Abstract
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.
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Notes
- 1.
If each triple’s provenance consists of only triple prov:wasDerivedFrom sourceTriple, a graph’s provenance graph would be a little larger than it. Even adding provenance information about only the activity and agent that produced a triple would result in the graph’s provenance graph being at minimum triple its size.
- 2.
Fuseki2 is available on https://jena.apache.org/documentation/fuseki2/.
- 3.
All Jena binary distributions are available on http://archive.apache.org/dist/jena/binaries/.
- 4.
Due to space restrictions, the preceding description and subsequent algorithm only focus on rdfs 5, 7, 9, and 11. Expanding them to cover the rest is straightforward.
- 5.
- 6.
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Naja, I., Gibbins, N. (2018). Using Provenance to Efficiently Propagate SPARQL Updates on RDF Source Graphs. In: Belhajjame, K., Gehani, A., Alper, P. (eds) Provenance and Annotation of Data and Processes. IPAW 2018. Lecture Notes in Computer Science(), vol 11017. Springer, Cham. https://doi.org/10.1007/978-3-319-98379-0_12
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