Easy and complex: new perspectives for metadata modeling using RDF-star and Named Graphs

TL;DR

This paper explores how RDF-star and Named Graphs can be combined to simplify complex data models, enhance provenance, and maintain backward compatibility by effectively modeling meta-level information.

Contribution

It introduces a novel approach combining RDF-star and Named Graphs to improve meta-level data modeling and reduce complexity in RDF-based systems.

Findings

RDF-star enables statements about individual statements.

Combining RDF-star with Named Graphs facilitates meta-level data representation.

Meta-level modeling improves provenance and backward compatibility.

Abstract

The Resource Description Framework is well-established as a lingua franca for data modeling and is designed to integrate heterogeneous data at instance and schema level using statements. While RDF is conceptually simple, data models nevertheless get complex, when complex data needs to be represented. Additional levels of indirection with intermediate resources instead of simple properties lead to higher barriers for prospective users of the data. Based on three patterns, we argue that shifting information to a meta-level can not only be used to (1) provide provenance information, but can also help to (2) maintain backwards compatibility for existing models, and to (3) reduce the complexity of a data model. There are, however, multiple ways in RDF to use a meta-level, i.e., to provide additional statements about statements. With Named Graphs, there exists a well-established mechanism to describe groups of statements. Since its inception, however, it has been hard to make statements about single statements. With the introduction of RDF-star, a new way to provide data about single statements is now available. We show that the combination of RDF-star and Named Graphs is a viable solution to express data on a meta-level and propose that this meta-level should be used as first class citizen in data modeling.