Recently I learned about the Resource Description Framework (RDF) as a core piece related to the JSON-LD credential format in the digital identity space. There is an intense debate in multiple communities from AI to data engineering to digital identity on how to represent data and provide relationships, or links, of that data to other data in a meaningful, useful way.

RDF

It seems the basic value proposition of RDF is reducing transaction cost of discovering and connecting data from multiple sources or datasets by having common ontologies, or vocabularies, across multiple websites, apps, or software services. Complexity of RDF and the overhead of recreating and modeling a data format to be usable in the RDF format seem to be the main drawbacks to RDF and they are major drawbacks.

JSON-LD Credential Format

RDF seems to be both implied and required by the JSON-LD credential format usage.

Middle Ground

A good middle ground seems to be to use graph databases like Neo4J that allow data to be modeled in an intuitive way even if that intuitive way is not semantically compatible or compliant with other similar data sources.

And it seems that in general industries or disciplines tend to gravitate toward a shared ontology or set of terms over time so maybe the need for RDF can be addressed sufficiently with AI text processing to reverse-engineer a meta-graph ontology for multiple contexts and then relate that meta-graph with an acceptable degree of accuracy.

References

• RDF Triple Stores vs. Labeled Property Graphs: What’s the Difference?
• Whatever Happened to the Semantic Web?
• JSON-LD 1.1 Specification

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Kent Bull