Using Provenance to Efficiently Propagate SPARQL Updates on RDF Source Graphs
| Autor: | Iman Naja, Nicholas Gibbins |
|---|---|
| Přispěvatelé: | Belhajjame, K., Gehani, A., Alper, P. |
| Rok vydání: | 2018 |
| Předmět: |
020203 distributed computing
Vocabulary Theoretical computer science Computer science media_common.quotation_subject 02 engineering and technology computer.file_format Graph 020204 information systems Scalability 0202 electrical engineering electronic engineering information engineering Rdf graph SPARQL RDF Semantic Web computer MathematicsofComputing_DISCRETEMATHEMATICS media_common |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783319983783 IPAW |
| Popis: | To promote sharing on the Semantic Web, information is published in machine-readable structured graphs expressed in RDF or OWL. This allows information consumers to create graphs using other source graphs. Information, however, is dynamic and when a source graph changes, graphs based on it need to be updated as well to preserve their integrity. To avoid regenerating a graph after one of its source graphs changes, since that approach can be expensive, we rely on its provenance to reduce the resources needed to reflect changes to its source graph. Accordingly, we expand the W3C PROV standard and present RGPROV, a vocabulary for RDF graph creation and update. RGPROV allows us to understand the dependencies a graph has on its source graphs and facilitates the propagation of the SPARQL updates applied to those source graphs through it. Additionally, we present a model that implements a modified DRed algorithm which makes use of RGPROV to enable partial modifications to be made on the RDF graph, thus reflecting the SPARQL updates on the source graph efficiently, without having to keep track of the provenance of each triple. Hence, only SPARQL updates are communicated, the need for complete re-derivation is done away with, and provenance is kept at the graph level making it better scalable. |
| Databáze: | OpenAIRE |
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