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RDF and property graph models have many similarities, such as using basicgraph concepts like nodes and edges. However, such models differ in theirmodeling approach, expressivity, serialization, and the nature of applications.RDF is the de-facto standard model for knowledge graphs on the Semantic Web andsupported by a rich ecosystem for inference and processing. The property graphmodel, in contrast, provides advantages in scalable graph analytical tasks,such as graph matching, path analysis, and graph traversal. RDF-star extendsRDF and allows capturing metadata as a first-class citizen. To tap on theadvantages of alternative models, the literature proposes different ways oftransforming knowledge graphs between property graphs and RDF. However, most ofthese approaches cannot provide complete transformations for RDF-star graphs.Hence, this paper provides a step towards transforming RDF-star graphs intoproperty graphs. In particular, we identify different cases to evaluatetransformation approaches from RDF-star to property graphs. Specifically, wecategorize two classes of transformation approaches and analyze them based onthe test cases. The obtained insights will form the foundation for buildingcomplete transformation approaches in the future.

Transforming RDF-star to Property Graphs: A Preliminary Analysis of Transformation Approaches -- extended version