Pelgrin, O., Taelman, R., Galárraga, L., & Hose, K. (2023). GLENDA: Querying RDF Archives with Full SPARQL. In The Semantic Web: ESWC 2023 Satellite Events (pp. 75–80). Springer. https://doi.org/10.34726/5411
The dynamicity of semantic data has propelled the research on RDF Archiving, i.e., the task of storing and making the full history of large RDF datasets accessible. However, existing archiving techniques fail to scale when confronted with very large RDF datasets and support only simple SPARQL queries. In this demonstration, we therefore showcase GLENDA, a system that can run full SPARQL 1.1 compliant queries over large RDF archives. We achieve this through a multi-snapshot change-based storage architecture that we interface using the Comunica query engine. Thanks to this integration we demonstrate that fast SPARQL query processing over multiple versions of a knowledge graph is possible. Moreover, our demonstration provides different statistics about the history of RDF datasets that can be useful for tasks beyond querying and by providing insights about the evolution dynamics of the data.
en
Project (external):
Danish Council for Independent Research (DFF) European Union’s Horizon 2020 Research Foundation – Flanders (FWO)
