Fediscount: Shopping Online at a Federated Store Using FedUP as SPARQL Federation Engine

Julien Aimonier-Davat (1) , Minh-Hoang Dang (1) , Pascal Molli (1) , Brice Nédelec (1) , Hala Skaf-Molli (1)

1 LS2N - Laboratoire des Sciences du Numérique de Nantes

Processing SPARQL queries over large federations of SPARQL endpoints is essential for maintaining the Se- mantic Web decentralized. However, existing federation engines struggle to query more than a dozen of endpoints. We recently proposed FedUP, a new type of federation engine based on unions-over-joins query plans that outper- forms state-of-the-art federation engines by orders of magnitude on large federations. This demonstration paper introduces Fediscount, a federated online shopping application based on the FedShop benchmark, illustrating the capabilities of FedUP. The application is based on standard Semantic Web technologies, enabling end-users to shop online in a virtual federated store comprising 20, 100, or even 200 SPARQL endpoints. This breakthrough opens up promising new avenues for developing and deploying federated applications.

Mots clés: Semantic Web; Federated Query Processing; Source Selection

Domaines: Informatique [cs]

Julien Aimonier-Davat, Minh-Hoang Dang, Pascal Molli, Brice Nédelec, Hala Skaf-Molli. Fediscount: Shopping Online at a Federated Store Using FedUP as SPARQL Federation Engine. The ACM Web Conference (WWW ’24), May 2024, Singapore, Singapore. ⟨10.1145/3589335.3651249⟩. ⟨hal-04538264⟩