Passage: Ensuring Completeness and Responsiveness of Public SPARQL Endpoints with SPARQL Continuation Queries

Thi Hoang Thi PHAM, Gabriela Montoya, Brice Nédelec, hala skaf-molli, Pascal Molli

Track: Semantics and knowledge

Keywords: Semantic web, Public Knowledge Graph, SPARQL endpoint, Responsiveness, Completeness, Performances

TL;DR: We introduce the concept of SPARQL continuation queries. When a SPARQL endpoint interrupts a query, it returns partial results along with a SPARQL continuation query to retrieve the remaining results.

Abstract:

Being able to query online public knowledge graphs such as Wikidata or DBpedia is extremely valuable. However, these queries can
be interrupted due to the fair use policies enforced by SPARQL
endpoint providers, leading to incomplete results. While these policies help maintain responsiveness for public SPARQL endpoints,
they compromise the completeness of query results, limiting the
feasibility of various downstream tasks. Ideally, we shouldn’t have
to choose between completeness and responsiveness. To address
this issue, we introduce the concept of SPARQL continuation queries.
When a SPARQL endpoint interrupts a query, it returns partial
results along with a SPARQL continuation query to retrieve the
remaining results. If the continuation query is also interrupted,
the process repeats, generating further continuation queries until the complete results are obtained. In our experimention, we
show that our continuation server Passage ensures completeness
and responsiveness with performances in execution time similar to
BlazeGraph.

Submission Number: 2567