio Gutierrez, Sabrina Kirrane, José Emilio Labra Gayo, Roberto Navigli, Sebastian Neumaier, Axel-Cyrille Ngonga Ngomo, Axel Polleres, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan F. Sequeda, Steffen Staab, Antoine Zimmermann: Knowledge Graphs. ACM Comput. Surv. 54(4): 71:1-71:37 (2022) https://dl.acm.org/doi/10.1145/3447772
2. Renzo Angles, Marcelo Arenas, Pablo Barceló, Aidan Hogan, Juan L. Reutter, Domagoj Vrgoc:
   Foundations of Modern Query Languages for Graph Databases. ACM Comput. Surv. 50(5): 68:1-68:40 (2017) https://dl.acm.org/doi/10.1145/3104031
3. Souripriya Das, Seema Sundara, and Richard Cyganiak. R2RML: RDB to RDF Mapping Language. http://www.w3.org/TR/r2rml/.