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Efficient Provenance-Aware Querying of Graph Databases with Datalog

EasyChair Preprint no. 8978

9 pagesDate: October 3, 2022


We establish a translation between a formalism for dynamic programming over hypergraphs and the computation of semiring-based provenance for Datalog programs. The benefit of this translation is a new method for computing the provenance of Datalog programs for specific classes of semirings, which we apply to provenance-aware querying of graph databases. Theoretical results and practical optimizations lead to an efficient implementation using \textsc{Soufflé}, a state-of-the-art Datalog interpreter. Experimental results on real-world data suggest this approach to be efficient in practical contexts, competing with dedicated solutions for graphs.

Keyphrases: Datalog, dynamic programming, Graph Databases, Provenance, semirings, transportation networks

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Yann Ramusat and Silviu Maniu and Pierre Senellart},
  title = {Efficient Provenance-Aware Querying of Graph Databases with Datalog},
  howpublished = {EasyChair Preprint no. 8978},

  year = {EasyChair, 2022}}
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