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

• DOI: 10.1007/s41019-020-00118-0
• Publication Date: 2020-05-08T09:02:40Z
• Authors: Leslie F. Sikos; Dean Philp
• Keywords: Serialization; Predicate (mathematical logic); JSON

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