SemLAV: Local-As-View Mediation for SPARQL Queries

Abstract

Abstract. The Local-As-View (LAV) integration approach aims at querying heterogeneous data in dynamic environments. In LAV, data sources are described as views over a global schema which is used to pose queries. Query processing requires to generate and execute query rewritings, but for SPARQL queries, the LAV query rewritings may not be generated or executed in a reasonable time. In this paper, we present SemLAV, an alternative technique to process SPARQL queries over a LAV integration system without generating rewritings. SemLAV executes the query against a partial instance of the global schema which is built on-the-fly with data from the relevant views. The paper presents an experimental study for SemLAV, and compares its performance with traditional LAV-based query processing techniques. The results suggest that SemLAV scales up to SPARQL queries even over a large number of views, while it significantly outperforms traditional solutions.

Flexible Querying in Linked Data Sources

“…The main contribution in this framework is an algorithm for reformulating a user query into sub-queries over the data sources. In [14] a Local As View (LAV) approach called SemLAV is suggested for linked data integration. The authors provide and implement algorithms that reduce the number of revising of SPARQL queries over views describing data sources.…”

Implementing Master-Slave P2P Mapping Paradigm in Semantic Enterprise Information Integration: An Illustrative Case Study

“…Currently in the field of information integration, whether using a single global schema (including the global schema or global ontology) or using multiple schemas (such as federal schemas), or P2P data integration, the approaches of mapping between schemas can be categorized into three basic ways: GAV (Global As View) approach such as Mastro [3]; LAV (Local As View) approach such as SemLAV [4]; and GLAV ( Global-Local As View) approach such as Hyper [5].…”

Services for connecting and integrating big number of linked datasets

“…The above techniques have been also applied in the context of Linked Data [158]. In particular, SemLAV [159] is a LAV-based approach for processing in a scalable way SPARQL queries, by producing answers for SPARQL queries against large integration systems, whereas in [141], GAV SPARQL views are exploited for rewriting queries against a global vocabulary. Regarding other query rewriting approaches, in [244] techniques for query rewriting over taxonomy-based sources were proposed while in [148] the authors proposed a framework performing query rewriting for SPARQL queries.…”