ProvRPQ: An Interactive Tool for Provenance-Aware Regular Path Queries on RDF Graphs

Wang, Xin; Wang, Junhu

doi:10.1007/978-3-319-46922-5_44

Cited by 6 publications

(1 citation statement)

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“…DeFacto 87 is an application that implements PROV-O for deep fact validation, i.e., finding confirming sources for statements on the Web [134]. ProvRPQ is a tool for provenance-aware regular path queries (RPQs), which are used to express navigations over RDF graphs [135]. This interactive querying tool can clearly justify how paths conforming to RPQs can be navigated from source to target resources in RDF graphs by expanding conventional answers and introducing witness resources.…”

Section: Software Tools For Manipulating Rdf Provenancementioning

confidence: 99%

Provenance-Aware Knowledge Representation: A Survey of Data Models and Contextualized Knowledge Graphs

Sikos

Philp

2020

Data Sci. Eng.

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Expressing machine-interpretable statements in the form of subject-predicate-object triples is a well-established practice for capturing semantics of structured data. However, the standard used for representing these triples, RDF, inherently lacks the mechanism to attach provenance data, which would be crucial to make automatically generated and/or processed data authoritative. This paper is a critical review of data models, annotation frameworks, knowledge organization systems, serialization syntaxes, and algebras that enable provenance-aware RDF statements. The various approaches are assessed in terms of standard compliance, formal semantics, tuple type, vocabulary term usage, blank nodes, provenance granularity, and scalability. This can be used to advance existing solutions and help implementers to select the most suitable approach (or a combination of approaches) for their applications. Moreover, the analysis of the mechanisms and their limitations highlighted in this paper can serve as the basis for novel approaches in RDF-powered applications with increasing provenance needs.

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Section: Software Tools For Manipulating Rdf Provenancementioning

confidence: 99%