MashQL: a query-by-diagram topping SPARQL
Proceedings of the 2nd international workshop on Ontologies and information systems for the semantic web
Towards Building a Knowledge Base for Research on Andean Weaving
BNCOD 26 Proceedings of the 26th British National Conference on Databases: Dataspace: The Final Frontier
3XL: Supporting efficient operations on very large OWL Lite triple-stores
Information Systems
The extension-based inference algorithm for pD*
Data & Knowledge Engineering
Editorial: Efficient incremental update and querying in AWETO RDF storage system
Data & Knowledge Engineering
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The growth of RDF data makes it imperative that an efficient mechanism for bulk-loading RDF graphs be supported. Thus, the paper proposes a bulk-load scheme that allows fast loading of arbitrarily large RDF graphs into a database. Specifically, three modes of load are supported: i) loading into an empty RDF graph, ii) appending to a non-empty RDF graph, and iii) concurrent loads into multiple graphs. The bulk-load scheme is implemented as part of Oracle Database Semantic Technologies and the performance experiments conducted with a variety of RDF graphs (from UniProt and synthesized data of Lehigh University Benchmark) demonstrate the scalability of the approach. The paper outlines the challenges involved in bulk-loading of large RDF graphs, describes the bulk-load scheme, discusses its implementation, and presents a performance study.