Modeling Evolving Data in Graphs While Preserving Backward Compatibility: The Power of RDF Quads

Modeling your data as a graph has a significant advantage: The schema does not need to be explicitly defined or specified ahead of time. Thus, you can add data to your graph without being constrained by any schema. One of the less recognized problems with data addition to a graph, however, is the potential for loss of backward compatibility with regard to queries designed before the changes are made to the data. Use of RDF Quads (W3C RDF1.1 Recommendation 25-FEB-2014) as your graph data model would allow schema evolution caused by data addition to your graph to preserve backward compatibility of all your pre-existing queries.

The tutorial also includes discussions on the following topics:

• new way of distinguishing among the various types of graphs: normal (discrete math) graph, RDF triples, Property Graph, RDF Quads.
• the new RDF# proposal for extension to RDF and SPARQL that allows explicit naming of RDF triples
• review of W3C SPARQL Query language and W3C SPARQL Update (used for DML)
• comparison between two popular graph query languages: SPARQL and PGQL
• use of RDF data for graph analytics
• review of W3C R2RML (RDB to RDF Mapping Language)
• methodology for creating relational-to-RDF (R2RML) mapping for a given relational schema.

All of these discussions are complemented with live demo on a freely downloadable VM running Oracle 19c.